Overview

Dataset statistics

Number of variables67
Number of observations9309
Missing cells160797
Missing cells (%)25.8%
Duplicate rows3
Duplicate rows (%)< 0.1%
Total size in memory5.0 MiB
Average record size in memory561.0 B

Variable types

Text9
Categorical31
Numeric25
Boolean1
DateTime1

Dataset

DescriptionSW기업의 마케팅 활동을 지원하기 위하여 공공부문(행정기관, 지자체, 공공기관)의 소프트웨어 및 정보통신기술 장비, 정보보호 예정수요를 조사하여 예정조사 결과 발표 -컬럼명: 기관명, 기관유형, 총예산, HW 구매예산, 상용SW 구매예산, SW구축 사업계획 예산, 품목별 용도, 구매수량, 분기별 금액, 재원 등
URLhttps://www.data.go.kr/data/15075001/fileData.do

Alerts

Dataset has 3 (< 0.1%) duplicate rowsDuplicates
하드웨어 구매예산정보통신기술-소분류 is highly imbalanced (55.4%)Imbalance
하드웨어 구매예산리스여부 is highly imbalanced (84.3%)Imbalance
상용소프트웨어예산구분코드 is highly imbalanced (50.9%)Imbalance
상용소프트웨어예산정보보호사업 구분코드 is highly imbalanced (74.2%)Imbalance
상용소프트웨어예산정보보호사업 구분명 is highly imbalanced (74.2%)Imbalance
소프트웨어구축예산신사업유형구분 is highly imbalanced (62.2%)Imbalance
소프트웨어구축예산정보보호사업 구분코드 is highly imbalanced (69.3%)Imbalance
소프트웨어구축예산정보보호사업 구분명 is highly imbalanced (69.3%)Imbalance
소프트웨어구축예산보안성지속서비스 세부 요율(퍼센트) is highly imbalanced (90.3%)Imbalance
소프트웨어구축예산대기업 참여제한 예외인정 여부 is highly imbalanced (58.9%)Imbalance
소프트웨어구축예산총사업종료 is highly imbalanced (66.4%)Imbalance
소프트웨어구축예산당해사업시작 is highly imbalanced (55.1%)Imbalance
소프트웨어구축예산당해사업종료 is highly imbalanced (65.9%)Imbalance
하드웨어 구매예산품목명(용도) has 5713 (61.4%) missing valuesMissing
하드웨어 구매예산구매예산 has 5713 (61.4%) missing valuesMissing
하드웨어 구매예산구매수량 has 5713 (61.4%) missing valuesMissing
하드웨어 구매예산1분기금액 has 5713 (61.4%) missing valuesMissing
하드웨어 구매예산2분기금액 has 5713 (61.4%) missing valuesMissing
하드웨어 구매예산3분기금액 has 5713 (61.4%) missing valuesMissing
하드웨어 구매예산4분기금액 has 5713 (61.4%) missing valuesMissing
하드웨어 구매예산리스여부 has 5713 (61.4%) missing valuesMissing
하드웨어 구매예산합계 has 5713 (61.4%) missing valuesMissing
하드웨어 구매예산사업명 has 7473 (80.3%) missing valuesMissing
하드웨어 구매예산사업개요 has 7474 (80.3%) missing valuesMissing
하드웨어 구매예산사업기간 has 7473 (80.3%) missing valuesMissing
하드웨어 구매예산사업예산 has 7475 (80.3%) missing valuesMissing
상용소프트웨어예산품목명(용도) has 5637 (60.6%) missing valuesMissing
상용소프트웨어예산구매예산 has 5637 (60.6%) missing valuesMissing
상용소프트웨어예산1분기금액 has 5637 (60.6%) missing valuesMissing
상용소프트웨어예산2분기금액 has 5637 (60.6%) missing valuesMissing
상용소프트웨어예산3분기금액 has 5637 (60.6%) missing valuesMissing
상용소프트웨어예산4분기금액 has 5637 (60.6%) missing valuesMissing
상용소프트웨어예산합계 has 5637 (60.6%) missing valuesMissing
소프트웨어구축예산사업명 has 2175 (23.4%) missing valuesMissing
소프트웨어구축예산사업개요 has 2275 (24.4%) missing valuesMissing
소프트웨어구축예산정보보호사업 비율(퍼센트) has 7558 (81.2%) missing valuesMissing
소프트웨어구축예산총사업시작 has 2175 (23.4%) missing valuesMissing
소프트웨어구축예산총사업금액 has 2175 (23.4%) missing valuesMissing
소프트웨어구축예산당해사업금액 has 2175 (23.4%) missing valuesMissing
소프트웨어구축예산분리발주예산 has 2175 (23.4%) missing valuesMissing
소프트웨어구축예산하드웨어장비도입금액 has 2175 (23.4%) missing valuesMissing
소프트웨어구축예산하드웨어유지보수금액 has 7341 (78.9%) missing valuesMissing
소프트웨어구축예산상용소프트웨어도입금액 has 2175 (23.4%) missing valuesMissing
소프트웨어구축예산상용소프트웨어유지보수요율(퍼센트) has 7627 (81.9%) missing valuesMissing
하드웨어 구매예산구매예산 is highly skewed (γ1 = 39.83669076)Skewed
하드웨어 구매예산구매수량 is highly skewed (γ1 = 58.05216705)Skewed
하드웨어 구매예산1분기금액 is highly skewed (γ1 = 57.66305274)Skewed
하드웨어 구매예산2분기금액 is highly skewed (γ1 = 34.04038945)Skewed
하드웨어 구매예산3분기금액 is highly skewed (γ1 = 26.655733)Skewed
하드웨어 구매예산4분기금액 is highly skewed (γ1 = 31.77546374)Skewed
하드웨어 구매예산합계 is highly skewed (γ1 = 39.83669076)Skewed
하드웨어 구매예산사업예산 is highly skewed (γ1 = 30.60242007)Skewed
상용소프트웨어예산1분기금액 is highly skewed (γ1 = 38.6974264)Skewed
상용소프트웨어예산3분기금액 is highly skewed (γ1 = 22.79288652)Skewed
상용소프트웨어예산4분기금액 is highly skewed (γ1 = 20.41270269)Skewed
소프트웨어구축예산총사업금액 is highly skewed (γ1 = 24.40941738)Skewed
소프트웨어구축예산분리발주예산 is highly skewed (γ1 = 38.10349693)Skewed
소프트웨어구축예산하드웨어장비도입금액 is highly skewed (γ1 = 33.26157518)Skewed
소프트웨어구축예산상용소프트웨어도입금액 is highly skewed (γ1 = 42.05079245)Skewed
총예산 has 343 (3.7%) zerosZeros
하드웨어구매예산 has 2436 (26.2%) zerosZeros
상용소프트웨어구매예산 has 2001 (21.5%) zerosZeros
소프트웨어구축 사업계획 예산 has 582 (6.3%) zerosZeros
하드웨어 구매예산1분기금액 has 1863 (20.0%) zerosZeros
하드웨어 구매예산2분기금액 has 2373 (25.5%) zerosZeros
하드웨어 구매예산3분기금액 has 3002 (32.2%) zerosZeros
하드웨어 구매예산4분기금액 has 3117 (33.5%) zerosZeros
상용소프트웨어예산1분기금액 has 1964 (21.1%) zerosZeros
상용소프트웨어예산2분기금액 has 2664 (28.6%) zerosZeros
상용소프트웨어예산3분기금액 has 2968 (31.9%) zerosZeros
상용소프트웨어예산4분기금액 has 3069 (33.0%) zerosZeros
소프트웨어구축예산분리발주예산 has 6978 (75.0%) zerosZeros
소프트웨어구축예산하드웨어장비도입금액 has 6837 (73.4%) zerosZeros
소프트웨어구축예산하드웨어유지보수금액 has 1160 (12.5%) zerosZeros
소프트웨어구축예산상용소프트웨어도입금액 has 6838 (73.5%) zerosZeros
소프트웨어구축예산상용소프트웨어유지보수요율(퍼센트) has 987 (10.6%) zerosZeros

Reproduction

Analysis started2023-12-12 17:51:52.727653
Analysis finished2023-12-12 17:51:56.859196
Duration4.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct2226
Distinct (%)23.9%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
2023-12-13T02:51:57.123800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length8.195832
Min length3

Characters and Unicode

Total characters76295
Distinct characters371
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique984 ?
Unique (%)10.6%

Sample

1st row(재)강원테크노파크
2nd row(재)건설기술교육원
3rd row(재)건설기술교육원
4th row(재)경기문화재단 경기도박물관
5th row(재)경기콘텐츠진흥원
ValueCountFrequency (%)
경기도 424
 
3.5%
서울특별시 335
 
2.8%
인천광역시 169
 
1.4%
재단법인 166
 
1.4%
전라남도 143
 
1.2%
충청남도 94
 
0.8%
한국중부발전(주 93
 
0.8%
경상남도 90
 
0.7%
경기도청 86
 
0.7%
안양시청 73
 
0.6%
Other values (2171) 10369
86.1%
2023-12-13T02:51:57.613101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3726
 
4.9%
3095
 
4.1%
3076
 
4.0%
2733
 
3.6%
2590
 
3.4%
2194
 
2.9%
1781
 
2.3%
1612
 
2.1%
1583
 
2.1%
1581
 
2.1%
Other values (361) 52324
68.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 72904
95.6%
Space Separator 2733
 
3.6%
Open Punctuation 266
 
0.3%
Close Punctuation 266
 
0.3%
Uppercase Letter 67
 
0.1%
Decimal Number 31
 
< 0.1%
Dash Punctuation 11
 
< 0.1%
Other Punctuation 9
 
< 0.1%
Other Symbol 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3726
 
5.1%
3095
 
4.2%
3076
 
4.2%
2590
 
3.6%
2194
 
3.0%
1781
 
2.4%
1612
 
2.2%
1583
 
2.2%
1581
 
2.2%
1450
 
2.0%
Other values (338) 50216
68.9%
Decimal Number
ValueCountFrequency (%)
1 10
32.3%
8 7
22.6%
5 3
 
9.7%
9 3
 
9.7%
4 3
 
9.7%
6 2
 
6.5%
3 1
 
3.2%
2 1
 
3.2%
0 1
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
K 17
25.4%
D 12
17.9%
N 12
17.9%
P 9
13.4%
S 5
 
7.5%
C 4
 
6.0%
E 4
 
6.0%
A 4
 
6.0%
Space Separator
ValueCountFrequency (%)
2733
100.0%
Open Punctuation
ValueCountFrequency (%)
( 266
100.0%
Close Punctuation
ValueCountFrequency (%)
) 266
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Punctuation
ValueCountFrequency (%)
. 9
100.0%
Other Symbol
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 72912
95.6%
Common 3316
 
4.3%
Latin 67
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3726
 
5.1%
3095
 
4.2%
3076
 
4.2%
2590
 
3.6%
2194
 
3.0%
1781
 
2.4%
1612
 
2.2%
1583
 
2.2%
1581
 
2.2%
1450
 
2.0%
Other values (339) 50224
68.9%
Common
ValueCountFrequency (%)
2733
82.4%
( 266
 
8.0%
) 266
 
8.0%
- 11
 
0.3%
1 10
 
0.3%
. 9
 
0.3%
8 7
 
0.2%
5 3
 
0.1%
9 3
 
0.1%
4 3
 
0.1%
Other values (4) 5
 
0.2%
Latin
ValueCountFrequency (%)
K 17
25.4%
D 12
17.9%
N 12
17.9%
P 9
13.4%
S 5
 
7.5%
C 4
 
6.0%
E 4
 
6.0%
A 4
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 72904
95.6%
ASCII 3383
 
4.4%
None 8
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3726
 
5.1%
3095
 
4.2%
3076
 
4.2%
2590
 
3.6%
2194
 
3.0%
1781
 
2.4%
1612
 
2.2%
1583
 
2.2%
1581
 
2.2%
1450
 
2.0%
Other values (338) 50216
68.9%
ASCII
ValueCountFrequency (%)
2733
80.8%
( 266
 
7.9%
) 266
 
7.9%
K 17
 
0.5%
D 12
 
0.4%
N 12
 
0.4%
- 11
 
0.3%
1 10
 
0.3%
. 9
 
0.3%
P 9
 
0.3%
Other values (12) 38
 
1.1%
None
ValueCountFrequency (%)
8
100.0%

기관유형
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
지자체
4124 
공공기관
3591 
국가기관
1420 
기타
 
174

Length

Max length4
Median length4
Mean length3.5196047
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공공기관
2nd row공공기관
3rd row공공기관
4th row공공기관
5th row공공기관

Common Values

ValueCountFrequency (%)
지자체 4124
44.3%
공공기관 3591
38.6%
국가기관 1420
 
15.3%
기타 174
 
1.9%

Length

2023-12-13T02:51:57.810294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:51:57.937141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지자체 4124
44.3%
공공기관 3591
38.6%
국가기관 1420
 
15.3%
기타 174
 
1.9%

총예산
Real number (ℝ)

ZEROS 

Distinct1713
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1023025 × 1010
Minimum0
Maximum6.50295 × 1011
Zeros343
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:51:58.344586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6402400
Q12.547289 × 108
median1.247195 × 109
Q35.8216355 × 109
95-th percentile6.4871375 × 1010
Maximum6.50295 × 1011
Range6.50295 × 1011
Interquartile range (IQR)5.5669066 × 109

Descriptive statistics

Standard deviation3.6718759 × 1010
Coefficient of variation (CV)3.3310966
Kurtosis173.69024
Mean1.1023025 × 1010
Median Absolute Deviation (MAD)1.202719 × 109
Skewness11.137288
Sum1.0261334 × 1014
Variance1.3482673 × 1021
MonotonicityNot monotonic
2023-12-13T02:51:58.537674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 343
 
3.7%
87270910310 203
 
2.2%
16569861000 93
 
1.0%
64871375000 86
 
0.9%
15088935880 73
 
0.8%
21081042086 73
 
0.8%
4996371000 71
 
0.8%
53250000000 60
 
0.6%
11978808413 56
 
0.6%
2356030000 53
 
0.6%
Other values (1703) 8198
88.1%
ValueCountFrequency (%)
0 343
3.7%
500000 1
 
< 0.1%
660000 1
 
< 0.1%
880000 1
 
< 0.1%
900000 1
 
< 0.1%
1000000 3
 
< 0.1%
1200000 3
 
< 0.1%
1300000 1
 
< 0.1%
1309000 1
 
< 0.1%
1320000 1
 
< 0.1%
ValueCountFrequency (%)
650295000000 17
 
0.2%
317437000000 13
 
0.1%
214714000000 2
 
< 0.1%
147095000000 38
 
0.4%
139437000000 23
 
0.2%
112970000000 10
 
0.1%
92232000000 7
 
0.1%
87270910310 203
2.2%
80276720000 30
 
0.3%
78340567000 5
 
0.1%

하드웨어구매예산
Real number (ℝ)

ZEROS 

Distinct851
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.942451 × 109
Minimum0
Maximum3.00683 × 1011
Zeros2436
Zeros (%)26.2%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:51:58.738660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.68 × 108
Q39.9175 × 108
95-th percentile5.159945 × 109
Maximum3.00683 × 1011
Range3.00683 × 1011
Interquartile range (IQR)9.9175 × 108

Descriptive statistics

Standard deviation1.3672874 × 1010
Coefficient of variation (CV)7.0389801
Kurtosis353.11815
Mean1.942451 × 109
Median Absolute Deviation (MAD)1.68 × 108
Skewness17.833898
Sum1.8082276 × 1013
Variance1.8694748 × 1020
MonotonicityNot monotonic
2023-12-13T02:51:58.927962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2436
 
26.2%
5159945000 203
 
2.2%
9489556000 93
 
1.0%
1972383000 86
 
0.9%
3342687880 73
 
0.8%
2841568000 73
 
0.8%
2329283000 71
 
0.8%
2515000000 60
 
0.6%
1243191560 56
 
0.6%
1202900000 53
 
0.6%
Other values (841) 6105
65.6%
ValueCountFrequency (%)
0 2436
26.2%
1000000 3
 
< 0.1%
1070000 1
 
< 0.1%
1110000 1
 
< 0.1%
1200000 1
 
< 0.1%
1250000 1
 
< 0.1%
1300000 1
 
< 0.1%
1330000 1
 
< 0.1%
1412000 1
 
< 0.1%
1500000 1
 
< 0.1%
ValueCountFrequency (%)
300683000000 13
 
0.1%
164909000000 17
0.2%
94164000000 2
 
< 0.1%
51712060000 12
 
0.1%
35570035000 5
 
0.1%
27822148000 10
 
0.1%
23890384000 4
 
< 0.1%
21170000000 23
0.2%
19692487640 29
0.3%
19285000000 37
0.4%

상용소프트웨어구매예산
Real number (ℝ)

ZEROS 

Distinct924
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.414787 × 108
Minimum0
Maximum1.3055798 × 1010
Zeros2001
Zeros (%)21.5%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:51:59.130068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12530000
median1.005 × 108
Q33.20388 × 108
95-th percentile2.551057 × 109
Maximum1.3055798 × 1010
Range1.3055798 × 1010
Interquartile range (IQR)3.17858 × 108

Descriptive statistics

Standard deviation1.0335393 × 109
Coefficient of variation (CV)2.3410853
Kurtosis43.095508
Mean4.414787 × 108
Median Absolute Deviation (MAD)1.005 × 108
Skewness5.3499581
Sum4.1097252 × 1012
Variance1.0682034 × 1018
MonotonicityNot monotonic
2023-12-13T02:51:59.313685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2001
 
21.5%
2574878000 203
 
2.2%
2400305000 93
 
1.0%
504262000 86
 
0.9%
1316701000 73
 
0.8%
318605000 73
 
0.8%
465138000 71
 
0.8%
1000000 71
 
0.8%
1470000000 60
 
0.6%
2223939000 56
 
0.6%
Other values (914) 6522
70.1%
ValueCountFrequency (%)
0 2001
21.5%
100000 1
 
< 0.1%
115000 1
 
< 0.1%
200000 1
 
< 0.1%
242000 4
 
< 0.1%
250000 2
 
< 0.1%
270000 2
 
< 0.1%
300000 1
 
< 0.1%
388000 1
 
< 0.1%
400000 3
 
< 0.1%
ValueCountFrequency (%)
13055798000 13
 
0.1%
8710358000 13
 
0.1%
7279608000 12
 
0.1%
6297238000 12
 
0.1%
5661600000 17
0.2%
5439300200 6
 
0.1%
5254436000 13
 
0.1%
5050087519 37
0.4%
4800000000 3
 
< 0.1%
4493100000 17
0.2%
Distinct1522
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.6390938 × 109
Minimum0
Maximum4.79724 × 1011
Zeros582
Zeros (%)6.3%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:51:59.465146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.1558 × 108
median6.5 × 108
Q33.7115716 × 109
95-th percentile5.5318521 × 1010
Maximum4.79724 × 1011
Range4.79724 × 1011
Interquartile range (IQR)3.5959916 × 109

Descriptive statistics

Standard deviation2.8228256 × 1010
Coefficient of variation (CV)3.267502
Kurtosis143.12782
Mean8.6390938 × 109
Median Absolute Deviation (MAD)6.398 × 108
Skewness9.7310572
Sum8.0421324 × 1013
Variance7.9683444 × 1020
MonotonicityNot monotonic
2023-12-13T02:51:59.613226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 582
 
6.3%
79536087310 203
 
2.2%
4680000000 93
 
1.0%
62394730000 86
 
0.9%
10429547000 73
 
0.8%
17920869086 73
 
0.8%
2201950000 71
 
0.8%
49265000000 60
 
0.6%
8511677853 56
 
0.6%
810980000 53
 
0.6%
Other values (1512) 7959
85.5%
ValueCountFrequency (%)
0 582
6.3%
500000 1
 
< 0.1%
660000 1
 
< 0.1%
710000 1
 
< 0.1%
880000 1
 
< 0.1%
1200000 8
 
0.1%
1300000 1
 
< 0.1%
1320000 1
 
< 0.1%
1325000 2
 
< 0.1%
1332000 1
 
< 0.1%
ValueCountFrequency (%)
479724000000 17
 
0.2%
147095000000 38
 
0.4%
120550000000 2
 
< 0.1%
116961000000 23
 
0.2%
90832000000 7
 
0.1%
83991122700 10
 
0.1%
79536087310 203
2.2%
79335720000 30
 
0.3%
68708000000 5
 
0.1%
66108151500 14
 
0.2%
Distinct2610
Distinct (%)72.6%
Missing5713
Missing (%)61.4%
Memory size72.9 KiB
2023-12-13T02:51:59.922966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length39
Mean length11.201891
Min length2

Characters and Unicode

Total characters40282
Distinct characters509
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2347 ?
Unique (%)65.3%

Sample

1st row지상라이다 공공측량성과심사용 H/W
2nd rowLiDAR 성과심사 프로그램 및 장비 구매
3rd row전산장비(Workstation) 구매
4th rowPC 및 모니터 구매
5th rowPC(정책홍보)
ValueCountFrequency (%)
교체 495
 
5.6%
구입 352
 
4.0%
260
 
2.9%
pc 258
 
2.9%
구매 228
 
2.6%
노후 200
 
2.3%
업무용 185
 
2.1%
컴퓨터 184
 
2.1%
네트워크 168
 
1.9%
모니터 157
 
1.8%
Other values (2405) 6378
71.9%
2023-12-13T02:52:00.437101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5270
 
13.1%
1084
 
2.7%
914
 
2.3%
804
 
2.0%
) 770
 
1.9%
( 770
 
1.9%
747
 
1.9%
C 720
 
1.8%
720
 
1.8%
709
 
1.8%
Other values (499) 27774
68.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29418
73.0%
Space Separator 5270
 
13.1%
Uppercase Letter 3021
 
7.5%
Close Punctuation 786
 
2.0%
Open Punctuation 786
 
2.0%
Decimal Number 415
 
1.0%
Lowercase Letter 360
 
0.9%
Other Punctuation 130
 
0.3%
Dash Punctuation 78
 
0.2%
Connector Punctuation 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1084
 
3.7%
914
 
3.1%
804
 
2.7%
747
 
2.5%
720
 
2.4%
709
 
2.4%
694
 
2.4%
684
 
2.3%
671
 
2.3%
602
 
2.0%
Other values (428) 21789
74.1%
Uppercase Letter
ValueCountFrequency (%)
C 720
23.8%
P 686
22.7%
S 197
 
6.5%
V 193
 
6.4%
T 172
 
5.7%
L 160
 
5.3%
I 154
 
5.1%
A 118
 
3.9%
D 112
 
3.7%
N 107
 
3.5%
Other values (15) 402
13.3%
Lowercase Letter
ValueCountFrequency (%)
c 71
19.7%
p 40
11.1%
o 36
10.0%
v 30
8.3%
t 30
8.3%
n 21
 
5.8%
e 20
 
5.6%
i 16
 
4.4%
r 15
 
4.2%
a 13
 
3.6%
Other values (13) 68
18.9%
Decimal Number
ValueCountFrequency (%)
2 170
41.0%
3 78
18.8%
0 57
 
13.7%
4 42
 
10.1%
1 41
 
9.9%
5 7
 
1.7%
8 6
 
1.4%
7 5
 
1.2%
9 5
 
1.2%
6 4
 
1.0%
Other Punctuation
ValueCountFrequency (%)
, 95
73.1%
/ 30
 
23.1%
. 3
 
2.3%
· 2
 
1.5%
Close Punctuation
ValueCountFrequency (%)
) 770
98.0%
] 16
 
2.0%
Open Punctuation
ValueCountFrequency (%)
( 770
98.0%
[ 16
 
2.0%
Math Symbol
ValueCountFrequency (%)
+ 1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
5270
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29418
73.0%
Common 7483
 
18.6%
Latin 3381
 
8.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1084
 
3.7%
914
 
3.1%
804
 
2.7%
747
 
2.5%
720
 
2.4%
709
 
2.4%
694
 
2.4%
684
 
2.3%
671
 
2.3%
602
 
2.0%
Other values (428) 21789
74.1%
Latin
ValueCountFrequency (%)
C 720
21.3%
P 686
20.3%
S 197
 
5.8%
V 193
 
5.7%
T 172
 
5.1%
L 160
 
4.7%
I 154
 
4.6%
A 118
 
3.5%
D 112
 
3.3%
N 107
 
3.2%
Other values (38) 762
22.5%
Common
ValueCountFrequency (%)
5270
70.4%
) 770
 
10.3%
( 770
 
10.3%
2 170
 
2.3%
, 95
 
1.3%
3 78
 
1.0%
- 78
 
1.0%
0 57
 
0.8%
4 42
 
0.6%
1 41
 
0.5%
Other values (13) 112
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29418
73.0%
ASCII 10861
 
27.0%
None 2
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5270
48.5%
) 770
 
7.1%
( 770
 
7.1%
C 720
 
6.6%
P 686
 
6.3%
S 197
 
1.8%
V 193
 
1.8%
T 172
 
1.6%
2 170
 
1.6%
L 160
 
1.5%
Other values (59) 1753
 
16.1%
Hangul
ValueCountFrequency (%)
1084
 
3.7%
914
 
3.1%
804
 
2.7%
747
 
2.5%
720
 
2.4%
709
 
2.4%
694
 
2.4%
684
 
2.3%
671
 
2.3%
602
 
2.0%
Other values (428) 21789
74.1%
None
ValueCountFrequency (%)
· 2
100.0%
Arrows
ValueCountFrequency (%)
1
100.0%
Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
<NA>
5713 
PC 및 주변기기
1007 
통신기기
979 
서버 및 관련장비
 
541
정보보호장비
 
446
Other values (3)
623 

Length

Max length9
Median length4
Mean length4.9663766
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 5713
61.4%
PC 및 주변기기 1007
 
10.8%
통신기기 979
 
10.5%
서버 및 관련장비 541
 
5.8%
정보보호장비 446
 
4.8%
기타 HW 364
 
3.9%
방송기기 155
 
1.7%
기반시설 104
 
1.1%

Length

2023-12-13T02:52:00.590104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:00.699526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5713
44.7%
1548
 
12.1%
pc 1007
 
7.9%
주변기기 1007
 
7.9%
통신기기 979
 
7.7%
서버 541
 
4.2%
관련장비 541
 
4.2%
정보보호장비 446
 
3.5%
기타 364
 
2.9%
hw 364
 
2.9%
Other values (2) 259
 
2.0%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
<NA>
5713 
컴퓨팅장비
2016 
네트워크장비
979 
정보보호장비
 
446
방송장비
 
155

Length

Max length6
Median length4
Mean length4.5227199
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 5713
61.4%
컴퓨팅장비 2016
 
21.7%
네트워크장비 979
 
10.5%
정보보호장비 446
 
4.8%
방송장비 155
 
1.7%

Length

2023-12-13T02:52:00.843132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:00.962732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5713
61.4%
컴퓨팅장비 2016
 
21.7%
네트워크장비 979
 
10.5%
정보보호장비 446
 
4.8%
방송장비 155
 
1.7%
Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
<NA>
5713 
기타 컴퓨팅
1475 
스위치
 
407
서버
 
351
네트워크 보안장비
 
335
Other values (10)
1028 

Length

Max length9
Median length4
Mean length4.4203459
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 5713
61.4%
기타 컴퓨팅 1475
 
15.8%
스위치 407
 
4.4%
서버 351
 
3.8%
네트워크 보안장비 335
 
3.6%
정보보안 304
 
3.3%
물리보안 142
 
1.5%
기타 네트워크 134
 
1.4%
스토리지 125
 
1.3%
영상장비 98
 
1.1%
Other values (5) 225
 
2.4%

Length

2023-12-13T02:52:01.079226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5713
50.8%
기타 1609
 
14.3%
컴퓨팅 1475
 
13.1%
네트워크 469
 
4.2%
스위치 407
 
3.6%
서버 351
 
3.1%
보안장비 335
 
3.0%
정보보안 304
 
2.7%
물리보안 142
 
1.3%
스토리지 125
 
1.1%
Other values (6) 323
 
2.9%
Distinct41
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
<NA>
5713 
PC (사무용)
1007 
기타
740 
네트워크 보안장비
 
335
L2
 
164
Other values (36)
1350 

Length

Max length20
Median length4
Mean length4.6333656
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 5713
61.4%
PC (사무용) 1007
 
10.8%
기타 740
 
7.9%
네트워크 보안장비 335
 
3.6%
L2 164
 
1.8%
X86 146
 
1.6%
CCTV 109
 
1.2%
보안관리 108
 
1.2%
기반시설 104
 
1.1%
스토리지 104
 
1.1%
Other values (31) 779
 
8.4%

Length

2023-12-13T02:52:01.207436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5713
51.4%
사무용 1007
 
9.1%
pc 1007
 
9.1%
기타 806
 
7.2%
네트워크 335
 
3.0%
보안장비 335
 
3.0%
l2 164
 
1.5%
x86 146
 
1.3%
cctv 109
 
1.0%
보안관리 108
 
1.0%
Other values (44) 1390
 
12.5%

하드웨어 구매예산구매예산
Real number (ℝ)

MISSING  SKEWED 

Distinct1656
Distinct (%)46.1%
Missing5713
Missing (%)61.4%
Infinite0
Infinite (%)0.0%
Mean3.6087712 × 108
Minimum69000
Maximum2.34584 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:01.334835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum69000
5-th percentile2809246.8
Q116701915
median47000000
Q31.389625 × 108
95-th percentile7.1399259 × 108
Maximum2.34584 × 1011
Range2.3458393 × 1011
Interquartile range (IQR)1.2226058 × 108

Descriptive statistics

Standard deviation4.6439739 × 109
Coefficient of variation (CV)12.868574
Kurtosis1870.3715
Mean3.6087712 × 108
Median Absolute Deviation (MAD)39000000
Skewness39.836691
Sum1.2977141 × 1012
Variance2.1566494 × 1019
MonotonicityNot monotonic
2023-12-13T02:52:01.481460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000000 86
 
0.9%
100000000 67
 
0.7%
20000000 65
 
0.7%
30000000 54
 
0.6%
10000000 45
 
0.5%
25000000 42
 
0.5%
40000000 42
 
0.5%
60000000 39
 
0.4%
15000000 34
 
0.4%
22000000 34
 
0.4%
Other values (1646) 3088
33.2%
(Missing) 5713
61.4%
ValueCountFrequency (%)
69000 1
 
< 0.1%
250000 1
 
< 0.1%
300000 2
< 0.1%
336000 1
 
< 0.1%
366000 1
 
< 0.1%
420000 1
 
< 0.1%
500000 2
< 0.1%
520000 3
< 0.1%
600000 2
< 0.1%
700000 3
< 0.1%
ValueCountFrequency (%)
234584000000 1
< 0.1%
94164000000 1
< 0.1%
74702484000 1
< 0.1%
50381960000 1
< 0.1%
33513000000 1
< 0.1%
29925000000 1
< 0.1%
27005345000 1
< 0.1%
26269910000 1
< 0.1%
19895327000 1
< 0.1%
19589261000 1
< 0.1%

하드웨어 구매예산구매수량
Real number (ℝ)

MISSING  SKEWED 

Distinct284
Distinct (%)7.9%
Missing5713
Missing (%)61.4%
Infinite0
Infinite (%)0.0%
Mean239.12319
Minimum1
Maximum457828
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:01.644454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q320
95-th percentile295.5
Maximum457828
Range457827
Interquartile range (IQR)19

Descriptive statistics

Standard deviation7720.3195
Coefficient of variation (CV)32.28595
Kurtosis3436.2004
Mean239.12319
Median Absolute Deviation (MAD)2
Skewness58.052167
Sum859887
Variance59603334
MonotonicityNot monotonic
2023-12-13T02:52:01.781354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1303
 
14.0%
2 427
 
4.6%
10 138
 
1.5%
3 133
 
1.4%
4 125
 
1.3%
5 108
 
1.2%
20 87
 
0.9%
6 68
 
0.7%
30 64
 
0.7%
100 56
 
0.6%
Other values (274) 1087
 
11.7%
(Missing) 5713
61.4%
ValueCountFrequency (%)
1 1303
14.0%
2 427
 
4.6%
3 133
 
1.4%
4 125
 
1.3%
5 108
 
1.2%
6 68
 
0.7%
7 42
 
0.5%
8 51
 
0.5%
9 26
 
0.3%
10 138
 
1.5%
ValueCountFrequency (%)
457828 1
< 0.1%
49875 1
< 0.1%
30762 1
< 0.1%
20000 1
< 0.1%
15260 1
< 0.1%
10286 1
< 0.1%
9796 1
< 0.1%
8785 1
< 0.1%
8708 1
< 0.1%
8000 1
< 0.1%

하드웨어 구매예산1분기금액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct921
Distinct (%)25.6%
Missing5713
Missing (%)61.4%
Infinite0
Infinite (%)0.0%
Mean1.3358786 × 108
Minimum0
Maximum2.34584 × 1011
Zeros1863
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:01.903904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q330000000
95-th percentile2.229265 × 108
Maximum2.34584 × 1011
Range2.34584 × 1011
Interquartile range (IQR)30000000

Descriptive statistics

Standard deviation3.9662789 × 109
Coefficient of variation (CV)29.690415
Kurtosis3400.1305
Mean1.3358786 × 108
Median Absolute Deviation (MAD)0
Skewness57.663053
Sum4.8038193 × 1011
Variance1.5731368 × 1019
MonotonicityNot monotonic
2023-12-13T02:52:02.103489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1863
 
20.0%
50000000 42
 
0.5%
20000000 35
 
0.4%
30000000 28
 
0.3%
100000000 28
 
0.3%
25000000 23
 
0.2%
5000000 20
 
0.2%
22000000 19
 
0.2%
3000000 19
 
0.2%
15000000 19
 
0.2%
Other values (911) 1500
 
16.1%
(Missing) 5713
61.4%
ValueCountFrequency (%)
0 1863
20.0%
140000 1
 
< 0.1%
250000 1
 
< 0.1%
300000 2
 
< 0.1%
353000 1
 
< 0.1%
366000 1
 
< 0.1%
420000 1
 
< 0.1%
500000 1
 
< 0.1%
520000 2
 
< 0.1%
600000 1
 
< 0.1%
ValueCountFrequency (%)
234584000000 1
< 0.1%
33513000000 1
< 0.1%
10000000000 1
< 0.1%
9929570000 1
< 0.1%
7250000000 1
< 0.1%
6600000000 1
< 0.1%
5637800000 1
< 0.1%
4875675000 1
< 0.1%
4000000000 1
< 0.1%
3500000000 1
< 0.1%

하드웨어 구매예산2분기금액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct689
Distinct (%)19.2%
Missing5713
Missing (%)61.4%
Infinite0
Infinite (%)0.0%
Mean72367182
Minimum0
Maximum3.1388 × 1010
Zeros2373
Zeros (%)25.5%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:02.262378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q320000000
95-th percentile2.60164 × 108
Maximum3.1388 × 1010
Range3.1388 × 1010
Interquartile range (IQR)20000000

Descriptive statistics

Standard deviation6.6243698 × 108
Coefficient of variation (CV)9.1538313
Kurtosis1459.732
Mean72367182
Median Absolute Deviation (MAD)0
Skewness34.040389
Sum2.6023239 × 1011
Variance4.3882275 × 1017
MonotonicityNot monotonic
2023-12-13T02:52:02.436895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2373
25.5%
50000000 36
 
0.4%
100000000 29
 
0.3%
10000000 25
 
0.3%
20000000 19
 
0.2%
15000000 18
 
0.2%
30000000 17
 
0.2%
60000000 15
 
0.2%
5000000 15
 
0.2%
40000000 14
 
0.2%
Other values (679) 1035
 
11.1%
(Missing) 5713
61.4%
ValueCountFrequency (%)
0 2373
25.5%
69000 1
 
< 0.1%
336000 1
 
< 0.1%
353000 1
 
< 0.1%
500000 1
 
< 0.1%
700000 2
 
< 0.1%
750000 1
 
< 0.1%
774900 1
 
< 0.1%
780000 1
 
< 0.1%
850000 1
 
< 0.1%
ValueCountFrequency (%)
31388000000 1
< 0.1%
12000000000 1
< 0.1%
11000000000 1
< 0.1%
9713300000 1
< 0.1%
8530000000 1
< 0.1%
4000000000 1
< 0.1%
3611000000 1
< 0.1%
3500000000 1
< 0.1%
3300000000 1
< 0.1%
2800000000 1
< 0.1%

하드웨어 구매예산3분기금액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct364
Distinct (%)10.1%
Missing5713
Missing (%)61.4%
Infinite0
Infinite (%)0.0%
Mean92805206
Minimum0
Maximum5.038196 × 1010
Zeros3002
Zeros (%)32.2%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:02.595837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1.2 × 108
Maximum5.038196 × 1010
Range5.038196 × 1010
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2971275 × 109
Coefficient of variation (CV)13.976883
Kurtosis843.52308
Mean92805206
Median Absolute Deviation (MAD)0
Skewness26.655733
Sum3.3372752 × 1011
Variance1.6825398 × 1018
MonotonicityNot monotonic
2023-12-13T02:52:02.789386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3002
32.2%
20000000 21
 
0.2%
50000000 15
 
0.2%
100000000 15
 
0.2%
10000000 14
 
0.2%
30000000 14
 
0.2%
25000000 13
 
0.1%
40000000 12
 
0.1%
60000000 9
 
0.1%
5000000 8
 
0.1%
Other values (354) 473
 
5.1%
(Missing) 5713
61.4%
ValueCountFrequency (%)
0 3002
32.2%
300000 1
 
< 0.1%
353000 1
 
< 0.1%
500000 1
 
< 0.1%
520000 1
 
< 0.1%
560000 1
 
< 0.1%
600000 1
 
< 0.1%
750000 1
 
< 0.1%
900000 1
 
< 0.1%
1000000 4
 
< 0.1%
ValueCountFrequency (%)
50381960000 1
< 0.1%
31388000000 1
< 0.1%
29925000000 1
< 0.1%
22500000000 1
< 0.1%
19895327000 1
< 0.1%
10320132000 1
< 0.1%
9923425000 1
< 0.1%
9300000000 1
< 0.1%
8540000000 1
< 0.1%
8350000000 1
< 0.1%

하드웨어 구매예산4분기금액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct350
Distinct (%)9.7%
Missing5713
Missing (%)61.4%
Infinite0
Infinite (%)0.0%
Mean62116874
Minimum0
Maximum3.1388 × 1010
Zeros3117
Zeros (%)33.5%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:02.970034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1.085 × 108
Maximum3.1388 × 1010
Range3.1388 × 1010
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.2754819 × 108
Coefficient of variation (CV)13.322438
Kurtosis1150.4788
Mean62116874
Median Absolute Deviation (MAD)0
Skewness31.775464
Sum2.2337228 × 1011
Variance6.84836 × 1017
MonotonicityNot monotonic
2023-12-13T02:52:03.186776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3117
33.5%
10000000 12
 
0.1%
50000000 9
 
0.1%
20000000 7
 
0.1%
15000000 6
 
0.1%
55000000 6
 
0.1%
100000000 6
 
0.1%
40000000 5
 
0.1%
30000000 5
 
0.1%
3000000 5
 
0.1%
Other values (340) 418
 
4.5%
(Missing) 5713
61.4%
ValueCountFrequency (%)
0 3117
33.5%
353000 1
 
< 0.1%
500000 1
 
< 0.1%
600000 1
 
< 0.1%
700000 1
 
< 0.1%
750000 2
 
< 0.1%
1000000 2
 
< 0.1%
1260000 1
 
< 0.1%
1320000 1
 
< 0.1%
1400000 1
 
< 0.1%
ValueCountFrequency (%)
31388000000 1
< 0.1%
31202484000 1
< 0.1%
12830400000 1
< 0.1%
9705345000 1
< 0.1%
5120000000 1
< 0.1%
4939261000 1
< 0.1%
4556000000 1
< 0.1%
4395900000 1
< 0.1%
3750400000 1
< 0.1%
3600000000 1
< 0.1%

하드웨어 구매예산리스여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing5713
Missing (%)61.4%
Memory size18.3 KiB
False
3514 
True
 
82
(Missing)
5713 
ValueCountFrequency (%)
False 3514
37.7%
True 82
 
0.9%
(Missing) 5713
61.4%
2023-12-13T02:52:03.366010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
<NA>
5713 
자체예산
2632 
정부(지자체)예산
964 

Length

Max length9
Median length4
Mean length4.5177785
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 5713
61.4%
자체예산 2632
28.3%
정부(지자체)예산 964
 
10.4%

Length

2023-12-13T02:52:03.498762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:03.632853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5713
61.4%
자체예산 2632
28.3%
정부(지자체)예산 964
 
10.4%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
<NA>
5713 
자체
2169 
위탁
1427 

Length

Max length4
Median length4
Mean length3.2274143
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 5713
61.4%
자체 2169
 
23.3%
위탁 1427
 
15.3%

Length

2023-12-13T02:52:03.780111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:03.899685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5713
61.4%
자체 2169
 
23.3%
위탁 1427
 
15.3%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
<NA>
5713 
미발주
3592 
발주
 
4

Length

Max length4
Median length4
Mean length3.6132775
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 5713
61.4%
미발주 3592
38.6%
발주 4
 
< 0.1%

Length

2023-12-13T02:52:04.393001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:04.550700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5713
61.4%
미발주 3592
38.6%
발주 4
 
< 0.1%

하드웨어 구매예산합계
Real number (ℝ)

MISSING  SKEWED 

Distinct1656
Distinct (%)46.1%
Missing5713
Missing (%)61.4%
Infinite0
Infinite (%)0.0%
Mean3.6087712 × 108
Minimum69000
Maximum2.34584 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:04.705740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum69000
5-th percentile2809246.8
Q116701915
median47000000
Q31.389625 × 108
95-th percentile7.1399259 × 108
Maximum2.34584 × 1011
Range2.3458393 × 1011
Interquartile range (IQR)1.2226058 × 108

Descriptive statistics

Standard deviation4.6439739 × 109
Coefficient of variation (CV)12.868574
Kurtosis1870.3715
Mean3.6087712 × 108
Median Absolute Deviation (MAD)39000000
Skewness39.836691
Sum1.2977141 × 1012
Variance2.1566494 × 1019
MonotonicityNot monotonic
2023-12-13T02:52:04.892844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000000 86
 
0.9%
100000000 67
 
0.7%
20000000 65
 
0.7%
30000000 54
 
0.6%
10000000 45
 
0.5%
25000000 42
 
0.5%
40000000 42
 
0.5%
60000000 39
 
0.4%
15000000 34
 
0.4%
22000000 34
 
0.4%
Other values (1646) 3088
33.2%
(Missing) 5713
61.4%
ValueCountFrequency (%)
69000 1
 
< 0.1%
250000 1
 
< 0.1%
300000 2
< 0.1%
336000 1
 
< 0.1%
366000 1
 
< 0.1%
420000 1
 
< 0.1%
500000 2
< 0.1%
520000 3
< 0.1%
600000 2
< 0.1%
700000 3
< 0.1%
ValueCountFrequency (%)
234584000000 1
< 0.1%
94164000000 1
< 0.1%
74702484000 1
< 0.1%
50381960000 1
< 0.1%
33513000000 1
< 0.1%
29925000000 1
< 0.1%
27005345000 1
< 0.1%
26269910000 1
< 0.1%
19895327000 1
< 0.1%
19589261000 1
< 0.1%
Distinct1332
Distinct (%)72.5%
Missing7473
Missing (%)80.3%
Memory size72.9 KiB
2023-12-13T02:52:05.246690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length31
Mean length13.610566
Min length2

Characters and Unicode

Total characters24989
Distinct characters448
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1113 ?
Unique (%)60.6%

Sample

1st row지상라이다 공공측량성과심사용 H/W
2nd rowLiDAR 성과심사 프로그램 및 장비 구매
3rd row전산장비(Workstation) 구매
4th rowPC 및 모니터 구매
5th row컴퓨터 본체 구매
ValueCountFrequency (%)
교체 431
 
7.5%
구입 263
 
4.6%
노후 226
 
3.9%
구매 203
 
3.5%
145
 
2.5%
네트워크 117
 
2.0%
구축 105
 
1.8%
전산장비 101
 
1.8%
장비 89
 
1.5%
업무용 88
 
1.5%
Other values (1395) 3992
69.3%
2023-12-13T02:52:05.799159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3924
 
15.7%
759
 
3.0%
613
 
2.5%
565
 
2.3%
553
 
2.2%
548
 
2.2%
527
 
2.1%
519
 
2.1%
430
 
1.7%
426
 
1.7%
Other values (438) 16125
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18703
74.8%
Space Separator 3924
 
15.7%
Uppercase Letter 1245
 
5.0%
Decimal Number 333
 
1.3%
Open Punctuation 243
 
1.0%
Close Punctuation 242
 
1.0%
Lowercase Letter 131
 
0.5%
Dash Punctuation 101
 
0.4%
Other Punctuation 56
 
0.2%
Initial Punctuation 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
759
 
4.1%
613
 
3.3%
565
 
3.0%
553
 
3.0%
548
 
2.9%
527
 
2.8%
519
 
2.8%
430
 
2.3%
426
 
2.3%
397
 
2.1%
Other values (370) 13366
71.5%
Uppercase Letter
ValueCountFrequency (%)
C 308
24.7%
P 222
17.8%
T 115
 
9.2%
I 96
 
7.7%
V 87
 
7.0%
S 75
 
6.0%
A 55
 
4.4%
L 46
 
3.7%
D 44
 
3.5%
W 28
 
2.2%
Other values (14) 169
13.6%
Lowercase Letter
ValueCountFrequency (%)
c 27
20.6%
p 17
13.0%
o 13
9.9%
v 12
9.2%
t 11
8.4%
n 10
 
7.6%
i 9
 
6.9%
a 5
 
3.8%
r 5
 
3.8%
e 4
 
3.1%
Other values (12) 18
13.7%
Decimal Number
ValueCountFrequency (%)
2 149
44.7%
3 93
27.9%
0 52
 
15.6%
1 16
 
4.8%
4 13
 
3.9%
9 4
 
1.2%
5 2
 
0.6%
6 2
 
0.6%
8 1
 
0.3%
7 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 35
62.5%
/ 11
 
19.6%
. 5
 
8.9%
· 5
 
8.9%
Open Punctuation
ValueCountFrequency (%)
( 240
98.8%
[ 3
 
1.2%
Close Punctuation
ValueCountFrequency (%)
) 239
98.8%
] 3
 
1.2%
Space Separator
ValueCountFrequency (%)
3924
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 101
100.0%
Initial Punctuation
ValueCountFrequency (%)
9
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18703
74.8%
Common 4910
 
19.6%
Latin 1376
 
5.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
759
 
4.1%
613
 
3.3%
565
 
3.0%
553
 
3.0%
548
 
2.9%
527
 
2.8%
519
 
2.8%
430
 
2.3%
426
 
2.3%
397
 
2.1%
Other values (370) 13366
71.5%
Latin
ValueCountFrequency (%)
C 308
22.4%
P 222
16.1%
T 115
 
8.4%
I 96
 
7.0%
V 87
 
6.3%
S 75
 
5.5%
A 55
 
4.0%
L 46
 
3.3%
D 44
 
3.2%
W 28
 
2.0%
Other values (36) 300
21.8%
Common
ValueCountFrequency (%)
3924
79.9%
( 240
 
4.9%
) 239
 
4.9%
2 149
 
3.0%
- 101
 
2.1%
3 93
 
1.9%
0 52
 
1.1%
, 35
 
0.7%
1 16
 
0.3%
4 13
 
0.3%
Other values (12) 48
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18702
74.8%
ASCII 6272
 
25.1%
Punctuation 9
 
< 0.1%
None 5
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3924
62.6%
C 308
 
4.9%
( 240
 
3.8%
) 239
 
3.8%
P 222
 
3.5%
2 149
 
2.4%
T 115
 
1.8%
- 101
 
1.6%
I 96
 
1.5%
3 93
 
1.5%
Other values (56) 785
 
12.5%
Hangul
ValueCountFrequency (%)
759
 
4.1%
613
 
3.3%
565
 
3.0%
553
 
3.0%
548
 
2.9%
527
 
2.8%
519
 
2.8%
430
 
2.3%
426
 
2.3%
397
 
2.1%
Other values (369) 13365
71.5%
Punctuation
ValueCountFrequency (%)
9
100.0%
None
ValueCountFrequency (%)
· 5
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Distinct1362
Distinct (%)74.2%
Missing7474
Missing (%)80.3%
Memory size72.9 KiB
2023-12-13T02:52:06.109281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length136
Median length71
Mean length17.834332
Min length2

Characters and Unicode

Total characters32726
Distinct characters505
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1183 ?
Unique (%)64.5%

Sample

1st row대용량의 3차원 지상라이다 성과를 처리할 수 있는 워크스테이션 구입
2nd rowLiDAR성과자료의 고용량 데이터 처리가 필요한 수치표고자료 심사에 사용되는 고사양 WorkStation이 필요
3rd row지하공간통합지도 심사의 대용량 데이터의 처리 등 효율성 증대 효과 (Workstation 1대 장비 필요)
4th row국가기본도 및 1:1,000 수치지형도 품질검사(실내) 수행을 위한 전산장비(데스크톱 컴퓨터) 구매
5th row컴퓨터 본체 구매
ValueCountFrequency (%)
교체 639
 
7.9%
노후 308
 
3.8%
295
 
3.6%
구입 232
 
2.9%
구매 171
 
2.1%
장비 143
 
1.8%
노후장비 129
 
1.6%
업무용 106
 
1.3%
구축 103
 
1.3%
네트워크 97
 
1.2%
Other values (2093) 5878
72.6%
2023-12-13T02:52:06.707645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6266
 
19.1%
830
 
2.5%
796
 
2.4%
734
 
2.2%
723
 
2.2%
716
 
2.2%
643
 
2.0%
597
 
1.8%
530
 
1.6%
496
 
1.5%
Other values (495) 20395
62.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23847
72.9%
Space Separator 6266
 
19.1%
Uppercase Letter 1346
 
4.1%
Decimal Number 371
 
1.1%
Close Punctuation 229
 
0.7%
Open Punctuation 228
 
0.7%
Other Punctuation 189
 
0.6%
Lowercase Letter 189
 
0.6%
Dash Punctuation 41
 
0.1%
Other Symbol 18
 
0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
830
 
3.5%
796
 
3.3%
734
 
3.1%
723
 
3.0%
716
 
3.0%
643
 
2.7%
597
 
2.5%
530
 
2.2%
496
 
2.1%
446
 
1.9%
Other values (425) 17336
72.7%
Uppercase Letter
ValueCountFrequency (%)
C 317
23.6%
P 240
17.8%
S 108
 
8.0%
V 97
 
7.2%
T 92
 
6.8%
I 65
 
4.8%
A 61
 
4.5%
L 60
 
4.5%
D 52
 
3.9%
W 38
 
2.8%
Other values (16) 216
16.0%
Lowercase Letter
ValueCountFrequency (%)
c 33
17.5%
p 20
10.6%
t 17
9.0%
o 16
8.5%
a 15
7.9%
v 14
7.4%
e 11
 
5.8%
n 11
 
5.8%
r 10
 
5.3%
i 10
 
5.3%
Other values (11) 32
16.9%
Decimal Number
ValueCountFrequency (%)
2 113
30.5%
1 70
18.9%
0 67
18.1%
3 46
12.4%
4 25
 
6.7%
5 15
 
4.0%
7 12
 
3.2%
9 9
 
2.4%
6 8
 
2.2%
8 6
 
1.6%
Other Punctuation
ValueCountFrequency (%)
, 135
71.4%
/ 27
 
14.3%
· 14
 
7.4%
. 10
 
5.3%
* 2
 
1.1%
: 1
 
0.5%
Space Separator
ValueCountFrequency (%)
6266
100.0%
Close Punctuation
ValueCountFrequency (%)
) 229
100.0%
Open Punctuation
ValueCountFrequency (%)
( 228
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Other Symbol
ValueCountFrequency (%)
18
100.0%
Math Symbol
ValueCountFrequency (%)
1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23839
72.8%
Common 7344
 
22.4%
Latin 1535
 
4.7%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
830
 
3.5%
796
 
3.3%
734
 
3.1%
723
 
3.0%
716
 
3.0%
643
 
2.7%
597
 
2.5%
530
 
2.2%
496
 
2.1%
446
 
1.9%
Other values (424) 17328
72.7%
Latin
ValueCountFrequency (%)
C 317
20.7%
P 240
15.6%
S 108
 
7.0%
V 97
 
6.3%
T 92
 
6.0%
I 65
 
4.2%
A 61
 
4.0%
L 60
 
3.9%
D 52
 
3.4%
W 38
 
2.5%
Other values (37) 405
26.4%
Common
ValueCountFrequency (%)
6266
85.3%
) 229
 
3.1%
( 228
 
3.1%
, 135
 
1.8%
2 113
 
1.5%
1 70
 
1.0%
0 67
 
0.9%
3 46
 
0.6%
- 41
 
0.6%
/ 27
 
0.4%
Other values (13) 122
 
1.7%
Han
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23839
72.8%
ASCII 8846
 
27.0%
Geometric Shapes 18
 
0.1%
None 14
 
< 0.1%
CJK 8
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6266
70.8%
C 317
 
3.6%
P 240
 
2.7%
) 229
 
2.6%
( 228
 
2.6%
, 135
 
1.5%
2 113
 
1.3%
S 108
 
1.2%
V 97
 
1.1%
T 92
 
1.0%
Other values (57) 1021
 
11.5%
Hangul
ValueCountFrequency (%)
830
 
3.5%
796
 
3.3%
734
 
3.1%
723
 
3.0%
716
 
3.0%
643
 
2.7%
597
 
2.5%
530
 
2.2%
496
 
2.1%
446
 
1.9%
Other values (424) 17328
72.7%
Geometric Shapes
ValueCountFrequency (%)
18
100.0%
None
ValueCountFrequency (%)
· 14
100.0%
CJK
ValueCountFrequency (%)
8
100.0%
Arrows
ValueCountFrequency (%)
1
100.0%
Distinct87
Distinct (%)4.7%
Missing7473
Missing (%)80.3%
Memory size72.9 KiB
2023-12-13T02:52:06.936646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters31212
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)1.0%

Sample

1st row2023-01 ~ 2023-03
2nd row2023-01 ~ 2023-03
3rd row2023-01 ~ 2023-03
4th row2023-04 ~ 2023-05
5th row2023-01 ~ 2023-12
ValueCountFrequency (%)
1836
33.3%
2023-01 1163
21.1%
2023-12 1009
18.3%
2023-06 354
 
6.4%
2023-03 269
 
4.9%
2023-04 220
 
4.0%
2023-02 153
 
2.8%
2023-05 139
 
2.5%
2023-07 107
 
1.9%
2023-09 106
 
1.9%
Other values (18) 152
 
2.8%
2023-12-13T02:52:07.301496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 8545
27.4%
0 6300
20.2%
3 3904
12.5%
- 3672
11.8%
3672
11.8%
1 2299
 
7.4%
~ 1836
 
5.9%
6 355
 
1.1%
4 226
 
0.7%
5 142
 
0.5%
Other values (3) 261
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22032
70.6%
Dash Punctuation 3672
 
11.8%
Space Separator 3672
 
11.8%
Math Symbol 1836
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 8545
38.8%
0 6300
28.6%
3 3904
17.7%
1 2299
 
10.4%
6 355
 
1.6%
4 226
 
1.0%
5 142
 
0.6%
7 111
 
0.5%
9 108
 
0.5%
8 42
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
- 3672
100.0%
Space Separator
ValueCountFrequency (%)
3672
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1836
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 31212
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 8545
27.4%
0 6300
20.2%
3 3904
12.5%
- 3672
11.8%
3672
11.8%
1 2299
 
7.4%
~ 1836
 
5.9%
6 355
 
1.1%
4 226
 
0.7%
5 142
 
0.5%
Other values (3) 261
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31212
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 8545
27.4%
0 6300
20.2%
3 3904
12.5%
- 3672
11.8%
3672
11.8%
1 2299
 
7.4%
~ 1836
 
5.9%
6 355
 
1.1%
4 226
 
0.7%
5 142
 
0.5%
Other values (3) 261
 
0.8%

하드웨어 구매예산사업예산
Real number (ℝ)

MISSING  SKEWED 

Distinct948
Distinct (%)51.7%
Missing7475
Missing (%)80.3%
Infinite0
Infinite (%)0.0%
Mean6.8385554 × 108
Minimum366000
Maximum2.34584 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:07.478559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366000
5-th percentile3726000
Q122030000
median63500000
Q32.2 × 108
95-th percentile1.993 × 109
Maximum2.34584 × 1011
Range2.3458363 × 1011
Interquartile range (IQR)1.9797 × 108

Descriptive statistics

Standard deviation6.2734758 × 109
Coefficient of variation (CV)9.1736858
Kurtosis1084.6385
Mean6.8385554 × 108
Median Absolute Deviation (MAD)53500000
Skewness30.60242
Sum1.2541911 × 1012
Variance3.9356499 × 1019
MonotonicityNot monotonic
2023-12-13T02:52:07.679258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000000 39
 
0.4%
100000000 39
 
0.4%
20000000 27
 
0.3%
25000000 23
 
0.2%
30000000 23
 
0.2%
60000000 22
 
0.2%
200000000 20
 
0.2%
70000000 15
 
0.2%
150000000 14
 
0.2%
24000000 14
 
0.2%
Other values (938) 1598
 
17.2%
(Missing) 7475
80.3%
ValueCountFrequency (%)
366000 1
 
< 0.1%
500000 2
< 0.1%
520000 1
 
< 0.1%
700000 1
 
< 0.1%
780000 1
 
< 0.1%
800000 1
 
< 0.1%
850000 1
 
< 0.1%
960000 1
 
< 0.1%
991000 1
 
< 0.1%
1000000 4
< 0.1%
ValueCountFrequency (%)
234584000000 1
 
< 0.1%
94164000000 1
 
< 0.1%
50381960000 1
 
< 0.1%
33513000000 1
 
< 0.1%
29925000000 1
 
< 0.1%
19895327000 1
 
< 0.1%
16252000000 3
< 0.1%
12000000000 1
 
< 0.1%
10320132000 1
 
< 0.1%
9929570000 1
 
< 0.1%
Distinct2180
Distinct (%)59.4%
Missing5637
Missing (%)60.6%
Memory size72.9 KiB
2023-12-13T02:52:08.024416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length39
Mean length10.030229
Min length2

Characters and Unicode

Total characters36831
Distinct characters478
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1935 ?
Unique (%)52.7%

Sample

1st row사무용SW
2nd row백신소프트웨어 구입
3rd row업무용 소프트웨어 구입
4th row경기게임아카데미 교육 운영
5th row서부 창작터 스타트업 입주공간 운영지원 및 서부 창작터 교육 프로그램 지원
ValueCountFrequency (%)
사무용sw 669
 
8.5%
구입 397
 
5.1%
소프트웨어 396
 
5.1%
sw 318
 
4.1%
백신 302
 
3.9%
구매 238
 
3.0%
178
 
2.3%
사무용 158
 
2.0%
업무용 149
 
1.9%
솔루션 142
 
1.8%
Other values (1892) 4879
62.3%
2023-12-13T02:52:08.529982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4226
 
11.5%
1613
 
4.4%
S 1607
 
4.4%
W 1400
 
3.8%
1244
 
3.4%
1069
 
2.9%
933
 
2.5%
875
 
2.4%
810
 
2.2%
763
 
2.1%
Other values (468) 22291
60.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26322
71.5%
Uppercase Letter 4448
 
12.1%
Space Separator 4226
 
11.5%
Lowercase Letter 646
 
1.8%
Open Punctuation 368
 
1.0%
Close Punctuation 367
 
1.0%
Other Punctuation 194
 
0.5%
Decimal Number 180
 
0.5%
Dash Punctuation 72
 
0.2%
Connector Punctuation 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1613
 
6.1%
1244
 
4.7%
1069
 
4.1%
933
 
3.5%
875
 
3.3%
810
 
3.1%
763
 
2.9%
720
 
2.7%
715
 
2.7%
704
 
2.7%
Other values (398) 16876
64.1%
Uppercase Letter
ValueCountFrequency (%)
S 1607
36.1%
W 1400
31.5%
P 284
 
6.4%
C 270
 
6.1%
D 138
 
3.1%
M 104
 
2.3%
B 100
 
2.2%
A 86
 
1.9%
O 69
 
1.6%
E 63
 
1.4%
Other values (15) 327
 
7.4%
Lowercase Letter
ValueCountFrequency (%)
s 118
18.3%
w 106
16.4%
e 61
9.4%
i 48
 
7.4%
r 42
 
6.5%
a 34
 
5.3%
n 33
 
5.1%
t 30
 
4.6%
o 28
 
4.3%
l 23
 
3.6%
Other values (13) 123
19.0%
Decimal Number
ValueCountFrequency (%)
2 80
44.4%
0 39
21.7%
3 32
 
17.8%
1 17
 
9.4%
5 4
 
2.2%
6 4
 
2.2%
4 2
 
1.1%
7 2
 
1.1%
Other Punctuation
ValueCountFrequency (%)
/ 97
50.0%
, 80
41.2%
. 12
 
6.2%
· 2
 
1.0%
& 1
 
0.5%
# 1
 
0.5%
\ 1
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 360
97.8%
[ 8
 
2.2%
Close Punctuation
ValueCountFrequency (%)
) 359
97.8%
] 8
 
2.2%
Space Separator
ValueCountFrequency (%)
4226
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 72
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26321
71.5%
Common 5415
 
14.7%
Latin 5094
 
13.8%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1613
 
6.1%
1244
 
4.7%
1069
 
4.1%
933
 
3.5%
875
 
3.3%
810
 
3.1%
763
 
2.9%
720
 
2.7%
715
 
2.7%
704
 
2.7%
Other values (397) 16875
64.1%
Latin
ValueCountFrequency (%)
S 1607
31.5%
W 1400
27.5%
P 284
 
5.6%
C 270
 
5.3%
D 138
 
2.7%
s 118
 
2.3%
w 106
 
2.1%
M 104
 
2.0%
B 100
 
2.0%
A 86
 
1.7%
Other values (38) 881
17.3%
Common
ValueCountFrequency (%)
4226
78.0%
( 360
 
6.6%
) 359
 
6.6%
/ 97
 
1.8%
, 80
 
1.5%
2 80
 
1.5%
- 72
 
1.3%
0 39
 
0.7%
3 32
 
0.6%
1 17
 
0.3%
Other values (12) 53
 
1.0%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26320
71.5%
ASCII 10507
 
28.5%
None 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4226
40.2%
S 1607
 
15.3%
W 1400
 
13.3%
( 360
 
3.4%
) 359
 
3.4%
P 284
 
2.7%
C 270
 
2.6%
D 138
 
1.3%
s 118
 
1.1%
w 106
 
1.0%
Other values (59) 1639
 
15.6%
Hangul
ValueCountFrequency (%)
1613
 
6.1%
1244
 
4.7%
1069
 
4.1%
933
 
3.5%
875
 
3.3%
810
 
3.1%
763
 
2.9%
720
 
2.7%
715
 
2.7%
704
 
2.7%
Other values (396) 16874
64.1%
None
ValueCountFrequency (%)
· 2
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct14
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
<NA>
5637 
보안 SW
1408 
개인 및 사무용 SW
1396 
기타응용 SW
 
203
운영체계 SW
 
162
Other values (9)
 
503

Length

Max length16
Median length4
Mean length5.7217746
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개인 및 사무용 SW
2nd row보안 SW
3rd row개인 및 사무용 SW
4th row<NA>
5th row기타응용 SW

Common Values

ValueCountFrequency (%)
<NA> 5637
60.6%
보안 SW 1408
 
15.1%
개인 및 사무용 SW 1396
 
15.0%
기타응용 SW 203
 
2.2%
운영체계 SW 162
 
1.7%
시스템관리 및 스토리지 SW 109
 
1.2%
기타 시스템 SW 95
 
1.0%
데이터관리 및 분석 SW 90
 
1.0%
DBMS 및 관련 개발툴 43
 
0.5%
산업특화용 SW 42
 
0.5%
Other values (4) 124
 
1.3%

Length

2023-12-13T02:52:08.694266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5637
34.3%
sw 3599
21.9%
1638
 
10.0%
보안 1408
 
8.6%
개인 1396
 
8.5%
사무용 1396
 
8.5%
기타응용 203
 
1.2%
운영체계 162
 
1.0%
기타 127
 
0.8%
시스템관리 109
 
0.7%
Other values (15) 767
 
4.7%
Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
<NA>
7901 
A02
882 
A05
 
180
A03
 
119
A01
 
84
Other values (6)
 
143

Length

Max length4
Median length4
Mean length3.8487485
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd rowA02
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 7901
84.9%
A02 882
 
9.5%
A05 180
 
1.9%
A03 119
 
1.3%
A01 84
 
0.9%
A06 59
 
0.6%
A04 57
 
0.6%
B03 20
 
0.2%
B01 4
 
< 0.1%
B04 2
 
< 0.1%

Length

2023-12-13T02:52:08.845015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7901
84.9%
a02 882
 
9.5%
a05 180
 
1.9%
a03 119
 
1.3%
a01 84
 
0.9%
a06 59
 
0.6%
a04 57
 
0.6%
b03 20
 
0.2%
b01 4
 
< 0.1%
b04 2
 
< 0.1%
Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
<NA>
7901 
정보보안 제품-시스템(단말) 보안
882 
정보보안 제품-보안관리
 
180
정보보안 제품-콘텐츠(데이터) / 정보유출방지보안
 
119
정보보안 제품-네트워크 보안
 
84
Other values (6)
 
143

Length

Max length27
Median length4
Mean length6.0611236
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row정보보안 제품-시스템(단말) 보안
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 7901
84.9%
정보보안 제품-시스템(단말) 보안 882
 
9.5%
정보보안 제품-보안관리 180
 
1.9%
정보보안 제품-콘텐츠(데이터) / 정보유출방지보안 119
 
1.3%
정보보안 제품-네트워크 보안 84
 
0.9%
정보보안 제품-기타 정보보안제품 59
 
0.6%
정보보안 제품-암호 / 인증" 57
 
0.6%
물리보안 제품-접근제어 제품 20
 
0.2%
물리보안 제품-CCTV 4
 
< 0.1%
물리보안 제품-알람 모니터링 2
 
< 0.1%

Length

2023-12-13T02:52:08.979841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 7901
65.2%
정보보안 1381
 
11.4%
보안 966
 
8.0%
제품-시스템(단말 882
 
7.3%
제품-보안관리 180
 
1.5%
176
 
1.5%
제품-콘텐츠(데이터 119
 
1.0%
정보유출방지보안 119
 
1.0%
제품-네트워크 84
 
0.7%
제품-기타 60
 
0.5%
Other values (10) 249
 
2.1%

상용소프트웨어예산구매예산
Real number (ℝ)

MISSING 

Distinct1942
Distinct (%)52.9%
Missing5637
Missing (%)60.6%
Infinite0
Infinite (%)0.0%
Mean81842643
Minimum36000
Maximum1.17026 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:09.113160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36000
5-th percentile915090
Q15836125
median20850000
Q355000000
95-th percentile2.699604 × 108
Maximum1.17026 × 1010
Range1.1702564 × 1010
Interquartile range (IQR)49163875

Descriptive statistics

Standard deviation3.3914249 × 108
Coefficient of variation (CV)4.1438359
Kurtosis451.67111
Mean81842643
Median Absolute Deviation (MAD)17850000
Skewness17.325845
Sum3.0052619 × 1011
Variance1.1501763 × 1017
MonotonicityNot monotonic
2023-12-13T02:52:09.253557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000000 51
 
0.5%
5000000 49
 
0.5%
20000000 46
 
0.5%
10000000 45
 
0.5%
1000000 40
 
0.4%
6000000 39
 
0.4%
3000000 38
 
0.4%
4000000 35
 
0.4%
50000000 34
 
0.4%
35000000 32
 
0.3%
Other values (1932) 3263
35.1%
(Missing) 5637
60.6%
ValueCountFrequency (%)
36000 1
< 0.1%
98000 1
< 0.1%
100000 1
< 0.1%
110000 1
< 0.1%
115000 1
< 0.1%
123200 1
< 0.1%
132000 1
< 0.1%
150000 1
< 0.1%
165000 1
< 0.1%
170000 1
< 0.1%
ValueCountFrequency (%)
11702600000 1
< 0.1%
5661600000 1
< 0.1%
5165378000 1
< 0.1%
5081572000 1
< 0.1%
4800000000 1
< 0.1%
3760360000 1
< 0.1%
3615581000 1
< 0.1%
3385000000 1
< 0.1%
3382400000 1
< 0.1%
3351200000 1
< 0.1%

상용소프트웨어예산1분기금액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct1072
Distinct (%)29.2%
Missing5637
Missing (%)60.6%
Infinite0
Infinite (%)0.0%
Mean28822683
Minimum0
Maximum1.17026 × 1010
Zeros1964
Zeros (%)21.1%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:09.398623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q316545000
95-th percentile1.0102745 × 108
Maximum1.17026 × 1010
Range1.17026 × 1010
Interquartile range (IQR)16545000

Descriptive statistics

Standard deviation2.2953172 × 108
Coefficient of variation (CV)7.9635792
Kurtosis1859.5228
Mean28822683
Median Absolute Deviation (MAD)0
Skewness38.697426
Sum1.0583689 × 1011
Variance5.2684809 × 1016
MonotonicityNot monotonic
2023-12-13T02:52:09.544112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1964
 
21.1%
10000000 23
 
0.2%
35000000 19
 
0.2%
50000000 19
 
0.2%
40000000 19
 
0.2%
20000000 18
 
0.2%
30000000 18
 
0.2%
3000000 17
 
0.2%
6000000 16
 
0.2%
1500000 13
 
0.1%
Other values (1062) 1546
 
16.6%
(Missing) 5637
60.6%
ValueCountFrequency (%)
0 1964
21.1%
36000 1
 
< 0.1%
66000 1
 
< 0.1%
98000 1
 
< 0.1%
100000 1
 
< 0.1%
150000 1
 
< 0.1%
165000 1
 
< 0.1%
180000 1
 
< 0.1%
196000 2
 
< 0.1%
200000 1
 
< 0.1%
ValueCountFrequency (%)
11702600000 1
< 0.1%
3615581000 1
< 0.1%
3382400000 1
< 0.1%
2807208000 1
< 0.1%
1713887000 1
< 0.1%
1400000000 1
< 0.1%
1350000000 1
< 0.1%
1105000000 2
< 0.1%
1083000000 1
< 0.1%
1061700000 1
< 0.1%

상용소프트웨어예산2분기금액
Real number (ℝ)

MISSING  ZEROS 

Distinct654
Distinct (%)17.8%
Missing5637
Missing (%)60.6%
Infinite0
Infinite (%)0.0%
Mean23482010
Minimum0
Maximum5.165378 × 109
Zeros2664
Zeros (%)28.6%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:09.699937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31500000
95-th percentile84287900
Maximum5.165378 × 109
Range5.165378 × 109
Interquartile range (IQR)1500000

Descriptive statistics

Standard deviation1.6048429 × 108
Coefficient of variation (CV)6.8343508
Kurtosis411.62116
Mean23482010
Median Absolute Deviation (MAD)0
Skewness17.536424
Sum8.622594 × 1010
Variance2.5755208 × 1016
MonotonicityNot monotonic
2023-12-13T02:52:09.836164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2664
28.6%
3000000 23
 
0.2%
1000000 17
 
0.2%
30000000 16
 
0.2%
5000000 15
 
0.2%
100000000 14
 
0.2%
15000000 11
 
0.1%
20000000 11
 
0.1%
10000000 11
 
0.1%
50000000 11
 
0.1%
Other values (644) 879
 
9.4%
(Missing) 5637
60.6%
ValueCountFrequency (%)
0 2664
28.6%
110000 1
 
< 0.1%
117800 1
 
< 0.1%
150000 1
 
< 0.1%
200000 1
 
< 0.1%
250000 3
 
< 0.1%
270000 1
 
< 0.1%
275000 1
 
< 0.1%
300000 2
 
< 0.1%
340000 1
 
< 0.1%
ValueCountFrequency (%)
5165378000 1
< 0.1%
3351200000 1
< 0.1%
2716776440 1
< 0.1%
2447056000 1
< 0.1%
2214410760 1
< 0.1%
2046473000 1
< 0.1%
1813859000 1
< 0.1%
1800000000 2
< 0.1%
1615680000 1
< 0.1%
1530000000 1
< 0.1%

상용소프트웨어예산3분기금액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct442
Distinct (%)12.0%
Missing5637
Missing (%)60.6%
Infinite0
Infinite (%)0.0%
Mean17099561
Minimum0
Maximum5.081572 × 109
Zeros2968
Zeros (%)31.9%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:09.976680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile53000000
Maximum5.081572 × 109
Range5.081572 × 109
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.5476369 × 108
Coefficient of variation (CV)9.0507403
Kurtosis637.99935
Mean17099561
Median Absolute Deviation (MAD)0
Skewness22.792887
Sum6.2789589 × 1010
Variance2.3951799 × 1016
MonotonicityNot monotonic
2023-12-13T02:52:10.119765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2968
31.9%
5000000 23
 
0.2%
1000000 12
 
0.1%
20000000 11
 
0.1%
30000000 10
 
0.1%
6000000 10
 
0.1%
2000000 9
 
0.1%
50000000 9
 
0.1%
35000000 9
 
0.1%
100000000 8
 
0.1%
Other values (432) 603
 
6.5%
(Missing) 5637
60.6%
ValueCountFrequency (%)
0 2968
31.9%
14770 1
 
< 0.1%
44000 1
 
< 0.1%
66000 1
 
< 0.1%
150000 4
 
< 0.1%
220000 2
 
< 0.1%
240000 2
 
< 0.1%
242000 4
 
< 0.1%
250000 4
 
< 0.1%
283000 1
 
< 0.1%
ValueCountFrequency (%)
5081572000 1
< 0.1%
4800000000 1
< 0.1%
3160214000 1
< 0.1%
2290232700 1
< 0.1%
2100000000 1
< 0.1%
1608000000 1
< 0.1%
1529835000 1
< 0.1%
1458600000 1
< 0.1%
1306000000 1
< 0.1%
1094790000 1
< 0.1%

상용소프트웨어예산4분기금액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct396
Distinct (%)10.8%
Missing5637
Missing (%)60.6%
Infinite0
Infinite (%)0.0%
Mean12438390
Minimum0
Maximum3.385 × 109
Zeros3069
Zeros (%)33.0%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:10.265579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile46503325
Maximum3.385 × 109
Range3.385 × 109
Interquartile range (IQR)0

Descriptive statistics

Standard deviation87939634
Coefficient of variation (CV)7.0700175
Kurtosis641.34056
Mean12438390
Median Absolute Deviation (MAD)0
Skewness20.412703
Sum4.5673767 × 1010
Variance7.7333792 × 1015
MonotonicityNot monotonic
2023-12-13T02:52:10.420245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3069
33.0%
10000000 13
 
0.1%
1000000 12
 
0.1%
5000000 11
 
0.1%
20000000 10
 
0.1%
3000000 10
 
0.1%
4000000 9
 
0.1%
6000000 8
 
0.1%
1500000 8
 
0.1%
2000000 8
 
0.1%
Other values (386) 514
 
5.5%
(Missing) 5637
60.6%
ValueCountFrequency (%)
0 3069
33.0%
55000 2
 
< 0.1%
100000 1
 
< 0.1%
115000 1
 
< 0.1%
123200 1
 
< 0.1%
150000 1
 
< 0.1%
170000 1
 
< 0.1%
200000 1
 
< 0.1%
250000 3
 
< 0.1%
300000 2
 
< 0.1%
ValueCountFrequency (%)
3385000000 1
< 0.1%
1404000000 1
< 0.1%
1158401000 1
< 0.1%
1107933000 1
< 0.1%
941000000 1
< 0.1%
921000000 1
< 0.1%
875437000 1
< 0.1%
818000000 1
< 0.1%
800000000 1
< 0.1%
752500000 1
< 0.1%

상용소프트웨어예산합계
Real number (ℝ)

MISSING 

Distinct1942
Distinct (%)52.9%
Missing5637
Missing (%)60.6%
Infinite0
Infinite (%)0.0%
Mean81842643
Minimum36000
Maximum1.17026 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:10.569508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36000
5-th percentile915090
Q15836125
median20850000
Q355000000
95-th percentile2.699604 × 108
Maximum1.17026 × 1010
Range1.1702564 × 1010
Interquartile range (IQR)49163875

Descriptive statistics

Standard deviation3.3914249 × 108
Coefficient of variation (CV)4.1438359
Kurtosis451.67111
Mean81842643
Median Absolute Deviation (MAD)17850000
Skewness17.325845
Sum3.0052619 × 1011
Variance1.1501763 × 1017
MonotonicityNot monotonic
2023-12-13T02:52:10.709060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000000 51
 
0.5%
5000000 49
 
0.5%
20000000 46
 
0.5%
10000000 45
 
0.5%
1000000 40
 
0.4%
6000000 39
 
0.4%
3000000 38
 
0.4%
4000000 35
 
0.4%
50000000 34
 
0.4%
35000000 32
 
0.3%
Other values (1932) 3263
35.1%
(Missing) 5637
60.6%
ValueCountFrequency (%)
36000 1
< 0.1%
98000 1
< 0.1%
100000 1
< 0.1%
110000 1
< 0.1%
115000 1
< 0.1%
123200 1
< 0.1%
132000 1
< 0.1%
150000 1
< 0.1%
165000 1
< 0.1%
170000 1
< 0.1%
ValueCountFrequency (%)
11702600000 1
< 0.1%
5661600000 1
< 0.1%
5165378000 1
< 0.1%
5081572000 1
< 0.1%
4800000000 1
< 0.1%
3760360000 1
< 0.1%
3615581000 1
< 0.1%
3385000000 1
< 0.1%
3382400000 1
< 0.1%
3351200000 1
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
<NA>
5639 
자체예산
2599 
정부(지자체)예산
1071 

Length

Max length9
Median length4
Mean length4.5752498
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row자체예산
2nd row자체예산
3rd row자체예산
4th row<NA>
5th row정부(지자체)예산

Common Values

ValueCountFrequency (%)
<NA> 5639
60.6%
자체예산 2599
27.9%
정부(지자체)예산 1071
 
11.5%

Length

2023-12-13T02:52:10.841215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:10.952292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5639
60.6%
자체예산 2599
27.9%
정부(지자체)예산 1071
 
11.5%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
<NA>
5637 
(조달청)나라장터
2443 
(기관)자체 구매
1229 

Length

Max length9
Median length4
Mean length5.9722849
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row(조달청)나라장터
2nd row(조달청)나라장터
3rd row(조달청)나라장터
4th row<NA>
5th row(조달청)나라장터

Common Values

ValueCountFrequency (%)
<NA> 5637
60.6%
(조달청)나라장터 2443
26.2%
(기관)자체 구매 1229
 
13.2%

Length

2023-12-13T02:52:11.062757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:11.161053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5637
53.5%
조달청)나라장터 2443
23.2%
기관)자체 1229
 
11.7%
구매 1229
 
11.7%
Distinct6183
Distinct (%)86.7%
Missing2175
Missing (%)23.4%
Memory size72.9 KiB
2023-12-13T02:52:11.392650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length44
Mean length17.559994
Min length3

Characters and Unicode

Total characters125273
Distinct characters638
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5900 ?
Unique (%)82.7%

Sample

1st row그룹웨어 유지보수
2nd row교육관리시스템 유지보수
3rd row전산시스템(서버, 네트워크) 유지보수
4th row전산 유지관리
5th row경기게임문화센터운영
ValueCountFrequency (%)
유지보수 2408
 
9.9%
유지관리 1764
 
7.3%
989
 
4.1%
2023 921
 
3.8%
홈페이지 554
 
2.3%
용역 535
 
2.2%
시스템 473
 
1.9%
구축 457
 
1.9%
정보시스템 448
 
1.8%
운영 442
 
1.8%
Other values (6206) 15280
63.0%
2023-12-13T02:52:12.178113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17137
 
13.7%
6468
 
5.2%
5462
 
4.4%
5169
 
4.1%
4178
 
3.3%
4095
 
3.3%
3602
 
2.9%
3552
 
2.8%
3188
 
2.5%
3185
 
2.5%
Other values (628) 69237
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 94942
75.8%
Space Separator 17137
 
13.7%
Decimal Number 5216
 
4.2%
Uppercase Letter 3854
 
3.1%
Dash Punctuation 1329
 
1.1%
Close Punctuation 932
 
0.7%
Open Punctuation 932
 
0.7%
Lowercase Letter 489
 
0.4%
Other Punctuation 343
 
0.3%
Math Symbol 79
 
0.1%
Other values (5) 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6468
 
6.8%
5462
 
5.8%
5169
 
5.4%
4178
 
4.4%
4095
 
4.3%
3602
 
3.8%
3552
 
3.7%
3188
 
3.4%
3185
 
3.4%
2583
 
2.7%
Other values (541) 53460
56.3%
Uppercase Letter
ValueCountFrequency (%)
S 524
13.6%
P 377
 
9.8%
C 366
 
9.5%
I 354
 
9.2%
D 262
 
6.8%
T 226
 
5.9%
R 213
 
5.5%
B 198
 
5.1%
M 167
 
4.3%
A 164
 
4.3%
Other values (16) 1003
26.0%
Lowercase Letter
ValueCountFrequency (%)
e 93
19.0%
a 44
 
9.0%
o 43
 
8.8%
i 35
 
7.2%
n 31
 
6.3%
c 30
 
6.1%
t 28
 
5.7%
r 27
 
5.5%
s 26
 
5.3%
p 21
 
4.3%
Other values (13) 111
22.7%
Decimal Number
ValueCountFrequency (%)
2 2581
49.5%
3 1224
23.5%
0 1223
23.4%
1 70
 
1.3%
4 69
 
1.3%
5 25
 
0.5%
9 13
 
0.2%
6 7
 
0.1%
8 3
 
0.1%
7 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
, 127
37.0%
/ 96
28.0%
· 79
23.0%
. 20
 
5.8%
& 10
 
2.9%
' 7
 
2.0%
: 2
 
0.6%
* 1
 
0.3%
1
 
0.3%
Math Symbol
ValueCountFrequency (%)
~ 74
93.7%
+ 2
 
2.5%
2
 
2.5%
1
 
1.3%
Close Punctuation
ValueCountFrequency (%)
) 707
75.9%
] 224
 
24.0%
1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 707
75.9%
[ 224
 
24.0%
1
 
0.1%
Letter Number
ValueCountFrequency (%)
3
37.5%
3
37.5%
2
25.0%
Space Separator
ValueCountFrequency (%)
17137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1329
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 4
100.0%
Final Punctuation
ValueCountFrequency (%)
3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Initial Punctuation
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 94940
75.8%
Common 25980
 
20.7%
Latin 4351
 
3.5%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6468
 
6.8%
5462
 
5.8%
5169
 
5.4%
4178
 
4.4%
4095
 
4.3%
3602
 
3.8%
3552
 
3.7%
3188
 
3.4%
3185
 
3.4%
2583
 
2.7%
Other values (539) 53458
56.3%
Latin
ValueCountFrequency (%)
S 524
 
12.0%
P 377
 
8.7%
C 366
 
8.4%
I 354
 
8.1%
D 262
 
6.0%
T 226
 
5.2%
R 213
 
4.9%
B 198
 
4.6%
M 167
 
3.8%
A 164
 
3.8%
Other values (42) 1500
34.5%
Common
ValueCountFrequency (%)
17137
66.0%
2 2581
 
9.9%
- 1329
 
5.1%
3 1224
 
4.7%
0 1223
 
4.7%
) 707
 
2.7%
( 707
 
2.7%
[ 224
 
0.9%
] 224
 
0.9%
, 127
 
0.5%
Other values (25) 497
 
1.9%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 94938
75.8%
ASCII 30233
 
24.1%
None 82
 
0.1%
Number Forms 8
 
< 0.1%
Punctuation 6
 
< 0.1%
Math Operators 2
 
< 0.1%
Compat Jamo 2
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17137
56.7%
2 2581
 
8.5%
- 1329
 
4.4%
3 1224
 
4.0%
0 1223
 
4.0%
) 707
 
2.3%
( 707
 
2.3%
S 524
 
1.7%
P 377
 
1.2%
C 366
 
1.2%
Other values (66) 4058
 
13.4%
Hangul
ValueCountFrequency (%)
6468
 
6.8%
5462
 
5.8%
5169
 
5.4%
4178
 
4.4%
4095
 
4.3%
3602
 
3.8%
3552
 
3.7%
3188
 
3.4%
3185
 
3.4%
2583
 
2.7%
Other values (538) 53456
56.3%
None
ValueCountFrequency (%)
· 79
96.3%
1
 
1.2%
1
 
1.2%
1
 
1.2%
Number Forms
ValueCountFrequency (%)
3
37.5%
3
37.5%
2
25.0%
Punctuation
ValueCountFrequency (%)
3
50.0%
2
33.3%
1
 
16.7%
Math Operators
ValueCountFrequency (%)
2
100.0%
Compat Jamo
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct6472
Distinct (%)92.0%
Missing2275
Missing (%)24.4%
Memory size72.9 KiB
2023-12-13T02:52:12.523067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length246
Median length203
Mean length29.348593
Min length3

Characters and Unicode

Total characters206438
Distinct characters759
Distinct categories16 ?
Distinct scripts4 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6257 ?
Unique (%)89.0%

Sample

1st row그룹웨어 유지보수
2nd row기 구축된 교육관리시스템의 유지보수
3rd row운영중인 서버, 네트워크 장비의 유지보수
4th row전산 유지관리
5th row■ 사업목적 : 경기게임문화센터 사업 소개 등 홈페이지 유지보수 ■ 사업개요 - 경기게임문화센터 홈페이지 유지보수 - 23- 사업 내용 업데이트, 관리자 페이지 기능 강화 ■ 기대효과: 안정적인 홈페이지 운영
ValueCountFrequency (%)
유지보수 2317
 
5.1%
2238
 
5.0%
유지관리 1716
 
3.8%
시스템 763
 
1.7%
운영 677
 
1.5%
홈페이지 653
 
1.4%
643
 
1.4%
위한 605
 
1.3%
구축 471
 
1.0%
사업 426
 
0.9%
Other values (11828) 34544
76.7%
2023-12-13T02:52:13.020354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38021
 
18.4%
7184
 
3.5%
6026
 
2.9%
5215
 
2.5%
5139
 
2.5%
5104
 
2.5%
4257
 
2.1%
4096
 
2.0%
3788
 
1.8%
3762
 
1.8%
Other values (749) 123846
60.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 152201
73.7%
Space Separator 38021
 
18.4%
Uppercase Letter 5612
 
2.7%
Other Punctuation 3121
 
1.5%
Decimal Number 3075
 
1.5%
Lowercase Letter 1016
 
0.5%
Dash Punctuation 1014
 
0.5%
Close Punctuation 1004
 
0.5%
Open Punctuation 995
 
0.5%
Other Symbol 273
 
0.1%
Other values (6) 106
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7184
 
4.7%
6026
 
4.0%
5215
 
3.4%
5139
 
3.4%
5104
 
3.4%
4257
 
2.8%
4096
 
2.7%
3788
 
2.5%
3762
 
2.5%
3543
 
2.3%
Other values (645) 104087
68.4%
Uppercase Letter
ValueCountFrequency (%)
S 829
14.8%
P 537
 
9.6%
C 534
 
9.5%
I 453
 
8.1%
W 449
 
8.0%
D 388
 
6.9%
T 304
 
5.4%
B 264
 
4.7%
R 257
 
4.6%
A 225
 
4.0%
Other values (16) 1372
24.4%
Lowercase Letter
ValueCountFrequency (%)
e 160
15.7%
a 98
 
9.6%
o 96
 
9.4%
t 79
 
7.8%
r 59
 
5.8%
i 57
 
5.6%
s 51
 
5.0%
n 48
 
4.7%
c 47
 
4.6%
p 39
 
3.8%
Other values (16) 282
27.8%
Other Punctuation
ValueCountFrequency (%)
, 2040
65.4%
/ 302
 
9.7%
· 283
 
9.1%
. 188
 
6.0%
: 137
 
4.4%
' 119
 
3.8%
* 18
 
0.6%
& 15
 
0.5%
" 15
 
0.5%
3
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 1259
40.9%
0 618
20.1%
3 595
19.3%
1 213
 
6.9%
4 113
 
3.7%
5 92
 
3.0%
6 71
 
2.3%
9 44
 
1.4%
7 39
 
1.3%
8 31
 
1.0%
Math Symbol
ValueCountFrequency (%)
~ 32
74.4%
+ 4
 
9.3%
2
 
4.7%
> 2
 
4.7%
< 1
 
2.3%
1
 
2.3%
× 1
 
2.3%
Open Punctuation
ValueCountFrequency (%)
( 949
95.4%
[ 29
 
2.9%
14
 
1.4%
2
 
0.2%
1
 
0.1%
Other Symbol
ValueCountFrequency (%)
204
74.7%
41
 
15.0%
24
 
8.8%
3
 
1.1%
1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 958
95.4%
] 29
 
2.9%
15
 
1.5%
2
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
- 1009
99.5%
5
 
0.5%
Final Punctuation
ValueCountFrequency (%)
24
85.7%
4
 
14.3%
Initial Punctuation
ValueCountFrequency (%)
20
83.3%
4
 
16.7%
Space Separator
ValueCountFrequency (%)
38021
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 5
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 152181
73.7%
Common 47608
 
23.1%
Latin 6629
 
3.2%
Han 20
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7184
 
4.7%
6026
 
4.0%
5215
 
3.4%
5139
 
3.4%
5104
 
3.4%
4257
 
2.8%
4096
 
2.7%
3788
 
2.5%
3762
 
2.5%
3543
 
2.3%
Other values (636) 104067
68.4%
Latin
ValueCountFrequency (%)
S 829
 
12.5%
P 537
 
8.1%
C 534
 
8.1%
I 453
 
6.8%
W 449
 
6.8%
D 388
 
5.9%
T 304
 
4.6%
B 264
 
4.0%
R 257
 
3.9%
A 225
 
3.4%
Other values (43) 2389
36.0%
Common
ValueCountFrequency (%)
38021
79.9%
, 2040
 
4.3%
2 1259
 
2.6%
- 1009
 
2.1%
) 958
 
2.0%
( 949
 
2.0%
0 618
 
1.3%
3 595
 
1.2%
/ 302
 
0.6%
· 283
 
0.6%
Other values (41) 1574
 
3.3%
Han
ValueCountFrequency (%)
6
30.0%
4
20.0%
2
 
10.0%
2
 
10.0%
2
 
10.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 152004
73.6%
ASCII 53582
 
26.0%
None 318
 
0.2%
Geometric Shapes 273
 
0.1%
Compat Jamo 177
 
0.1%
Punctuation 60
 
< 0.1%
CJK 20
 
< 0.1%
Arrows 3
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38021
71.0%
, 2040
 
3.8%
2 1259
 
2.3%
- 1009
 
1.9%
) 958
 
1.8%
( 949
 
1.8%
S 829
 
1.5%
0 618
 
1.2%
3 595
 
1.1%
P 537
 
1.0%
Other values (73) 6767
 
12.6%
Hangul
ValueCountFrequency (%)
7184
 
4.7%
6026
 
4.0%
5215
 
3.4%
5139
 
3.4%
5104
 
3.4%
4257
 
2.8%
4096
 
2.7%
3788
 
2.5%
3762
 
2.5%
3543
 
2.3%
Other values (632) 103890
68.3%
None
ValueCountFrequency (%)
· 283
89.0%
15
 
4.7%
14
 
4.4%
2
 
0.6%
2
 
0.6%
1
 
0.3%
× 1
 
0.3%
Geometric Shapes
ValueCountFrequency (%)
204
74.7%
41
 
15.0%
24
 
8.8%
3
 
1.1%
1
 
0.4%
Compat Jamo
ValueCountFrequency (%)
158
89.3%
17
 
9.6%
1
 
0.6%
1
 
0.6%
Punctuation
ValueCountFrequency (%)
24
40.0%
20
33.3%
5
 
8.3%
4
 
6.7%
4
 
6.7%
3
 
5.0%
CJK
ValueCountFrequency (%)
6
30.0%
4
20.0%
2
 
10.0%
2
 
10.0%
2
 
10.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
Arrows
ValueCountFrequency (%)
2
66.7%
1
33.3%
Number Forms
ValueCountFrequency (%)
1
100.0%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
계속사업
5530 
<NA>
2175 
신규사업
1604 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row계속사업
2nd row계속사업
3rd row계속사업
4th row계속사업
5th row계속사업

Common Values

ValueCountFrequency (%)
계속사업 5530
59.4%
<NA> 2175
 
23.4%
신규사업 1604
 
17.2%

Length

2023-12-13T02:52:13.179804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:13.286683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
계속사업 5530
59.4%
na 2175
 
23.4%
신규사업 1604
 
17.2%
Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
시스템운영유지관리 사업
5591 
<NA>
2175 
소프트웨어개발 사업
1043 
시스템운용환경구축 사업
 
189
정보화전략계획수립 사업
 
120
Other values (2)
 
191

Length

Max length14
Median length12
Mean length9.9113761
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시스템운영유지관리 사업
2nd row시스템운영유지관리 사업
3rd row시스템운영유지관리 사업
4th row시스템운영유지관리 사업
5th row시스템운영유지관리 사업

Common Values

ValueCountFrequency (%)
시스템운영유지관리 사업 5591
60.1%
<NA> 2175
 
23.4%
소프트웨어개발 사업 1043
 
11.2%
시스템운용환경구축 사업 189
 
2.0%
정보화전략계획수립 사업 120
 
1.3%
데이터베이스구축 사업 113
 
1.2%
디지털콘텐츠개발서비스 사업 78
 
0.8%

Length

2023-12-13T02:52:13.393478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:13.495730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사업 7134
43.4%
시스템운영유지관리 5591
34.0%
na 2175
 
13.2%
소프트웨어개발 1043
 
6.3%
시스템운용환경구축 189
 
1.1%
정보화전략계획수립 120
 
0.7%
데이터베이스구축 113
 
0.7%
디지털콘텐츠개발서비스 78
 
0.5%
Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
해당없음
6619 
<NA>
2175 
Cloud
 
198
Big Data
 
97
Mobile
 
86
Other values (4)
 
134

Length

Max length8
Median length4
Mean length4.0791707
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row해당없음
2nd row해당없음
3rd row해당없음
4th row해당없음
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 6619
71.1%
<NA> 2175
 
23.4%
Cloud 198
 
2.1%
Big Data 97
 
1.0%
Mobile 86
 
0.9%
IoT B 60
 
0.6%
AIF 59
 
0.6%
기타 11
 
0.1%
블록체인 4
 
< 0.1%

Length

2023-12-13T02:52:13.627691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:13.758410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 6619
69.9%
na 2175
 
23.0%
cloud 198
 
2.1%
big 97
 
1.0%
data 97
 
1.0%
mobile 86
 
0.9%
iot 60
 
0.6%
b 60
 
0.6%
aif 59
 
0.6%
기타 11
 
0.1%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
비해당
5383 
<NA>
2175 
해당
1145 
일부
606 

Length

Max length4
Median length3
Mean length3.0455473
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row비해당
2nd row비해당
3rd row해당
4th row비해당
5th row비해당

Common Values

ValueCountFrequency (%)
비해당 5383
57.8%
<NA> 2175
23.4%
해당 1145
 
12.3%
일부 606
 
6.5%

Length

2023-12-13T02:52:13.888777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:13.993775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비해당 5383
57.8%
na 2175
23.4%
해당 1145
 
12.3%
일부 606
 
6.5%
Distinct60
Distinct (%)3.4%
Missing7558
Missing (%)81.2%
Memory size72.9 KiB
2023-12-13T02:52:14.136574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.625928
Min length2

Characters and Unicode

Total characters6349
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)1.0%

Sample

1st row100%
2nd row100%
3rd row100%
4th row100%
5th row100%
ValueCountFrequency (%)
100 1145
65.4%
10 112
 
6.4%
20 92
 
5.3%
50 91
 
5.2%
30 79
 
4.5%
15 22
 
1.3%
40 22
 
1.3%
5 14
 
0.8%
80 11
 
0.6%
25 9
 
0.5%
Other values (50) 154
 
8.8%
2023-12-13T02:52:14.444611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2715
42.8%
% 1751
27.6%
1 1334
21.0%
5 146
 
2.3%
2 142
 
2.2%
3 118
 
1.9%
4 44
 
0.7%
8 28
 
0.4%
6 27
 
0.4%
7 26
 
0.4%
Other values (2) 18
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4595
72.4%
Other Punctuation 1754
 
27.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2715
59.1%
1 1334
29.0%
5 146
 
3.2%
2 142
 
3.1%
3 118
 
2.6%
4 44
 
1.0%
8 28
 
0.6%
6 27
 
0.6%
7 26
 
0.6%
9 15
 
0.3%
Other Punctuation
ValueCountFrequency (%)
% 1751
99.8%
. 3
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 6349
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2715
42.8%
% 1751
27.6%
1 1334
21.0%
5 146
 
2.3%
2 142
 
2.2%
3 118
 
1.9%
4 44
 
0.7%
8 28
 
0.4%
6 27
 
0.4%
7 26
 
0.4%
Other values (2) 18
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6349
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2715
42.8%
% 1751
27.6%
1 1334
21.0%
5 146
 
2.3%
2 142
 
2.2%
3 118
 
1.9%
4 44
 
0.7%
8 28
 
0.4%
6 27
 
0.4%
7 26
 
0.4%
Other values (2) 18
 
0.3%
Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
<NA>
7568 
A03
1367 
A01
 
135
A07
 
125
A02
 
43
Other values (3)
 
71

Length

Max length4
Median length4
Mean length3.8129767
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd rowA03
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 7568
81.3%
A03 1367
 
14.7%
A01 135
 
1.5%
A07 125
 
1.3%
A02 43
 
0.5%
A04 38
 
0.4%
B01 19
 
0.2%
B03 14
 
0.2%

Length

2023-12-13T02:52:14.567394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:14.672713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7568
81.3%
a03 1367
 
14.7%
a01 135
 
1.5%
a07 125
 
1.3%
a02 43
 
0.5%
a04 38
 
0.4%
b01 19
 
0.2%
b03 14
 
0.2%
Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
<NA>
7568 
유지관리
1367 
보안관제
 
135
기타 정보보안서비스
 
125
보안컨설팅
 
43
Other values (3)
 
71

Length

Max length10
Median length4
Mean length4.1166613
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row유지관리
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 7568
81.3%
유지관리 1367
 
14.7%
보안관제 135
 
1.5%
기타 정보보안서비스 125
 
1.3%
보안컨설팅 43
 
0.5%
보안성지속서비스 38
 
0.4%
영상보안서비스 19
 
0.2%
기타 물리보안서비스 14
 
0.2%

Length

2023-12-13T02:52:14.790908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:14.886426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7568
80.1%
유지관리 1367
 
14.5%
기타 139
 
1.5%
보안관제 135
 
1.4%
정보보안서비스 125
 
1.3%
보안컨설팅 43
 
0.5%
보안성지속서비스 38
 
0.4%
영상보안서비스 19
 
0.2%
물리보안서비스 14
 
0.1%
Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
<NA>
8755 
0%
 
516
8%
 
15
10%
 
6
7%
 
4
Other values (8)
 
13

Length

Max length5
Median length4
Mean length3.8830164
Min length2

Unique

Unique5 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 8755
94.0%
0% 516
 
5.5%
8% 15
 
0.2%
10% 6
 
0.1%
7% 4
 
< 0.1%
15% 3
 
< 0.1%
12% 3
 
< 0.1%
9% 2
 
< 0.1%
3% 1
 
< 0.1%
6.50% 1
 
< 0.1%
Other values (3) 3
 
< 0.1%

Length

2023-12-13T02:52:15.001204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8755
94.0%
0 516
 
5.5%
8 15
 
0.2%
10 6
 
0.1%
7 4
 
< 0.1%
15 3
 
< 0.1%
12 3
 
< 0.1%
9 2
 
< 0.1%
3 1
 
< 0.1%
6.50 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
1분기
6289 
<NA>
2175 
2분기
 
603
3분기
 
199
4분기
 
43

Length

Max length4
Median length3
Mean length3.2336449
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1분기
2nd row1분기
3rd row1분기
4th row1분기
5th row2분기

Common Values

ValueCountFrequency (%)
1분기 6289
67.6%
<NA> 2175
 
23.4%
2분기 603
 
6.5%
3분기 199
 
2.1%
4분기 43
 
0.5%

Length

2023-12-13T02:52:15.116193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:15.211755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1분기 6289
67.6%
na 2175
 
23.4%
2분기 603
 
6.5%
3분기 199
 
2.1%
4분기 43
 
0.5%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
해당사항없음
7099 
<NA>
2175 
대기업 참여제한 예외 인정 사업
 
22
대기업 참여제한 예외 인정 신청 검토 사업
 
13

Length

Max length23
Median length6
Mean length5.5824471
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row해당사항없음
2nd row해당사항없음
3rd row해당사항없음
4th row해당사항없음
5th row해당사항없음

Common Values

ValueCountFrequency (%)
해당사항없음 7099
76.3%
<NA> 2175
 
23.4%
대기업 참여제한 예외 인정 사업 22
 
0.2%
대기업 참여제한 예외 인정 신청 검토 사업 13
 
0.1%

Length

2023-12-13T02:52:15.328921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:15.427461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당사항없음 7099
74.9%
na 2175
 
23.0%
대기업 35
 
0.4%
참여제한 35
 
0.4%
예외 35
 
0.4%
인정 35
 
0.4%
사업 35
 
0.4%
신청 13
 
0.1%
검토 13
 
0.1%
Distinct53
Distinct (%)0.7%
Missing2175
Missing (%)23.4%
Memory size72.9 KiB
Minimum2015-01-01 00:00:00
Maximum2023-12-01 00:00:00
2023-12-13T02:52:15.526839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:15.646861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct44
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
2023-12
5964 
<NA>
2175 
2024-12
 
158
2024-02
 
118
2023-06
 
108
Other values (39)
786 

Length

Max length7
Median length7
Mean length6.2990654
Min length4

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row2023-12
2nd row2023-12
3rd row2023-12
4th row2023-12
5th row2023-12

Common Values

ValueCountFrequency (%)
2023-12 5964
64.1%
<NA> 2175
 
23.4%
2024-12 158
 
1.7%
2024-02 118
 
1.3%
2023-06 108
 
1.2%
2023-11 90
 
1.0%
2023-09 79
 
0.8%
2023-10 75
 
0.8%
2023-08 48
 
0.5%
2024-03 41
 
0.4%
Other values (34) 453
 
4.9%

Length

2023-12-13T02:52:15.770278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-12 5964
64.1%
na 2175
 
23.4%
2024-12 158
 
1.7%
2024-02 118
 
1.3%
2023-06 108
 
1.2%
2023-11 90
 
1.0%
2023-09 79
 
0.8%
2023-10 75
 
0.8%
2023-08 48
 
0.5%
2024-03 41
 
0.4%
Other values (34) 453
 
4.9%

소프트웨어구축예산총사업금액
Real number (ℝ)

MISSING  SKEWED 

Distinct4011
Distinct (%)56.2%
Missing2175
Missing (%)23.4%
Infinite0
Infinite (%)0.0%
Mean9.4617703 × 108
Minimum165000
Maximum2.87 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:15.889759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum165000
5-th percentile2678600
Q112000000
median66000000
Q33.3781025 × 108
95-th percentile2.5 × 109
Maximum2.87 × 1011
Range2.8699984 × 1011
Interquartile range (IQR)3.2581025 × 108

Descriptive statistics

Standard deviation7.3096733 × 109
Coefficient of variation (CV)7.7254817
Kurtosis760.17464
Mean9.4617703 × 108
Median Absolute Deviation (MAD)62149500
Skewness24.409417
Sum6.7500269 × 1012
Variance5.3431324 × 1019
MonotonicityNot monotonic
2023-12-13T02:52:16.036556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000000 94
 
1.0%
200000000 77
 
0.8%
100000000 76
 
0.8%
300000000 63
 
0.7%
22000000 60
 
0.6%
50000000 57
 
0.6%
150000000 55
 
0.6%
500000000 50
 
0.5%
3000000 45
 
0.5%
15000000 45
 
0.5%
Other values (4001) 6512
70.0%
(Missing) 2175
 
23.4%
ValueCountFrequency (%)
165000 1
< 0.1%
220000 1
< 0.1%
231000 1
< 0.1%
264000 1
< 0.1%
315000 1
< 0.1%
325600 1
< 0.1%
328000 1
< 0.1%
360000 1
< 0.1%
369600 1
< 0.1%
450000 1
< 0.1%
ValueCountFrequency (%)
287000000000 1
< 0.1%
260313000000 1
< 0.1%
210021000000 1
< 0.1%
189700000000 1
< 0.1%
150500000000 1
< 0.1%
99689000000 1
< 0.1%
99062000000 1
< 0.1%
97531000000 1
< 0.1%
93555000000 1
< 0.1%
89370000000 1
< 0.1%
Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
2023-01
5685 
<NA>
2175 
2023-03
 
358
2023-04
 
337
2023-05
 
193
Other values (11)
 
561

Length

Max length7
Median length7
Mean length6.2990654
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2023-01
2nd row2023-01
3rd row2023-01
4th row2023-01
5th row2023-04

Common Values

ValueCountFrequency (%)
2023-01 5685
61.1%
<NA> 2175
 
23.4%
2023-03 358
 
3.8%
2023-04 337
 
3.6%
2023-05 193
 
2.1%
2023-06 174
 
1.9%
2023-07 123
 
1.3%
2023-02 105
 
1.1%
2023-08 55
 
0.6%
2023-10 41
 
0.4%
Other values (6) 63
 
0.7%

Length

2023-12-13T02:52:16.167675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-01 5685
61.1%
na 2175
 
23.4%
2023-03 358
 
3.8%
2023-04 337
 
3.6%
2023-05 193
 
2.1%
2023-06 174
 
1.9%
2023-07 123
 
1.3%
2023-02 105
 
1.1%
2023-08 55
 
0.6%
2023-10 41
 
0.4%
Other values (6) 63
 
0.7%
Distinct24
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
2023-12
6266 
<NA>
2175 
2024-02
 
113
2023-06
 
108
2023-11
 
94
Other values (19)
 
553

Length

Max length7
Median length7
Mean length6.2990654
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-12
2nd row2023-12
3rd row2023-12
4th row2023-12
5th row2023-12

Common Values

ValueCountFrequency (%)
2023-12 6266
67.3%
<NA> 2175
 
23.4%
2024-02 113
 
1.2%
2023-06 108
 
1.2%
2023-11 94
 
1.0%
2023-09 79
 
0.8%
2023-10 76
 
0.8%
2023-08 48
 
0.5%
2024-03 40
 
0.4%
2024-04 38
 
0.4%
Other values (14) 272
 
2.9%

Length

2023-12-13T02:52:16.301870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-12 6266
67.3%
na 2175
 
23.4%
2024-02 113
 
1.2%
2023-06 108
 
1.2%
2023-11 94
 
1.0%
2023-09 79
 
0.8%
2023-10 76
 
0.8%
2023-08 48
 
0.5%
2024-03 40
 
0.4%
2024-04 38
 
0.4%
Other values (14) 272
 
2.9%
Distinct3967
Distinct (%)55.6%
Missing2175
Missing (%)23.4%
Infinite0
Infinite (%)0.0%
Mean5.8227626 × 108
Minimum165000
Maximum9.9689 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:16.449124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum165000
5-th percentile2670750
Q112000000
median63712500
Q33.07489 × 108
95-th percentile1.8459315 × 109
Maximum9.9689 × 1010
Range9.9688835 × 1010
Interquartile range (IQR)2.95489 × 108

Descriptive statistics

Standard deviation3.1507944 × 109
Coefficient of variation (CV)5.4111675
Kurtosis450.02798
Mean5.8227626 × 108
Median Absolute Deviation (MAD)59752500
Skewness18.334162
Sum4.1539589 × 1012
Variance9.9275052 × 1018
MonotonicityNot monotonic
2023-12-13T02:52:16.610406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000000 96
 
1.0%
200000000 85
 
0.9%
100000000 80
 
0.9%
300000000 63
 
0.7%
22000000 61
 
0.7%
50000000 59
 
0.6%
150000000 57
 
0.6%
500000000 50
 
0.5%
3000000 46
 
0.5%
15000000 45
 
0.5%
Other values (3957) 6492
69.7%
(Missing) 2175
 
23.4%
ValueCountFrequency (%)
165000 1
< 0.1%
220000 1
< 0.1%
231000 1
< 0.1%
264000 1
< 0.1%
315000 1
< 0.1%
325600 1
< 0.1%
328000 1
< 0.1%
360000 1
< 0.1%
369600 1
< 0.1%
450000 1
< 0.1%
ValueCountFrequency (%)
99689000000 1
< 0.1%
95200000000 1
< 0.1%
85112231000 1
< 0.1%
83851000000 1
< 0.1%
57400000000 1
< 0.1%
51352909000 1
< 0.1%
47351051000 1
< 0.1%
46248000000 1
< 0.1%
44787000000 1
< 0.1%
37489546000 1
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
미추진
6978 
<NA>
2175 
추진
 
156

Length

Max length4
Median length3
Mean length3.2168869
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미추진
2nd row미추진
3rd row미추진
4th row미추진
5th row미추진

Common Values

ValueCountFrequency (%)
미추진 6978
75.0%
<NA> 2175
 
23.4%
추진 156
 
1.7%

Length

2023-12-13T02:52:16.752245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:16.880130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미추진 6978
75.0%
na 2175
 
23.4%
추진 156
 
1.7%

소프트웨어구축예산분리발주예산
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct137
Distinct (%)1.9%
Missing2175
Missing (%)23.4%
Infinite0
Infinite (%)0.0%
Mean13138575
Minimum0
Maximum1.4 × 1010
Zeros6978
Zeros (%)75.0%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:17.001639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1.4 × 1010
Range1.4 × 1010
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.5071169 × 108
Coefficient of variation (CV)19.082107
Kurtosis1751.1757
Mean13138575
Median Absolute Deviation (MAD)0
Skewness38.103497
Sum9.3730592 × 1010
Variance6.2856349 × 1016
MonotonicityNot monotonic
2023-12-13T02:52:17.195112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6978
75.0%
200000000 6
 
0.1%
300000000 4
 
< 0.1%
120000000 3
 
< 0.1%
110000000 2
 
< 0.1%
500000000 2
 
< 0.1%
400000000 2
 
< 0.1%
100000000 2
 
< 0.1%
180000000 2
 
< 0.1%
250000000 2
 
< 0.1%
Other values (127) 131
 
1.4%
(Missing) 2175
 
23.4%
ValueCountFrequency (%)
0 6978
75.0%
500000 1
 
< 0.1%
792000 1
 
< 0.1%
1264000 1
 
< 0.1%
1500000 1
 
< 0.1%
1788600 1
 
< 0.1%
3500000 1
 
< 0.1%
3880000 1
 
< 0.1%
10000000 1
 
< 0.1%
11000000 1
 
< 0.1%
ValueCountFrequency (%)
14000000000 1
< 0.1%
8657000000 1
< 0.1%
7038815000 1
< 0.1%
6838000000 1
< 0.1%
5197000000 1
< 0.1%
3000000000 1
< 0.1%
2766000000 1
< 0.1%
2145000000 1
< 0.1%
2046921000 1
< 0.1%
1580000000 1
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
(기관)자체발주
4820 
(조달청)위탁발주
2314 
<NA>
2175 

Length

Max length9
Median length8
Mean length7.3139972
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row(기관)자체발주
2nd row(기관)자체발주
3rd row(기관)자체발주
4th row(기관)자체발주
5th row(기관)자체발주

Common Values

ValueCountFrequency (%)
(기관)자체발주 4820
51.8%
(조달청)위탁발주 2314
24.9%
<NA> 2175
23.4%

Length

2023-12-13T02:52:17.369609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:17.468513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기관)자체발주 4820
51.8%
조달청)위탁발주 2314
24.9%
na 2175
23.4%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
미발주
6494 
<NA>
2175 
발주
 
640

Length

Max length4
Median length3
Mean length3.1648942
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미발주
2nd row미발주
3rd row미발주
4th row미발주
5th row미발주

Common Values

ValueCountFrequency (%)
미발주 6494
69.8%
<NA> 2175
 
23.4%
발주 640
 
6.9%

Length

2023-12-13T02:52:17.603456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:17.723311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미발주 6494
69.8%
na 2175
 
23.4%
발주 640
 
6.9%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
미도입
6837 
<NA>
2175 
도입
 
297

Length

Max length4
Median length3
Mean length3.2017403
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미도입
2nd row미도입
3rd row미도입
4th row미도입
5th row미도입

Common Values

ValueCountFrequency (%)
미도입 6837
73.4%
<NA> 2175
 
23.4%
도입 297
 
3.2%

Length

2023-12-13T02:52:17.850704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:17.971765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미도입 6837
73.4%
na 2175
 
23.4%
도입 297
 
3.2%

소프트웨어구축예산하드웨어장비도입금액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct235
Distinct (%)3.3%
Missing2175
Missing (%)23.4%
Infinite0
Infinite (%)0.0%
Mean53449034
Minimum0
Maximum4.83088 × 1010
Zeros6837
Zeros (%)73.4%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:18.115862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum4.83088 × 1010
Range4.83088 × 1010
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0330807 × 109
Coefficient of variation (CV)19.328333
Kurtosis1300.6966
Mean53449034
Median Absolute Deviation (MAD)0
Skewness33.261575
Sum3.8130541 × 1011
Variance1.0672558 × 1018
MonotonicityNot monotonic
2023-12-13T02:52:18.654006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6837
73.4%
50000000 9
 
0.1%
100000000 8
 
0.1%
70000000 6
 
0.1%
300000000 5
 
0.1%
30000000 5
 
0.1%
25000000 5
 
0.1%
150000000 4
 
< 0.1%
200000000 3
 
< 0.1%
40000000 3
 
< 0.1%
Other values (225) 249
 
2.7%
(Missing) 2175
 
23.4%
ValueCountFrequency (%)
0 6837
73.4%
2000000 1
 
< 0.1%
3000000 1
 
< 0.1%
4000000 1
 
< 0.1%
5000000 2
 
< 0.1%
5500000 1
 
< 0.1%
6100000 1
 
< 0.1%
7000000 1
 
< 0.1%
7100000 1
 
< 0.1%
7130000 1
 
< 0.1%
ValueCountFrequency (%)
48308800000 1
< 0.1%
43811979000 1
< 0.1%
28976227000 1
< 0.1%
25778749000 1
< 0.1%
19550514000 1
< 0.1%
14576665000 1
< 0.1%
13587866000 1
< 0.1%
13515000000 1
< 0.1%
13388617600 1
< 0.1%
13333000000 1
< 0.1%
Distinct687
Distinct (%)34.9%
Missing7341
Missing (%)78.9%
Infinite0
Infinite (%)0.0%
Mean96400068
Minimum0
Maximum1.5146749 × 1010
Zeros1160
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:18.916385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q316184945
95-th percentile3.3635305 × 108
Maximum1.5146749 × 1010
Range1.5146749 × 1010
Interquartile range (IQR)16184945

Descriptive statistics

Standard deviation5.8525553 × 108
Coefficient of variation (CV)6.0711111
Kurtosis291.10698
Mean96400068
Median Absolute Deviation (MAD)0
Skewness14.801376
Sum1.8971533 × 1011
Variance3.4252403 × 1017
MonotonicityNot monotonic
2023-12-13T02:52:19.144162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1160
 
12.5%
20000000 8
 
0.1%
2400000 7
 
0.1%
70000000 7
 
0.1%
3000000 7
 
0.1%
10000000 6
 
0.1%
15000000 6
 
0.1%
30000000 5
 
0.1%
100000000 5
 
0.1%
3600000 5
 
0.1%
Other values (677) 752
 
8.1%
(Missing) 7341
78.9%
ValueCountFrequency (%)
0 1160
12.5%
3229 1
 
< 0.1%
3960 1
 
< 0.1%
360000 1
 
< 0.1%
367000 1
 
< 0.1%
618000 1
 
< 0.1%
630985 1
 
< 0.1%
690000 1
 
< 0.1%
708000 1
 
< 0.1%
725000 1
 
< 0.1%
ValueCountFrequency (%)
15146749470 1
< 0.1%
8513319000 1
< 0.1%
7861002000 1
< 0.1%
7540930000 1
< 0.1%
6396890000 1
< 0.1%
6306630000 1
< 0.1%
5225652000 1
< 0.1%
3888000000 1
< 0.1%
3843317000 1
< 0.1%
3000000000 1
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
미도입
6838 
<NA>
2175 
도입
 
296

Length

Max length4
Median length3
Mean length3.2018477
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미도입
2nd row미도입
3rd row미도입
4th row미도입
5th row미도입

Common Values

ValueCountFrequency (%)
미도입 6838
73.5%
<NA> 2175
 
23.4%
도입 296
 
3.2%

Length

2023-12-13T02:52:19.552024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:19.710963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미도입 6838
73.5%
na 2175
 
23.4%
도입 296
 
3.2%

소프트웨어구축예산상용소프트웨어도입금액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct240
Distinct (%)3.4%
Missing2175
Missing (%)23.4%
Infinite0
Infinite (%)0.0%
Mean26515177
Minimum0
Maximum2.96085 × 1010
Zeros6838
Zeros (%)73.5%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:19.889375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum2.96085 × 1010
Range2.96085 × 1010
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.5289623 × 108
Coefficient of variation (CV)20.852067
Kurtosis2001.7902
Mean26515177
Median Absolute Deviation (MAD)0
Skewness42.050792
Sum1.8915927 × 1011
Variance3.0569424 × 1017
MonotonicityNot monotonic
2023-12-13T02:52:20.093147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6838
73.5%
200000000 8
 
0.1%
400000000 6
 
0.1%
50000000 5
 
0.1%
300000000 5
 
0.1%
30000000 4
 
< 0.1%
100000000 4
 
< 0.1%
120000000 3
 
< 0.1%
28000000 3
 
< 0.1%
5000000 3
 
< 0.1%
Other values (230) 255
 
2.7%
(Missing) 2175
 
23.4%
ValueCountFrequency (%)
0 6838
73.5%
353000 1
 
< 0.1%
500000 1
 
< 0.1%
792000 1
 
< 0.1%
1000000 1
 
< 0.1%
1264000 1
 
< 0.1%
1500000 3
 
< 0.1%
1788600 1
 
< 0.1%
2230000 1
 
< 0.1%
2354000 1
 
< 0.1%
ValueCountFrequency (%)
29608500000 1
< 0.1%
26524000000 1
< 0.1%
14895000000 1
< 0.1%
11526000000 1
< 0.1%
9006332000 1
< 0.1%
7038815000 1
< 0.1%
5197000000 1
< 0.1%
3905000000 1
< 0.1%
3000000000 1
< 0.1%
2394546000 1
< 0.1%
Distinct61
Distinct (%)3.6%
Missing7627
Missing (%)81.9%
Infinite0
Infinite (%)0.0%
Mean5.2694233
Minimum0
Maximum25
Zeros987
Zeros (%)10.6%
Negative0
Negative (%)0.0%
Memory size81.9 KiB
2023-12-13T02:52:20.323883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q312
95-th percentile16
Maximum25
Range25
Interquartile range (IQR)12

Descriptive statistics

Standard deviation6.5391915
Coefficient of variation (CV)1.2409691
Kurtosis-1.364483
Mean5.2694233
Median Absolute Deviation (MAD)0
Skewness0.58198761
Sum8863.17
Variance42.761026
MonotonicityNot monotonic
2023-12-13T02:52:20.530946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 987
 
10.6%
12.0 170
 
1.8%
15.0 91
 
1.0%
14.0 86
 
0.9%
10.0 68
 
0.7%
16.0 56
 
0.6%
13.0 44
 
0.5%
11.0 32
 
0.3%
8.0 31
 
0.3%
20.0 18
 
0.2%
Other values (51) 99
 
1.1%
(Missing) 7627
81.9%
ValueCountFrequency (%)
0.0 987
10.6%
5.0 4
 
< 0.1%
5.12 1
 
< 0.1%
5.43 1
 
< 0.1%
5.64 1
 
< 0.1%
6.0 5
 
0.1%
6.5 2
 
< 0.1%
6.7 1
 
< 0.1%
7.0 10
 
0.1%
8.0 31
 
0.3%
ValueCountFrequency (%)
25.0 1
 
< 0.1%
20.0 18
 
0.2%
19.0 2
 
< 0.1%
18.6 1
 
< 0.1%
18.0 14
 
0.2%
17.5 1
 
< 0.1%
16.0 56
0.6%
15.37 1
 
< 0.1%
15.3 1
 
< 0.1%
15.0 91
1.0%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.9 KiB
자체예산
4393 
정부(지자체)예산
2741 
<NA>
2175 

Length

Max length9
Median length4
Mean length5.4722312
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row자체예산
2nd row자체예산
3rd row자체예산
4th row자체예산
5th row정부(지자체)예산

Common Values

ValueCountFrequency (%)
자체예산 4393
47.2%
정부(지자체)예산 2741
29.4%
<NA> 2175
23.4%

Length

2023-12-13T02:52:20.720562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:52:20.875983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자체예산 4393
47.2%
정부(지자체)예산 2741
29.4%
na 2175
23.4%

Sample

기관명기관유형총예산하드웨어구매예산상용소프트웨어구매예산소프트웨어구축 사업계획 예산하드웨어 구매예산품목명(용도)하드웨어 구매예산구분코드하드웨어 구매예산정보통신기술-대분류하드웨어 구매예산정보통신기술-중분류하드웨어 구매예산정보통신기술-소분류하드웨어 구매예산구매예산하드웨어 구매예산구매수량하드웨어 구매예산1분기금액하드웨어 구매예산2분기금액하드웨어 구매예산3분기금액하드웨어 구매예산4분기금액하드웨어 구매예산리스여부하드웨어 구매예산재원하드웨어 구매예산발주처구분하드웨어 구매예산발주여부하드웨어 구매예산합계하드웨어 구매예산사업명하드웨어 구매예산사업개요하드웨어 구매예산사업기간하드웨어 구매예산사업예산상용소프트웨어예산품목명(용도)상용소프트웨어예산구분코드상용소프트웨어예산정보보호사업 구분코드상용소프트웨어예산정보보호사업 구분명상용소프트웨어예산구매예산상용소프트웨어예산1분기금액상용소프트웨어예산2분기금액상용소프트웨어예산3분기금액상용소프트웨어예산4분기금액상용소프트웨어예산합계상용소프트웨어예산재원상용소프트웨어예산구매처구분소프트웨어구축예산사업명소프트웨어구축예산사업개요소프트웨어구축예산사업분류소프트웨어구축예산사업유형소프트웨어구축예산신사업유형구분소프트웨어구축예산정보보호사업 해당여부소프트웨어구축예산정보보호사업 비율(퍼센트)소프트웨어구축예산정보보호사업 구분코드소프트웨어구축예산정보보호사업 구분명소프트웨어구축예산보안성지속서비스 세부 요율(퍼센트)소프트웨어구축예산발주시기소프트웨어구축예산대기업 참여제한 예외인정 여부소프트웨어구축예산총사업시작소프트웨어구축예산총사업종료소프트웨어구축예산총사업금액소프트웨어구축예산당해사업시작소프트웨어구축예산당해사업종료소프트웨어구축예산당해사업금액소프트웨어구축예산분리발주여부소프트웨어구축예산분리발주예산소프트웨어구축예산발주처구분소프트웨어구축예산발주여부소프트웨어구축예산하드웨어장비도입여부소프트웨어구축예산하드웨어장비도입금액소프트웨어구축예산하드웨어유지보수금액소프트웨어구축예산상용소프트웨어도입여부소프트웨어구축예산상용소프트웨어도입금액소프트웨어구축예산상용소프트웨어유지보수요율(퍼센트)소프트웨어구축예산재원
0(재)강원테크노파크공공기관190000000500000014000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>사무용SW개인 및 사무용 SW<NA><NA>500000005000000005000000자체예산(조달청)나라장터그룹웨어 유지보수그룹웨어 유지보수계속사업시스템운영유지관리 사업해당없음비해당<NA><NA><NA><NA>1분기해당사항없음2023-012023-12140000002023-012023-1214000000미추진0(기관)자체발주미발주미도입0<NA>미도입0<NA>자체예산
1(재)건설기술교육원공공기관490000000800000041000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>백신소프트웨어 구입보안 SWA02정보보안 제품-시스템(단말) 보안600000000060000006000000자체예산(조달청)나라장터교육관리시스템 유지보수기 구축된 교육관리시스템의 유지보수계속사업시스템운영유지관리 사업해당없음비해당<NA><NA><NA><NA>1분기해당사항없음2023-012023-12350000002023-012023-1235000000미추진0(기관)자체발주미발주미도입0<NA>미도입0<NA>자체예산
2(재)건설기술교육원공공기관490000000800000041000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>업무용 소프트웨어 구입개인 및 사무용 SW<NA><NA>200000001000000100000002000000자체예산(조달청)나라장터전산시스템(서버, 네트워크) 유지보수운영중인 서버, 네트워크 장비의 유지보수계속사업시스템운영유지관리 사업해당없음해당100%A03유지관리<NA>1분기해당사항없음2023-012023-1260000002023-012023-126000000미추진0(기관)자체발주미발주미도입0<NA>미도입0<NA>자체예산
3(재)경기문화재단 경기도박물관공공기관3840000003840000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>전산 유지관리전산 유지관리계속사업시스템운영유지관리 사업해당없음비해당<NA><NA><NA><NA>1분기해당사항없음2023-012023-1238400002023-012023-123840000미추진0(기관)자체발주미발주미도입0<NA>미도입0<NA>자체예산
4(재)경기콘텐츠진흥원공공기관132315400002690690001054085000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기게임아카데미 교육 운영기타응용 SW<NA><NA>750000000007500000075000000정부(지자체)예산(조달청)나라장터경기게임문화센터운영■ 사업목적 : 경기게임문화센터 사업 소개 등 홈페이지 유지보수 ■ 사업개요 - 경기게임문화센터 홈페이지 유지보수 - 23- 사업 내용 업데이트, 관리자 페이지 기능 강화 ■ 기대효과: 안정적인 홈페이지 운영계속사업시스템운영유지관리 사업해당없음비해당<NA><NA><NA><NA>2분기해당사항없음2023-042023-12100000002023-042023-1210000000미추진0(기관)자체발주미발주미도입0<NA>미도입0<NA>정부(지자체)예산
5(재)경기콘텐츠진흥원공공기관132315400002690690001054085000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>서부 창작터 스타트업 입주공간 운영지원 및 서부 창작터 교육 프로그램 지원기타응용 SW<NA><NA>585900000585900005859000정부(지자체)예산(조달청)나라장터2023- 경기글로벌게임센터 홈페이지 통합 유지관리■ 사업목적 : 홈페이지의 통합 관리 및 기술지원 ■ 사업개요 - 경기글로벌게임센터 홈페이지 운영 및 유지보수 - 경기글로벌게임센터 홈페이지 클라우드 서버 운영 - 새로운경기 게임오디션 홈페이지 클라우드 서버 운영 ■ 기대효과 : 온라인 서비스 안정성 확보계속사업시스템운영유지관리 사업해당없음비해당<NA><NA><NA><NA>1분기해당사항없음2023-012023-12330000002023-012023-1233000000미추진0(기관)자체발주미발주미도입013000000미도입0<NA>정부(지자체)예산
6(재)경기콘텐츠진흥원공공기관132315400002690690001054085000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>진흥원 업무협업솔루션 구매기타응용 SW<NA><NA>492100000492100000049210000정부(지자체)예산(기관)자체 구매2023- 플레이엑스포 홈페이지 리뉴얼■ 사업목적 : 플레이엑스포 운영 방식의 전환에 따른 디자인 및 콘텐츠 리뉴얼 ■ 사업개요 - 온/오프라인 전환에 따른 디자인 개편 - BMS 기능 개선 및 유지보수 - 시스템 오류 개선 및 장애 발생 시 즉각 대응 - 행사 업데이트에 따른 세부 기능 수정 보완 ■ 기대효과 : 전환 방식에 따른 유연한 대처로 안정적인 시스템 운영계속사업디지털콘텐츠개발서비스 사업해당없음비해당<NA><NA><NA><NA>2분기해당사항없음2023-042023-12440000002023-042023-1244000000미추진0(기관)자체발주미발주미도입0<NA>미도입0<NA>정부(지자체)예산
7(재)경기콘텐츠진흥원공공기관132315400002690690001054085000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>업무용 SW 구입기타응용 SW<NA><NA>1390000000254000005300000060600000139000000정부(지자체)예산(조달청)나라장터경기 콘텐츠코리아 랩 누리집(홈페이지) 유지관리■ 사업목적 : 사업 참여자 편의성 및 사업의 효율적 관리를 위한 홈페이지 운영 ■ 사업개요 - 경기콘텐츠코리아 랩 홈페이지 유지보수 - 민간 클라우드 서버 운영 ■ 기대효과 : 안정적인 홈페이지 운영계속사업시스템운영유지관리 사업해당없음비해당<NA><NA><NA><NA>1분기해당사항없음2023-012023-12264800002023-012023-1226480000미추진0(기관)자체발주미발주미도입05000000미도입0<NA>정부(지자체)예산
8(재)경기콘텐츠진흥원공공기관132315400002690690001054085000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기XR센터 홈페이지 통합관리■ 사업목적 : 경기XR센터 명칭변경 및 경기VRAR제작거점센터 추가 개소에 따른 별도의 독립 홈페이지 구축 ■ 사업개요 - 홈페이지 통합운영 유지보수 - 시설 대관/장비 대여 예약시스템 기능 개선 및 연동 ■ 기대효과 : 경기XR센터 페이지 관리 일원화를 통한 업무 효율성 증대계속사업시스템운영유지관리 사업해당없음비해당<NA><NA><NA><NA>2분기해당사항없음2023-042023-12500000002023-042023-1250000000미추진0(기관)자체발주미발주미도입010000000미도입0<NA>정부(지자체)예산
9(재)경기콘텐츠진흥원공공기관132315400002690690001054085000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>경기문화창조허브 홈페이지 관리■ 사업목적 : G-HUB 홈페이지 고도화 완료에 따른 유지보수 용역 추진 ■ 사업개요 - 홈페이지 디자인과 기능개선 및 유지관리 ■ 기대효과 : 안정적인 홈페이지 운영계속사업시스템운영유지관리 사업해당없음비해당<NA><NA><NA><NA>2분기해당사항없음2023-042023-12330000002023-042023-1233000000미추진0(기관)자체발주미발주미도입0<NA>미도입0<NA>정부(지자체)예산
기관명기관유형총예산하드웨어구매예산상용소프트웨어구매예산소프트웨어구축 사업계획 예산하드웨어 구매예산품목명(용도)하드웨어 구매예산구분코드하드웨어 구매예산정보통신기술-대분류하드웨어 구매예산정보통신기술-중분류하드웨어 구매예산정보통신기술-소분류하드웨어 구매예산구매예산하드웨어 구매예산구매수량하드웨어 구매예산1분기금액하드웨어 구매예산2분기금액하드웨어 구매예산3분기금액하드웨어 구매예산4분기금액하드웨어 구매예산리스여부하드웨어 구매예산재원하드웨어 구매예산발주처구분하드웨어 구매예산발주여부하드웨어 구매예산합계하드웨어 구매예산사업명하드웨어 구매예산사업개요하드웨어 구매예산사업기간하드웨어 구매예산사업예산상용소프트웨어예산품목명(용도)상용소프트웨어예산구분코드상용소프트웨어예산정보보호사업 구분코드상용소프트웨어예산정보보호사업 구분명상용소프트웨어예산구매예산상용소프트웨어예산1분기금액상용소프트웨어예산2분기금액상용소프트웨어예산3분기금액상용소프트웨어예산4분기금액상용소프트웨어예산합계상용소프트웨어예산재원상용소프트웨어예산구매처구분소프트웨어구축예산사업명소프트웨어구축예산사업개요소프트웨어구축예산사업분류소프트웨어구축예산사업유형소프트웨어구축예산신사업유형구분소프트웨어구축예산정보보호사업 해당여부소프트웨어구축예산정보보호사업 비율(퍼센트)소프트웨어구축예산정보보호사업 구분코드소프트웨어구축예산정보보호사업 구분명소프트웨어구축예산보안성지속서비스 세부 요율(퍼센트)소프트웨어구축예산발주시기소프트웨어구축예산대기업 참여제한 예외인정 여부소프트웨어구축예산총사업시작소프트웨어구축예산총사업종료소프트웨어구축예산총사업금액소프트웨어구축예산당해사업시작소프트웨어구축예산당해사업종료소프트웨어구축예산당해사업금액소프트웨어구축예산분리발주여부소프트웨어구축예산분리발주예산소프트웨어구축예산발주처구분소프트웨어구축예산발주여부소프트웨어구축예산하드웨어장비도입여부소프트웨어구축예산하드웨어장비도입금액소프트웨어구축예산하드웨어유지보수금액소프트웨어구축예산상용소프트웨어도입여부소프트웨어구축예산상용소프트웨어도입금액소프트웨어구축예산상용소프트웨어유지보수요율(퍼센트)소프트웨어구축예산재원
9299횡성군지자체33443640005456000001432700002655494000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>통합스토리지 및 백업sw유지보수통합스토리지, 백업sw 유지보수계속사업시스템운영유지관리 사업해당없음비해당<NA><NA><NA><NA>1분기해당사항없음2023-012023-12199800002023-012023-1219980000미추진0(기관)자체발주미발주미도입0<NA>미도입0<NA>자체예산
9300횡성군지자체33443640005456000001432700002655494000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>행정업무지원시스템 유지보수웹하드 등계속사업시스템운영유지관리 사업해당없음비해당<NA><NA><NA><NA>1분기해당사항없음2023-012023-1260170002023-012023-126017000미추진0(기관)자체발주미발주미도입0<NA>미도입0<NA>자체예산
9301횡성군지자체33443640005456000001432700002655494000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>가상화서버유지보수내외부 가상화서버, 솔루션계속사업시스템운영유지관리 사업해당없음비해당<NA><NA><NA><NA>1분기해당사항없음2023-012023-12100530002023-012023-1210053000미추진0(기관)자체발주미발주미도입0<NA>미도입0<NA>자체예산
9302횡성군지자체33443640005456000001432700002655494000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>홈페이지 개인정보차단 sw유지보수홈페이지 개인정보차단 sw유지보수계속사업시스템운영유지관리 사업해당없음해당100%A03유지관리<NA>1분기해당사항없음2023-012023-12115310002023-012023-1211531000미추진0(기관)자체발주미발주미도입0<NA>미도입013.0자체예산
9303횡성군지자체33443640005456000001432700002655494000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>행정망보안시스템 유지보수개인정보처리시스템 접근제어, 개인정보접속이력, 보안usb계속사업시스템운영유지관리 사업해당없음해당100%A03유지관리<NA>1분기해당사항없음2023-012023-12252370002023-012023-1225237000미추진0(기관)자체발주미발주미도입025237000미도입0<NA>자체예산
9304횡성군지자체33443640005456000001432700002655494000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>내외부망보안시스템 유지보수방화벽, 웹방화벽, pc개인정보보호시스템계속사업시스템운영유지관리 사업해당없음해당100%A03유지관리<NA>1분기해당사항없음2023-012023-1279990002023-012023-127999000미추진0(기관)자체발주미발주미도입07999000미도입0<NA>자체예산
9305횡성군지자체33443640005456000001432700002655494000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2023~2024 정보통신시스템 통합유지보수 용역2023~2024 정보통신시스템 통합유지보수 용역계속사업시스템운영유지관리 사업해당없음비해당<NA><NA><NA><NA>1분기해당사항없음2023-012024-122506430002023-012023-12124440000미추진0(조달청)위탁발주미발주미도입0<NA>미도입0<NA>자체예산
9306횡성군지자체33443640005456000001432700002655494000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>방송중계시스템 고도화방송중계시스템 고도화 사업신규사업시스템운용환경구축 사업해당없음비해당<NA><NA><NA><NA>1분기해당사항없음2023-012023-12998370002023-012023-1299837000미추진0(기관)자체발주미발주미도입0<NA>미도입0<NA>자체예산
9307횡성군지자체33443640005456000001432700002655494000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>네트워크접근제어 시스템 구축네트워크접근제어 시스템 구축 - 관리서버 및 차단센서 구축신규사업시스템운용환경구축 사업해당없음비해당<NA><NA><NA><NA>1분기해당사항없음2023-012023-121227600002023-012023-12122760000미추진0(기관)자체발주미발주미도입0<NA>미도입0<NA>자체예산
9308횡성군지자체33443640005456000001432700002655494000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>로컬cctv 유지보수로컬cctv 유지보수계속사업시스템운영유지관리 사업해당없음해당100%A03유지관리<NA>1분기해당사항없음2023-012023-12943240002023-012023-1294324000미추진0(기관)자체발주미발주미도입094324000미도입0<NA>자체예산

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기관명기관유형총예산하드웨어구매예산상용소프트웨어구매예산소프트웨어구축 사업계획 예산하드웨어 구매예산품목명(용도)하드웨어 구매예산구분코드하드웨어 구매예산정보통신기술-대분류하드웨어 구매예산정보통신기술-중분류하드웨어 구매예산정보통신기술-소분류하드웨어 구매예산구매예산하드웨어 구매예산구매수량하드웨어 구매예산1분기금액하드웨어 구매예산2분기금액하드웨어 구매예산3분기금액하드웨어 구매예산4분기금액하드웨어 구매예산리스여부하드웨어 구매예산재원하드웨어 구매예산발주처구분하드웨어 구매예산발주여부하드웨어 구매예산합계하드웨어 구매예산사업명하드웨어 구매예산사업개요하드웨어 구매예산사업기간하드웨어 구매예산사업예산상용소프트웨어예산품목명(용도)상용소프트웨어예산구분코드상용소프트웨어예산정보보호사업 구분코드상용소프트웨어예산정보보호사업 구분명상용소프트웨어예산구매예산상용소프트웨어예산1분기금액상용소프트웨어예산2분기금액상용소프트웨어예산3분기금액상용소프트웨어예산4분기금액상용소프트웨어예산합계상용소프트웨어예산재원상용소프트웨어예산구매처구분소프트웨어구축예산사업명소프트웨어구축예산사업개요소프트웨어구축예산사업분류소프트웨어구축예산사업유형소프트웨어구축예산신사업유형구분소프트웨어구축예산정보보호사업 해당여부소프트웨어구축예산정보보호사업 비율(퍼센트)소프트웨어구축예산정보보호사업 구분코드소프트웨어구축예산정보보호사업 구분명소프트웨어구축예산보안성지속서비스 세부 요율(퍼센트)소프트웨어구축예산발주시기소프트웨어구축예산대기업 참여제한 예외인정 여부소프트웨어구축예산총사업시작소프트웨어구축예산총사업종료소프트웨어구축예산총사업금액소프트웨어구축예산당해사업시작소프트웨어구축예산당해사업종료소프트웨어구축예산당해사업금액소프트웨어구축예산분리발주여부소프트웨어구축예산분리발주예산소프트웨어구축예산발주처구분소프트웨어구축예산발주여부소프트웨어구축예산하드웨어장비도입여부소프트웨어구축예산하드웨어장비도입금액소프트웨어구축예산하드웨어유지보수금액소프트웨어구축예산상용소프트웨어도입여부소프트웨어구축예산상용소프트웨어도입금액소프트웨어구축예산상용소프트웨어유지보수요율(퍼센트)소프트웨어구축예산재원# duplicates
0건강보험심사평가원공공기관558187059523252900000164767180050918134152<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>보안SW보안 SWA02정보보안 제품-시스템(단말) 보안288750000288750000028875000자체예산(조달청)나라장터<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
1정선군시설관리공단공공기관5150800050000001640000030108000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>사무용SW개인 및 사무용 SW<NA><NA>400000000040000004000000자체예산(기관)자체 구매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
2충북연구원공공기관41831000115980001783300012400000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>사무용SW개인 및 사무용 SW<NA><NA>500000015000003500000005000000자체예산(조달청)나라장터<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2