Overview

Dataset statistics

Number of variables54
Number of observations10000
Missing cells287732
Missing cells (%)53.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 MiB
Average record size in memory467.0 B

Variable types

Numeric24
Categorical8
Text17
DateTime5

Dataset

Description경주시 계약과정정보공개시스템에서 제공하는 계약현황자료입니다.(계약종류,계약명,계약일자,계약금액,계약자,계약방법,착공일자,준공일자 등)
Author경상북도 경주시
URLhttps://www.data.go.kr/data/15062850/fileData.do

Alerts

증감액 has constant value ""Constant
계약관서 is highly imbalanced (52.7%)Imbalance
계약방법 is highly imbalanced (63.1%)Imbalance
변경사유 is highly imbalanced (98.8%)Imbalance
선급금액3 is highly imbalanced (99.9%)Imbalance
하도급율3 is highly imbalanced (99.8%)Imbalance
착공일자 has 1765 (17.6%) missing valuesMissing
감독공무원 has 3130 (31.3%) missing valuesMissing
계약사유 has 338 (3.4%) missing valuesMissing
변경금액2 has 8140 (81.4%) missing valuesMissing
증감액2 has 8140 (81.4%) missing valuesMissing
변경일자2 has 8140 (81.4%) missing valuesMissing
변경사유2 has 8140 (81.4%) missing valuesMissing
변경금액3 has 9802 (98.0%) missing valuesMissing
증감액3 has 9802 (98.0%) missing valuesMissing
변경일자3 has 9802 (98.0%) missing valuesMissing
변경사유3 has 9802 (98.0%) missing valuesMissing
선급금액 has 9516 (95.2%) missing valuesMissing
선급금액2 has 9986 (99.9%) missing valuesMissing
기성금액 has 9718 (97.2%) missing valuesMissing
기성금액2 has 9884 (98.8%) missing valuesMissing
기성금액3 has 9931 (99.3%) missing valuesMissing
기성금액4 has 9964 (99.6%) missing valuesMissing
기성금액5 has 9967 (99.7%) missing valuesMissing
기성금액6 has 9970 (99.7%) missing valuesMissing
기성금액7 has 9976 (99.8%) missing valuesMissing
기성금액8 has 9993 (99.9%) missing valuesMissing
준공금액 has 1883 (18.8%) missing valuesMissing
업체명 has 9981 (99.8%) missing valuesMissing
계약대표자 has 9981 (99.8%) missing valuesMissing
공종 has 9981 (99.8%) missing valuesMissing
하도급율 has 9981 (99.8%) missing valuesMissing
업체명2 has 9992 (99.9%) missing valuesMissing
계약대표자2 has 9992 (99.9%) missing valuesMissing
공종2 has 9992 (99.9%) missing valuesMissing
하도급율2 has 9992 (99.9%) missing valuesMissing
업체명3 has 9997 (> 99.9%) missing valuesMissing
계약대표자3 has 9997 (> 99.9%) missing valuesMissing
공종3 has 9997 (> 99.9%) missing valuesMissing
예정가격 is highly skewed (γ1 = 28.05221516)Skewed
번호 has unique valuesUnique
예정가격 has 4990 (49.9%) zerosZeros
낙찰율 has 4935 (49.4%) zerosZeros

Reproduction

Analysis started2024-03-14 10:14:34.407939
Analysis finished2024-03-14 10:14:38.558848
Duration4.15 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7977.7762
Minimum2
Maximum15957
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:14:38.956460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile797.95
Q13997.5
median7979.5
Q311937.25
95-th percentile15143.1
Maximum15957
Range15955
Interquartile range (IQR)7939.75

Descriptive statistics

Standard deviation4601.8748
Coefficient of variation (CV)0.57683679
Kurtosis-1.2008544
Mean7977.7762
Median Absolute Deviation (MAD)3970
Skewness0.0018460464
Sum79777762
Variance21177252
MonotonicityNot monotonic
2024-03-14T19:14:39.407984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1624 1
 
< 0.1%
11677 1
 
< 0.1%
12065 1
 
< 0.1%
8055 1
 
< 0.1%
2439 1
 
< 0.1%
10753 1
 
< 0.1%
9580 1
 
< 0.1%
15846 1
 
< 0.1%
5840 1
 
< 0.1%
8855 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2 1
< 0.1%
3 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
10 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
15 1
< 0.1%
18 1
< 0.1%
ValueCountFrequency (%)
15957 1
< 0.1%
15954 1
< 0.1%
15952 1
< 0.1%
15951 1
< 0.1%
15948 1
< 0.1%
15947 1
< 0.1%
15943 1
< 0.1%
15942 1
< 0.1%
15941 1
< 0.1%
15940 1
< 0.1%

계약관서
Categorical

IMBALANCE 

Distinct36
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
본청
6622 
도시재생사업본부
 
462
양남면
 
251
외동읍
 
233
문무대왕면
 
201
Other values (31)
2231 

Length

Max length9
Median length2
Mean length2.7798
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row화랑마을
2nd row강동면
3rd row본청
4th row본청
5th row본청

Common Values

ValueCountFrequency (%)
본청 6622
66.2%
도시재생사업본부 462
 
4.6%
양남면 251
 
2.5%
외동읍 233
 
2.3%
문무대왕면 201
 
2.0%
북경주행정복지센터 188
 
1.9%
산내면 180
 
1.8%
강동면 179
 
1.8%
건천읍 171
 
1.7%
천북면 162
 
1.6%
Other values (26) 1351
 
13.5%

Length

2024-03-14T19:14:39.880350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
본청 6622
66.2%
도시재생사업본부 462
 
4.6%
양남면 251
 
2.5%
외동읍 233
 
2.3%
문무대왕면 201
 
2.0%
북경주행정복지센터 188
 
1.9%
산내면 180
 
1.8%
강동면 179
 
1.8%
건천읍 171
 
1.7%
천북면 162
 
1.6%
Other values (26) 1351
 
13.5%
Distinct9844
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T19:14:41.090623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length47
Mean length25.2514
Min length5

Characters and Unicode

Total characters252514
Distinct characters803
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9713 ?
Unique (%)97.1%

Sample

1st row어울마당 주변 정비 공사
2nd row왕신2리 농로포장공사 시행
3rd row모화일반산업단지 상수도 관로 개선 공사 폐기물 운반용역
4th row2021년 버스승강장 발열의자 전기 인입공사
5th row건천읍 신평1리 돈지들 용배수로 정비공사
ValueCountFrequency (%)
용역 2120
 
4.0%
구입 1376
 
2.6%
시행 1274
 
2.4%
정비공사 939
 
1.8%
924
 
1.7%
실시설계용역 827
 
1.5%
재해복구사업 787
 
1.5%
공사 758
 
1.4%
실시설계 683
 
1.3%
경주 584
 
1.1%
Other values (9177) 43124
80.8%
2024-03-14T19:14:42.526158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43571
 
17.3%
8930
 
3.5%
6854
 
2.7%
4945
 
2.0%
4934
 
2.0%
4734
 
1.9%
4229
 
1.7%
4044
 
1.6%
3947
 
1.6%
) 3504
 
1.4%
Other values (793) 162822
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 192477
76.2%
Space Separator 43571
 
17.3%
Decimal Number 7320
 
2.9%
Close Punctuation 3570
 
1.4%
Open Punctuation 3555
 
1.4%
Uppercase Letter 844
 
0.3%
Dash Punctuation 430
 
0.2%
Math Symbol 344
 
0.1%
Other Punctuation 335
 
0.1%
Lowercase Letter 65
 
< 0.1%
Other values (3) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8930
 
4.6%
6854
 
3.6%
4945
 
2.6%
4934
 
2.6%
4734
 
2.5%
4229
 
2.2%
4044
 
2.1%
3947
 
2.1%
3322
 
1.7%
3280
 
1.7%
Other values (720) 143258
74.4%
Uppercase Letter
ValueCountFrequency (%)
C 101
12.0%
S 86
10.2%
P 82
9.7%
E 74
8.8%
T 74
8.8%
A 60
 
7.1%
D 56
 
6.6%
I 55
 
6.5%
L 53
 
6.3%
B 41
 
4.9%
Other values (12) 162
19.2%
Lowercase Letter
ValueCountFrequency (%)
o 11
16.9%
g 10
15.4%
k 8
12.3%
t 7
10.8%
e 5
7.7%
p 5
7.7%
c 5
7.7%
i 4
 
6.2%
v 2
 
3.1%
l 2
 
3.1%
Other values (5) 6
9.2%
Other Punctuation
ValueCountFrequency (%)
, 222
66.3%
. 39
 
11.6%
· 27
 
8.1%
/ 16
 
4.8%
' 15
 
4.5%
" 6
 
1.8%
! 4
 
1.2%
: 2
 
0.6%
* 1
 
0.3%
@ 1
 
0.3%
Other values (2) 2
 
0.6%
Decimal Number
ValueCountFrequency (%)
2 2867
39.2%
1 1711
23.4%
3 805
 
11.0%
0 795
 
10.9%
4 371
 
5.1%
5 229
 
3.1%
9 155
 
2.1%
6 141
 
1.9%
8 125
 
1.7%
7 121
 
1.7%
Close Punctuation
ValueCountFrequency (%)
) 3504
98.2%
46
 
1.3%
13
 
0.4%
] 7
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 3489
98.1%
46
 
1.3%
13
 
0.4%
[ 7
 
0.2%
Space Separator
ValueCountFrequency (%)
43571
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 430
100.0%
Math Symbol
ValueCountFrequency (%)
~ 344
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 192477
76.2%
Common 59127
 
23.4%
Latin 910
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8930
 
4.6%
6854
 
3.6%
4945
 
2.6%
4934
 
2.6%
4734
 
2.5%
4229
 
2.2%
4044
 
2.1%
3947
 
2.1%
3322
 
1.7%
3280
 
1.7%
Other values (720) 143258
74.4%
Latin
ValueCountFrequency (%)
C 101
11.1%
S 86
 
9.5%
P 82
 
9.0%
E 74
 
8.1%
T 74
 
8.1%
A 60
 
6.6%
D 56
 
6.2%
I 55
 
6.0%
L 53
 
5.8%
B 41
 
4.5%
Other values (28) 228
25.1%
Common
ValueCountFrequency (%)
43571
73.7%
) 3504
 
5.9%
( 3489
 
5.9%
2 2867
 
4.8%
1 1711
 
2.9%
3 805
 
1.4%
0 795
 
1.3%
- 430
 
0.7%
4 371
 
0.6%
~ 344
 
0.6%
Other values (25) 1240
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 192474
76.2%
ASCII 59891
 
23.7%
None 145
 
0.1%
Compat Jamo 3
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43571
72.8%
) 3504
 
5.9%
( 3489
 
5.8%
2 2867
 
4.8%
1 1711
 
2.9%
3 805
 
1.3%
0 795
 
1.3%
- 430
 
0.7%
4 371
 
0.6%
~ 344
 
0.6%
Other values (57) 2004
 
3.3%
Hangul
ValueCountFrequency (%)
8930
 
4.6%
6854
 
3.6%
4945
 
2.6%
4934
 
2.6%
4734
 
2.5%
4229
 
2.2%
4044
 
2.1%
3947
 
2.1%
3322
 
1.7%
3280
 
1.7%
Other values (718) 143255
74.4%
None
ValueCountFrequency (%)
46
31.7%
46
31.7%
· 27
18.6%
13
 
9.0%
13
 
9.0%
Compat Jamo
ValueCountFrequency (%)
2
66.7%
1
33.3%
Number Forms
ValueCountFrequency (%)
1
100.0%

계약종류
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
용역
4362 
공사
3873 
물품
1765 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공사
2nd row공사
3rd row용역
4th row공사
5th row공사

Common Values

ValueCountFrequency (%)
용역 4362
43.6%
공사 3873
38.7%
물품 1765
17.6%

Length

2024-03-14T19:14:42.761485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:14:42.931032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용역 4362
43.6%
공사 3873
38.7%
물품 1765
17.6%

계약유형
Categorical

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
전문
2291 
기술
1647 
일반
1575 
구매
1170 
폐기물
856 
Other values (16)
2461 

Length

Max length6
Median length2
Mean length2.3661
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row종합
2nd row전문
3rd row폐기물
4th row전기
5th row전문

Common Values

ValueCountFrequency (%)
전문 2291
22.9%
기술 1647
16.5%
일반 1575
15.8%
구매 1170
11.7%
폐기물 856
 
8.6%
종합 782
 
7.8%
관급자재구매 532
 
5.3%
전기 411
 
4.1%
기타 183
 
1.8%
문화재 118
 
1.2%
Other values (11) 435
 
4.3%

Length

2024-03-14T19:14:43.171903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전문 2291
22.9%
기술 1647
16.5%
일반 1575
15.8%
구매 1170
11.7%
폐기물 856
 
8.6%
종합 782
 
7.8%
관급자재구매 532
 
5.3%
전기 411
 
4.1%
기타 183
 
1.8%
문화재 118
 
1.2%
Other values (11) 435
 
4.3%

계약방법
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수의1인견적
8231 
수의2인이상견적
1343 
제한경쟁
 
254
일반경쟁
 
171
지명경쟁
 
1

Length

Max length8
Median length6
Mean length6.1834
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row수의1인견적
2nd row수의1인견적
3rd row수의2인이상견적
4th row수의1인견적
5th row수의2인이상견적

Common Values

ValueCountFrequency (%)
수의1인견적 8231
82.3%
수의2인이상견적 1343
 
13.4%
제한경쟁 254
 
2.5%
일반경쟁 171
 
1.7%
지명경쟁 1
 
< 0.1%

Length

2024-03-14T19:14:43.612339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:14:43.968075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수의1인견적 8231
82.3%
수의2인이상견적 1343
 
13.4%
제한경쟁 254
 
2.5%
일반경쟁 171
 
1.7%
지명경쟁 1
 
< 0.1%
Distinct515
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-07-31 00:00:00
Maximum2024-01-31 00:00:00
2024-03-14T19:14:44.328384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:14:44.826627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최초계약금액
Real number (ℝ)

Distinct5329
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36221051
Minimum70000
Maximum3.9 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:14:45.290811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum70000
5-th percentile1254000
Q14210000
median10000000
Q319350000
95-th percentile1.1588807 × 108
Maximum3.9 × 109
Range3.89993 × 109
Interquartile range (IQR)15140000

Descriptive statistics

Standard deviation1.5513074 × 108
Coefficient of variation (CV)4.2828889
Kurtosis255.11733
Mean36221051
Median Absolute Deviation (MAD)7060000
Skewness14.057446
Sum3.6221051 × 1011
Variance2.4065545 × 1016
MonotonicityNot monotonic
2024-03-14T19:14:45.700212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18000000 87
 
0.9%
1140000 78
 
0.8%
19800000 75
 
0.8%
9700000 56
 
0.6%
3920000 56
 
0.6%
9200000 54
 
0.5%
14250000 53
 
0.5%
4850000 50
 
0.5%
4900000 43
 
0.4%
18600000 43
 
0.4%
Other values (5319) 9405
94.0%
ValueCountFrequency (%)
70000 1
< 0.1%
114000 1
< 0.1%
150000 1
< 0.1%
165000 2
< 0.1%
194000 1
< 0.1%
196000 1
< 0.1%
200000 2
< 0.1%
203000 1
< 0.1%
250000 1
< 0.1%
264000 1
< 0.1%
ValueCountFrequency (%)
3900000000 1
< 0.1%
3731000000 1
< 0.1%
3597000000 1
< 0.1%
3415000000 1
< 0.1%
3396716000 1
< 0.1%
3097660000 1
< 0.1%
3047500000 1
< 0.1%
3005575000 1
< 0.1%
3003765070 1
< 0.1%
2882000000 1
< 0.1%

계약금액
Real number (ℝ)

Distinct5538
Distinct (%)55.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37018128
Minimum0
Maximum3.9 × 109
Zeros6
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:14:46.003883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1240950
Q14229500
median10016625
Q319440000
95-th percentile1.2051841 × 108
Maximum3.9 × 109
Range3.9 × 109
Interquartile range (IQR)15210500

Descriptive statistics

Standard deviation1.5890527 × 108
Coefficient of variation (CV)4.2926339
Kurtosis243.00763
Mean37018128
Median Absolute Deviation (MAD)7093915
Skewness13.769648
Sum3.7018128 × 1011
Variance2.5250886 × 1016
MonotonicityNot monotonic
2024-03-14T19:14:46.428631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18000000 90
 
0.9%
19800000 73
 
0.7%
3920000 55
 
0.5%
9200000 55
 
0.5%
9700000 54
 
0.5%
14250000 51
 
0.5%
4850000 50
 
0.5%
4900000 42
 
0.4%
2000000 41
 
0.4%
18600000 38
 
0.4%
Other values (5528) 9451
94.5%
ValueCountFrequency (%)
0 6
0.1%
40480 1
 
< 0.1%
70000 1
 
< 0.1%
114000 1
 
< 0.1%
165000 1
 
< 0.1%
190000 5
0.1%
194000 1
 
< 0.1%
196000 1
 
< 0.1%
200000 2
 
< 0.1%
203000 1
 
< 0.1%
ValueCountFrequency (%)
3900000000 1
< 0.1%
3731000000 1
< 0.1%
3597000000 1
< 0.1%
3415000000 1
< 0.1%
3396716000 1
< 0.1%
3287730000 1
< 0.1%
3097660000 1
< 0.1%
3005575000 1
< 0.1%
3003765070 1
< 0.1%
2882000000 1
< 0.1%

착공일자
Date

MISSING 

Distinct666
Distinct (%)8.1%
Missing1765
Missing (%)17.6%
Memory size156.2 KiB
Minimum2020-01-01 00:00:00
Maximum2024-03-11 00:00:00
2024-03-14T19:14:46.848258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:14:47.174189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct1092
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2019-11-18 00:00:00
Maximum2029-02-12 00:00:00
2024-03-14T19:14:47.411979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:14:47.645816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2067
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T19:14:48.478088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length7.7411
Min length2

Characters and Unicode

Total characters77411
Distinct characters534
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1043 ?
Unique (%)10.4%

Sample

1st row(주)경주조경
2nd row미래건설석재
3rd row영남개발(주)
4th row(주)성보전력
5th row(주)영민토건
ValueCountFrequency (%)
주식회사 1226
 
10.7%
대구지방조달청 293
 
2.6%
평화상사 131
 
1.1%
주)창조이앤씨 116
 
1.0%
로드엔지니어링 108
 
0.9%
거창민석재산업 103
 
0.9%
주)유성엔지니어링 99
 
0.9%
주)서창건설엔지니어링 89
 
0.8%
주)신영엔지니어링 87
 
0.8%
한국신기술산업(주 87
 
0.8%
Other values (2107) 9115
79.6%
2024-03-14T19:14:49.482368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7329
 
9.5%
( 5930
 
7.7%
) 5930
 
7.7%
2699
 
3.5%
2477
 
3.2%
2162
 
2.8%
1598
 
2.1%
1481
 
1.9%
1455
 
1.9%
1434
 
1.9%
Other values (524) 44916
58.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63533
82.1%
Open Punctuation 5930
 
7.7%
Close Punctuation 5930
 
7.7%
Space Separator 1455
 
1.9%
Uppercase Letter 427
 
0.6%
Other Punctuation 72
 
0.1%
Lowercase Letter 42
 
0.1%
Decimal Number 17
 
< 0.1%
Other Symbol 3
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7329
 
11.5%
2699
 
4.2%
2477
 
3.9%
2162
 
3.4%
1598
 
2.5%
1481
 
2.3%
1434
 
2.3%
1425
 
2.2%
1326
 
2.1%
1297
 
2.0%
Other values (475) 40305
63.4%
Uppercase Letter
ValueCountFrequency (%)
C 75
17.6%
S 71
16.6%
N 66
15.5%
E 62
14.5%
G 61
14.3%
T 10
 
2.3%
M 10
 
2.3%
D 9
 
2.1%
J 8
 
1.9%
I 8
 
1.9%
Other values (14) 47
11.0%
Lowercase Letter
ValueCountFrequency (%)
o 7
16.7%
i 7
16.7%
t 6
14.3%
m 4
9.5%
r 4
9.5%
n 3
7.1%
a 3
7.1%
d 2
 
4.8%
u 2
 
4.8%
b 1
 
2.4%
Other values (3) 3
7.1%
Decimal Number
ValueCountFrequency (%)
1 8
47.1%
2 7
41.2%
0 1
 
5.9%
4 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
& 63
87.5%
. 6
 
8.3%
, 3
 
4.2%
Open Punctuation
ValueCountFrequency (%)
( 5930
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5930
100.0%
Space Separator
ValueCountFrequency (%)
1455
100.0%
Other Symbol
ValueCountFrequency (%)
3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63536
82.1%
Common 13406
 
17.3%
Latin 469
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7329
 
11.5%
2699
 
4.2%
2477
 
3.9%
2162
 
3.4%
1598
 
2.5%
1481
 
2.3%
1434
 
2.3%
1425
 
2.2%
1326
 
2.1%
1297
 
2.0%
Other values (476) 40308
63.4%
Latin
ValueCountFrequency (%)
C 75
16.0%
S 71
15.1%
N 66
14.1%
E 62
13.2%
G 61
13.0%
T 10
 
2.1%
M 10
 
2.1%
D 9
 
1.9%
J 8
 
1.7%
I 8
 
1.7%
Other values (27) 89
19.0%
Common
ValueCountFrequency (%)
( 5930
44.2%
) 5930
44.2%
1455
 
10.9%
& 63
 
0.5%
1 8
 
0.1%
2 7
 
0.1%
. 6
 
< 0.1%
, 3
 
< 0.1%
- 2
 
< 0.1%
0 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63533
82.1%
ASCII 13875
 
17.9%
None 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
7329
 
11.5%
2699
 
4.2%
2477
 
3.9%
2162
 
3.4%
1598
 
2.5%
1481
 
2.3%
1434
 
2.3%
1425
 
2.2%
1326
 
2.1%
1297
 
2.0%
Other values (475) 40305
63.4%
ASCII
ValueCountFrequency (%)
( 5930
42.7%
) 5930
42.7%
1455
 
10.5%
C 75
 
0.5%
S 71
 
0.5%
N 66
 
0.5%
& 63
 
0.5%
E 62
 
0.4%
G 61
 
0.4%
T 10
 
0.1%
Other values (38) 152
 
1.1%
None
ValueCountFrequency (%)
3
100.0%
Distinct1920
Distinct (%)19.3%
Missing50
Missing (%)0.5%
Memory size156.2 KiB
2024-03-14T19:14:50.587903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length3
Mean length3.2280402
Min length2

Characters and Unicode

Total characters32119
Distinct characters335
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique953 ?
Unique (%)9.6%

Sample

1st row견제필
2nd row한영진
3rd row조민재
4th row최영삼
5th row손복호
ValueCountFrequency (%)
대구지방조달청 145
 
1.4%
대구지방조달청장 133
 
1.3%
백영식 131
 
1.3%
정성용 116
 
1.2%
조재홍 108
 
1.1%
임은정 103
 
1.0%
정상희 99
 
1.0%
김순금 91
 
0.9%
홍순팔 86
 
0.9%
최병혁 83
 
0.8%
Other values (1925) 8941
89.1%
2024-03-14T19:14:51.948823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2032
 
6.3%
1558
 
4.9%
1284
 
4.0%
991
 
3.1%
774
 
2.4%
769
 
2.4%
749
 
2.3%
639
 
2.0%
629
 
2.0%
587
 
1.8%
Other values (325) 22107
68.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31786
99.0%
Space Separator 86
 
0.3%
Close Punctuation 68
 
0.2%
Open Punctuation 68
 
0.2%
Other Punctuation 55
 
0.2%
Uppercase Letter 50
 
0.2%
Decimal Number 3
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2032
 
6.4%
1558
 
4.9%
1284
 
4.0%
991
 
3.1%
774
 
2.4%
769
 
2.4%
749
 
2.4%
639
 
2.0%
629
 
2.0%
587
 
1.8%
Other values (305) 21774
68.5%
Uppercase Letter
ValueCountFrequency (%)
A 13
26.0%
O 7
14.0%
D 5
 
10.0%
E 5
 
10.0%
M 4
 
8.0%
Z 3
 
6.0%
N 3
 
6.0%
R 2
 
4.0%
L 2
 
4.0%
B 2
 
4.0%
Other values (2) 4
 
8.0%
Lowercase Letter
ValueCountFrequency (%)
g 1
33.3%
e 1
33.3%
n 1
33.3%
Space Separator
ValueCountFrequency (%)
86
100.0%
Close Punctuation
ValueCountFrequency (%)
) 68
100.0%
Open Punctuation
ValueCountFrequency (%)
( 68
100.0%
Other Punctuation
ValueCountFrequency (%)
, 55
100.0%
Decimal Number
ValueCountFrequency (%)
1 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31786
99.0%
Common 280
 
0.9%
Latin 53
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2032
 
6.4%
1558
 
4.9%
1284
 
4.0%
991
 
3.1%
774
 
2.4%
769
 
2.4%
749
 
2.4%
639
 
2.0%
629
 
2.0%
587
 
1.8%
Other values (305) 21774
68.5%
Latin
ValueCountFrequency (%)
A 13
24.5%
O 7
13.2%
D 5
 
9.4%
E 5
 
9.4%
M 4
 
7.5%
Z 3
 
5.7%
N 3
 
5.7%
R 2
 
3.8%
L 2
 
3.8%
B 2
 
3.8%
Other values (5) 7
13.2%
Common
ValueCountFrequency (%)
86
30.7%
) 68
24.3%
( 68
24.3%
, 55
19.6%
1 3
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31786
99.0%
ASCII 333
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2032
 
6.4%
1558
 
4.9%
1284
 
4.0%
991
 
3.1%
774
 
2.4%
769
 
2.4%
749
 
2.4%
639
 
2.0%
629
 
2.0%
587
 
1.8%
Other values (305) 21774
68.5%
ASCII
ValueCountFrequency (%)
86
25.8%
) 68
20.4%
( 68
20.4%
, 55
16.5%
A 13
 
3.9%
O 7
 
2.1%
D 5
 
1.5%
E 5
 
1.5%
M 4
 
1.2%
1 3
 
0.9%
Other values (10) 19
 
5.7%

주소
Text

Distinct2084
Distinct (%)20.9%
Missing10
Missing (%)0.1%
Memory size156.2 KiB
2024-03-14T19:14:52.835075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length24.096496
Min length6

Characters and Unicode

Total characters240724
Distinct characters439
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1092 ?
Unique (%)10.9%

Sample

1st row경상북도 경주시 양정로 227(동천동)
2nd row경상북도 경주시 백률로58번길 15(동천동)
3rd row경상북도 경주시 천북면 신당소티고개길 86-18
4th row경상북도 경주시 천북면 천북로 61
5th row경상북도 경주시 백률로8번길 7 (동천동)
ValueCountFrequency (%)
경상북도 8642
 
19.3%
경주시 7933
 
17.7%
대구광역시 733
 
1.6%
동천동 659
 
1.5%
천북면 517
 
1.2%
양정로 490
 
1.1%
2층 361
 
0.8%
안강읍 360
 
0.8%
달서구 341
 
0.8%
건천읍 338
 
0.8%
Other values (3562) 24373
54.5%
2024-03-14T19:14:53.956598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38462
 
16.0%
17148
 
7.1%
11935
 
5.0%
10199
 
4.2%
9830
 
4.1%
9080
 
3.8%
9060
 
3.8%
8401
 
3.5%
1 7658
 
3.2%
2 7420
 
3.1%
Other values (429) 111531
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 146070
60.7%
Decimal Number 39248
 
16.3%
Space Separator 38462
 
16.0%
Open Punctuation 6360
 
2.6%
Close Punctuation 6359
 
2.6%
Dash Punctuation 3413
 
1.4%
Other Punctuation 686
 
0.3%
Uppercase Letter 93
 
< 0.1%
Math Symbol 30
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
17148
 
11.7%
11935
 
8.2%
10199
 
7.0%
9830
 
6.7%
9080
 
6.2%
9060
 
6.2%
8401
 
5.8%
6737
 
4.6%
5467
 
3.7%
5063
 
3.5%
Other values (397) 53150
36.4%
Decimal Number
ValueCountFrequency (%)
1 7658
19.5%
2 7420
18.9%
4 3980
10.1%
3 3656
9.3%
5 3320
8.5%
0 3261
8.3%
7 2584
 
6.6%
8 2521
 
6.4%
9 2427
 
6.2%
6 2421
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
C 46
49.5%
K 25
26.9%
B 9
 
9.7%
A 5
 
5.4%
S 3
 
3.2%
Y 1
 
1.1%
T 1
 
1.1%
I 1
 
1.1%
L 1
 
1.1%
D 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 679
99.0%
. 3
 
0.4%
/ 2
 
0.3%
· 2
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
c 1
33.3%
a 1
33.3%
b 1
33.3%
Space Separator
ValueCountFrequency (%)
38462
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6360
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6359
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3413
100.0%
Math Symbol
ValueCountFrequency (%)
~ 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 146070
60.7%
Common 94558
39.3%
Latin 96
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
17148
 
11.7%
11935
 
8.2%
10199
 
7.0%
9830
 
6.7%
9080
 
6.2%
9060
 
6.2%
8401
 
5.8%
6737
 
4.6%
5467
 
3.7%
5063
 
3.5%
Other values (397) 53150
36.4%
Common
ValueCountFrequency (%)
38462
40.7%
1 7658
 
8.1%
2 7420
 
7.8%
( 6360
 
6.7%
) 6359
 
6.7%
4 3980
 
4.2%
3 3656
 
3.9%
- 3413
 
3.6%
5 3320
 
3.5%
0 3261
 
3.4%
Other values (9) 10669
 
11.3%
Latin
ValueCountFrequency (%)
C 46
47.9%
K 25
26.0%
B 9
 
9.4%
A 5
 
5.2%
S 3
 
3.1%
Y 1
 
1.0%
c 1
 
1.0%
T 1
 
1.0%
a 1
 
1.0%
I 1
 
1.0%
Other values (3) 3
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 146070
60.7%
ASCII 94652
39.3%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38462
40.6%
1 7658
 
8.1%
2 7420
 
7.8%
( 6360
 
6.7%
) 6359
 
6.7%
4 3980
 
4.2%
3 3656
 
3.9%
- 3413
 
3.6%
5 3320
 
3.5%
0 3261
 
3.4%
Other values (21) 10763
 
11.4%
Hangul
ValueCountFrequency (%)
17148
 
11.7%
11935
 
8.2%
10199
 
7.0%
9830
 
6.7%
9080
 
6.2%
9060
 
6.2%
8401
 
5.8%
6737
 
4.6%
5467
 
3.7%
5063
 
3.5%
Other values (397) 53150
36.4%
None
ValueCountFrequency (%)
· 2
100.0%

감독공무원
Text

MISSING 

Distinct530
Distinct (%)7.7%
Missing3130
Missing (%)31.3%
Memory size156.2 KiB
2024-03-14T19:14:55.211703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.99869
Min length2

Characters and Unicode

Total characters20601
Distinct characters168
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique155 ?
Unique (%)2.3%

Sample

1st row배무한
2nd row황태웅
3rd row이다혁
4th row김준성
5th row강동일
ValueCountFrequency (%)
강동일 151
 
2.2%
박영재 146
 
2.1%
최병국 142
 
2.1%
김정후 136
 
2.0%
이상영 113
 
1.6%
이재민 113
 
1.6%
김정민 111
 
1.6%
김동현 108
 
1.6%
정운상 108
 
1.6%
설준엽 107
 
1.6%
Other values (520) 5635
82.0%
2024-03-14T19:14:56.707853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1498
 
7.3%
1339
 
6.5%
944
 
4.6%
752
 
3.7%
685
 
3.3%
665
 
3.2%
608
 
3.0%
539
 
2.6%
524
 
2.5%
476
 
2.3%
Other values (158) 12571
61.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20601
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1498
 
7.3%
1339
 
6.5%
944
 
4.6%
752
 
3.7%
685
 
3.3%
665
 
3.2%
608
 
3.0%
539
 
2.6%
524
 
2.5%
476
 
2.3%
Other values (158) 12571
61.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20601
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1498
 
7.3%
1339
 
6.5%
944
 
4.6%
752
 
3.7%
685
 
3.3%
665
 
3.2%
608
 
3.0%
539
 
2.6%
524
 
2.5%
476
 
2.3%
Other values (158) 12571
61.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20601
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1498
 
7.3%
1339
 
6.5%
944
 
4.6%
752
 
3.7%
685
 
3.3%
665
 
3.2%
608
 
3.0%
539
 
2.6%
524
 
2.5%
476
 
2.3%
Other values (158) 12571
61.0%

계약사유
Text

MISSING 

Distinct112
Distinct (%)1.2%
Missing338
Missing (%)3.4%
Memory size156.2 KiB
2024-03-14T19:14:57.449934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length118
Median length114
Mean length73.541192
Min length2

Characters and Unicode

Total characters710555
Distinct characters255
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)0.7%

Sample

1st row「건설산업기본법」외의 공사 관련 법령에 따른 공사로서 추정가격이 8천만원 이하인 공사에 대한 계약(제25조제1항제5호가목)
2nd row「건설산업기본법」에 따른 건설공사로 추정가격 2억원 이하의 공사, 같은 법에 따른 전문공사로 추정가격 1억원 이하의 공사 계약(제25조제1항제5호가목)
3rd row추정가격 2천만원 이하의 물품의 제조·구매계약 또는 용역계약(제25조제1항제5호나목)
4th row「건설산업기본법」에 따른 건설공사로 추정가격 2억원 이하의 공사, 같은 법에 따른 전문공사로 추정가격 1억원 이하의 공사 계약(제25조제1항제5호가목)
5th row「건설산업기본법」에 따른 건설공사로 추정가격 4억원 이하의 공사, 같은 법에 따른 전문공사로 추정가격 2억원 이하의 공사 계약(제25조제1항제5호가목)
ValueCountFrequency (%)
추정가격 13213
 
11.3%
따른 9082
 
7.8%
이하의 7848
 
6.7%
2천만원 7513
 
6.4%
또는 4871
 
4.2%
물품의 4733
 
4.1%
제조·구매계약 4509
 
3.9%
용역계약(제25조제1항제5호나목 4509
 
3.9%
공사 3311
 
2.8%
관한 2829
 
2.4%
Other values (376) 54091
46.4%
2024-03-14T19:14:58.852690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
106882
 
15.0%
36200
 
5.1%
2 18787
 
2.6%
17156
 
2.4%
16846
 
2.4%
5 16272
 
2.3%
15871
 
2.2%
15802
 
2.2%
14166
 
2.0%
13966
 
2.0%
Other values (245) 438607
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 494680
69.6%
Space Separator 106882
 
15.0%
Decimal Number 52169
 
7.3%
Other Punctuation 22816
 
3.2%
Close Punctuation 16999
 
2.4%
Open Punctuation 16998
 
2.4%
Dash Punctuation 5
 
< 0.1%
Uppercase Letter 4
 
< 0.1%
Other Number 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
36200
 
7.3%
17156
 
3.5%
16846
 
3.4%
15871
 
3.2%
15802
 
3.2%
14166
 
2.9%
13966
 
2.8%
13937
 
2.8%
13872
 
2.8%
13658
 
2.8%
Other values (219) 323206
65.3%
Decimal Number
ValueCountFrequency (%)
2 18787
36.0%
5 16272
31.2%
1 10867
20.8%
3 2764
 
5.3%
0 2689
 
5.2%
4 476
 
0.9%
8 222
 
0.4%
6 75
 
0.1%
7 12
 
< 0.1%
9 5
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
· 10351
45.4%
, 9781
42.9%
. 2681
 
11.8%
* 1
 
< 0.1%
% 1
 
< 0.1%
: 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 9572
56.3%
7427
43.7%
Open Punctuation
ValueCountFrequency (%)
( 9571
56.3%
7427
43.7%
Uppercase Letter
ValueCountFrequency (%)
P 2
50.0%
Q 2
50.0%
Space Separator
ValueCountFrequency (%)
106882
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Number
ValueCountFrequency (%)
1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 494680
69.6%
Common 215871
30.4%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
36200
 
7.3%
17156
 
3.5%
16846
 
3.4%
15871
 
3.2%
15802
 
3.2%
14166
 
2.9%
13966
 
2.8%
13937
 
2.8%
13872
 
2.8%
13658
 
2.8%
Other values (219) 323206
65.3%
Common
ValueCountFrequency (%)
106882
49.5%
2 18787
 
8.7%
5 16272
 
7.5%
1 10867
 
5.0%
· 10351
 
4.8%
, 9781
 
4.5%
) 9572
 
4.4%
( 9571
 
4.4%
7427
 
3.4%
7427
 
3.4%
Other values (14) 8934
 
4.1%
Latin
ValueCountFrequency (%)
P 2
50.0%
Q 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 494591
69.6%
ASCII 190669
 
26.8%
None 25205
 
3.5%
Compat Jamo 89
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
106882
56.1%
2 18787
 
9.9%
5 16272
 
8.5%
1 10867
 
5.7%
, 9781
 
5.1%
) 9572
 
5.0%
( 9571
 
5.0%
3 2764
 
1.4%
0 2689
 
1.4%
. 2681
 
1.4%
Other values (12) 803
 
0.4%
Hangul
ValueCountFrequency (%)
36200
 
7.3%
17156
 
3.5%
16846
 
3.4%
15871
 
3.2%
15802
 
3.2%
14166
 
2.9%
13966
 
2.8%
13937
 
2.8%
13872
 
2.8%
13658
 
2.8%
Other values (218) 323117
65.3%
None
ValueCountFrequency (%)
· 10351
41.1%
7427
29.5%
7427
29.5%
Compat Jamo
ValueCountFrequency (%)
89
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
100.0%

변경금액
Real number (ℝ)

Distinct5329
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36221051
Minimum70000
Maximum3.9 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:14:59.270908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum70000
5-th percentile1254000
Q14210000
median10000000
Q319350000
95-th percentile1.1588807 × 108
Maximum3.9 × 109
Range3.89993 × 109
Interquartile range (IQR)15140000

Descriptive statistics

Standard deviation1.5513074 × 108
Coefficient of variation (CV)4.2828889
Kurtosis255.11733
Mean36221051
Median Absolute Deviation (MAD)7060000
Skewness14.057446
Sum3.6221051 × 1011
Variance2.4065545 × 1016
MonotonicityNot monotonic
2024-03-14T19:14:59.732458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18000000 87
 
0.9%
1140000 78
 
0.8%
19800000 75
 
0.8%
9700000 56
 
0.6%
3920000 56
 
0.6%
9200000 54
 
0.5%
14250000 53
 
0.5%
4850000 50
 
0.5%
4900000 43
 
0.4%
18600000 43
 
0.4%
Other values (5319) 9405
94.0%
ValueCountFrequency (%)
70000 1
< 0.1%
114000 1
< 0.1%
150000 1
< 0.1%
165000 2
< 0.1%
194000 1
< 0.1%
196000 1
< 0.1%
200000 2
< 0.1%
203000 1
< 0.1%
250000 1
< 0.1%
264000 1
< 0.1%
ValueCountFrequency (%)
3900000000 1
< 0.1%
3731000000 1
< 0.1%
3597000000 1
< 0.1%
3415000000 1
< 0.1%
3396716000 1
< 0.1%
3097660000 1
< 0.1%
3047500000 1
< 0.1%
3005575000 1
< 0.1%
3003765070 1
< 0.1%
2882000000 1
< 0.1%

증감액
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2024-03-14T19:15:00.158704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:15:00.450333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%
Distinct654
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-08-09 00:00:00
Maximum2024-01-31 00:00:00
2024-03-14T19:15:00.758747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:15:01.203056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

변경사유
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
최초생성
9989 
최초계약사항
 
11

Length

Max length6
Median length4
Mean length4.0022
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
최초생성 9989
99.9%
최초계약사항 11
 
0.1%

Length

2024-03-14T19:15:01.662705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:15:01.995598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
최초생성 9989
99.9%
최초계약사항 11
 
0.1%

변경금액2
Real number (ℝ)

MISSING 

Distinct1729
Distinct (%)93.0%
Missing8140
Missing (%)81.4%
Infinite0
Infinite (%)0.0%
Mean74633740
Minimum0
Maximum3.28773 × 109
Zeros6
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:15:02.332286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1200000
Q110746750
median22853000
Q366509750
95-th percentile2.96772 × 108
Maximum3.28773 × 109
Range3.28773 × 109
Interquartile range (IQR)55763000

Descriptive statistics

Standard deviation1.815316 × 108
Coefficient of variation (CV)2.4322994
Kurtosis92.351491
Mean74633740
Median Absolute Deviation (MAD)18735250
Skewness7.8856362
Sum1.3881876 × 1011
Variance3.2953723 × 1016
MonotonicityNot monotonic
2024-03-14T19:15:02.790915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
760000 26
 
0.3%
90000000 18
 
0.2%
950000 13
 
0.1%
570000 7
 
0.1%
0 6
 
0.1%
1200000 6
 
0.1%
21800000 5
 
0.1%
10000000 5
 
0.1%
190000 5
 
0.1%
380000 4
 
< 0.1%
Other values (1719) 1765
 
17.6%
(Missing) 8140
81.4%
ValueCountFrequency (%)
0 6
0.1%
40480 1
 
< 0.1%
190000 5
0.1%
209000 1
 
< 0.1%
239000 1
 
< 0.1%
267960 1
 
< 0.1%
354960 1
 
< 0.1%
374000 1
 
< 0.1%
379500 1
 
< 0.1%
380000 4
< 0.1%
ValueCountFrequency (%)
3287730000 1
< 0.1%
2421352000 1
< 0.1%
2059910000 1
< 0.1%
1755640000 1
< 0.1%
1574400000 1
< 0.1%
1514403000 1
< 0.1%
1448825000 1
< 0.1%
1439900000 1
< 0.1%
1351110000 1
< 0.1%
1268700000 1
< 0.1%

증감액2
Real number (ℝ)

MISSING 

Distinct1696
Distinct (%)91.2%
Missing8140
Missing (%)81.4%
Infinite0
Infinite (%)0.0%
Mean4290076.8
Minimum-2.958439 × 108
Maximum5.39799 × 108
Zeros0
Zeros (%)0.0%
Negative861
Negative (%)8.6%
Memory size166.0 KiB
2024-03-14T19:15:03.210474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.958439 × 108
5-th percentile-6427361.5
Q1-963750
median360000
Q33613165
95-th percentile23077934
Maximum5.39799 × 108
Range8.356429 × 108
Interquartile range (IQR)4576915

Descriptive statistics

Standard deviation28417969
Coefficient of variation (CV)6.6241168
Kurtosis193.98113
Mean4290076.8
Median Absolute Deviation (MAD)1970620
Skewness10.826454
Sum7.9795428 × 109
Variance8.0758098 × 1014
MonotonicityNot monotonic
2024-03-14T19:15:03.627944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-380000 21
 
0.2%
-190000 13
 
0.1%
-570000 11
 
0.1%
-760000 9
 
0.1%
-50000 7
 
0.1%
-240000 6
 
0.1%
1030000 4
 
< 0.1%
-70000 4
 
< 0.1%
-480000 3
 
< 0.1%
50000 3
 
< 0.1%
Other values (1686) 1779
 
17.8%
(Missing) 8140
81.4%
ValueCountFrequency (%)
-295843900 1
< 0.1%
-117300000 1
< 0.1%
-95327260 1
< 0.1%
-78724800 1
< 0.1%
-59956000 1
< 0.1%
-55130000 1
< 0.1%
-45203160 1
< 0.1%
-44736000 1
< 0.1%
-41547000 1
< 0.1%
-39119060 1
< 0.1%
ValueCountFrequency (%)
539799000 1
< 0.1%
530209940 1
< 0.1%
451810000 1
< 0.1%
396150000 1
< 0.1%
240230000 1
< 0.1%
180395000 1
< 0.1%
172094600 1
< 0.1%
154885000 1
< 0.1%
152353000 1
< 0.1%
127793610 1
< 0.1%

변경일자2
Date

MISSING 

Distinct485
Distinct (%)26.1%
Missing8140
Missing (%)81.4%
Memory size156.2 KiB
Minimum2021-08-31 00:00:00
Maximum2202-04-28 00:00:00
2024-03-14T19:15:04.010011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:15:04.424613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

변경사유2
Text

MISSING 

Distinct685
Distinct (%)36.8%
Missing8140
Missing (%)81.4%
Memory size156.2 KiB
2024-03-14T19:15:05.747189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length197
Median length88
Mean length14.031183
Min length2

Characters and Unicode

Total characters26098
Distinct characters431
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique549 ?
Unique (%)29.5%

Sample

1st row물량변경에 따른 변경
2nd row설계변경 및 제경비 정산
3rd row설계변경
4th row설계변경 및 제경비 정산
5th row본공사 영농기 시공중지 기간 제외 및 공기 변경에 따른 용역기간 연장 및 점검횟수 정산 시행
ValueCountFrequency (%)
정산 684
 
9.9%
설계변경 591
 
8.6%
따른 499
 
7.2%
443
 
6.4%
보험료 308
 
4.5%
제경비 298
 
4.3%
변경 231
 
3.4%
159
 
2.3%
물량 146
 
2.1%
감액 146
 
2.1%
Other values (1177) 3383
49.1%
2024-03-14T19:15:07.667906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5050
 
19.4%
1490
 
5.7%
1152
 
4.4%
989
 
3.8%
952
 
3.6%
903
 
3.5%
861
 
3.3%
591
 
2.3%
508
 
1.9%
508
 
1.9%
Other values (421) 13094
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19537
74.9%
Space Separator 5050
 
19.4%
Decimal Number 851
 
3.3%
Other Punctuation 235
 
0.9%
Open Punctuation 130
 
0.5%
Close Punctuation 129
 
0.5%
Dash Punctuation 65
 
0.2%
Math Symbol 45
 
0.2%
Lowercase Letter 29
 
0.1%
Uppercase Letter 24
 
0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1490
 
7.6%
1152
 
5.9%
989
 
5.1%
952
 
4.9%
903
 
4.6%
861
 
4.4%
591
 
3.0%
508
 
2.6%
508
 
2.6%
492
 
2.5%
Other values (377) 11091
56.8%
Uppercase Letter
ValueCountFrequency (%)
L 3
12.5%
A 3
12.5%
T 3
12.5%
D 3
12.5%
S 2
8.3%
P 2
8.3%
C 2
8.3%
K 2
8.3%
U 1
 
4.2%
W 1
 
4.2%
Other values (2) 2
8.3%
Decimal Number
ValueCountFrequency (%)
2 201
23.6%
1 153
18.0%
0 135
15.9%
4 81
9.5%
5 64
 
7.5%
3 59
 
6.9%
6 49
 
5.8%
8 43
 
5.1%
7 36
 
4.2%
9 30
 
3.5%
Lowercase Letter
ValueCountFrequency (%)
m 11
37.9%
h 7
24.1%
a 7
24.1%
f 1
 
3.4%
d 1
 
3.4%
n 1
 
3.4%
o 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 120
51.1%
, 100
42.6%
: 8
 
3.4%
% 5
 
2.1%
* 1
 
0.4%
/ 1
 
0.4%
Math Symbol
ValueCountFrequency (%)
> 27
60.0%
17
37.8%
= 1
 
2.2%
Space Separator
ValueCountFrequency (%)
5050
100.0%
Open Punctuation
ValueCountFrequency (%)
( 130
100.0%
Close Punctuation
ValueCountFrequency (%)
) 129
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19537
74.9%
Common 6508
 
24.9%
Latin 53
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1490
 
7.6%
1152
 
5.9%
989
 
5.1%
952
 
4.9%
903
 
4.6%
861
 
4.4%
591
 
3.0%
508
 
2.6%
508
 
2.6%
492
 
2.5%
Other values (377) 11091
56.8%
Common
ValueCountFrequency (%)
5050
77.6%
2 201
 
3.1%
1 153
 
2.4%
0 135
 
2.1%
( 130
 
2.0%
) 129
 
2.0%
. 120
 
1.8%
, 100
 
1.5%
4 81
 
1.2%
- 65
 
1.0%
Other values (15) 344
 
5.3%
Latin
ValueCountFrequency (%)
m 11
20.8%
h 7
13.2%
a 7
13.2%
L 3
 
5.7%
A 3
 
5.7%
T 3
 
5.7%
D 3
 
5.7%
S 2
 
3.8%
P 2
 
3.8%
C 2
 
3.8%
Other values (9) 10
18.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19532
74.8%
ASCII 6543
 
25.1%
Arrows 17
 
0.1%
Compat Jamo 5
 
< 0.1%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5050
77.2%
2 201
 
3.1%
1 153
 
2.3%
0 135
 
2.1%
( 130
 
2.0%
) 129
 
2.0%
. 120
 
1.8%
, 100
 
1.5%
4 81
 
1.2%
- 65
 
1.0%
Other values (32) 379
 
5.8%
Hangul
ValueCountFrequency (%)
1490
 
7.6%
1152
 
5.9%
989
 
5.1%
952
 
4.9%
903
 
4.6%
861
 
4.4%
591
 
3.0%
508
 
2.6%
508
 
2.6%
492
 
2.5%
Other values (373) 11086
56.8%
Arrows
ValueCountFrequency (%)
17
100.0%
Compat Jamo
ValueCountFrequency (%)
2
40.0%
1
20.0%
1
20.0%
1
20.0%
CJK Compat
ValueCountFrequency (%)
1
100.0%

변경금액3
Real number (ℝ)

MISSING 

Distinct198
Distinct (%)100.0%
Missing9802
Missing (%)98.0%
Infinite0
Infinite (%)0.0%
Mean1.5710465 × 108
Minimum943000
Maximum1.8928 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:15:08.081898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum943000
5-th percentile4419300
Q132762000
median77915500
Q31.90869 × 108
95-th percentile4.8973006 × 108
Maximum1.8928 × 109
Range1.891857 × 109
Interquartile range (IQR)1.58107 × 108

Descriptive statistics

Standard deviation2.5396009 × 108
Coefficient of variation (CV)1.6165027
Kurtosis26.485821
Mean1.5710465 × 108
Median Absolute Deviation (MAD)59199910
Skewness4.623699
Sum3.110672 × 1010
Variance6.4495729 × 1016
MonotonicityNot monotonic
2024-03-14T19:15:08.492273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99611000 1
 
< 0.1%
14257200 1
 
< 0.1%
24614000 1
 
< 0.1%
45640000 1
 
< 0.1%
67268000 1
 
< 0.1%
585276100 1
 
< 0.1%
12160000 1
 
< 0.1%
101412000 1
 
< 0.1%
49599400 1
 
< 0.1%
37288000 1
 
< 0.1%
Other values (188) 188
 
1.9%
(Missing) 9802
98.0%
ValueCountFrequency (%)
943000 1
< 0.1%
1330000 1
< 0.1%
1730000 1
< 0.1%
2112000 1
< 0.1%
2160000 1
< 0.1%
3760900 1
< 0.1%
3787300 1
< 0.1%
3821400 1
< 0.1%
4160000 1
< 0.1%
4183000 1
< 0.1%
ValueCountFrequency (%)
1892800000 1
< 0.1%
1794555000 1
< 0.1%
1755000000 1
< 0.1%
852169000 1
< 0.1%
758560000 1
< 0.1%
703800000 1
< 0.1%
640774000 1
< 0.1%
600281000 1
< 0.1%
591666900 1
< 0.1%
585276100 1
< 0.1%

증감액3
Real number (ℝ)

MISSING 

Distinct192
Distinct (%)97.0%
Missing9802
Missing (%)98.0%
Infinite0
Infinite (%)0.0%
Mean157011.57
Minimum-48050000
Maximum4.529 × 108
Zeros1
Zeros (%)< 0.1%
Negative174
Negative (%)1.7%
Memory size166.0 KiB
2024-03-14T19:15:08.752917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-48050000
5-th percentile-24270405
Q1-3661867.5
median-1083000
Q3-233942.5
95-th percentile3225985
Maximum4.529 × 108
Range5.0095 × 108
Interquartile range (IQR)3427925

Descriptive statistics

Standard deviation39678031
Coefficient of variation (CV)252.7077
Kurtosis98.802411
Mean157011.57
Median Absolute Deviation (MAD)1043200
Skewness9.4258623
Sum31088290
Variance1.5743462 × 1015
MonotonicityNot monotonic
2024-03-14T19:15:09.003172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-150000 2
 
< 0.1%
-319000 2
 
< 0.1%
-6000 2
 
< 0.1%
-40000 2
 
< 0.1%
-93000 2
 
< 0.1%
-1320000 2
 
< 0.1%
3520000 1
 
< 0.1%
-1572000 1
 
< 0.1%
3174100 1
 
< 0.1%
-80000 1
 
< 0.1%
Other values (182) 182
 
1.8%
(Missing) 9802
98.0%
ValueCountFrequency (%)
-48050000 1
< 0.1%
-43180000 1
< 0.1%
-41099000 1
< 0.1%
-39020000 1
< 0.1%
-36562000 1
< 0.1%
-32306000 1
< 0.1%
-32074000 1
< 0.1%
-28232000 1
< 0.1%
-25949000 1
< 0.1%
-24272700 1
< 0.1%
ValueCountFrequency (%)
452900000 1
< 0.1%
280152000 1
< 0.1%
86585000 1
< 0.1%
17236000 1
< 0.1%
14464000 1
< 0.1%
8074080 1
< 0.1%
6592000 1
< 0.1%
6500000 1
< 0.1%
5760000 1
< 0.1%
3520000 1
< 0.1%

변경일자3
Real number (ℝ)

MISSING 

Distinct149
Distinct (%)75.3%
Missing9802
Missing (%)98.0%
Infinite0
Infinite (%)0.0%
Mean20227204
Minimum20211108
Maximum20240130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:15:09.251281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20211108
5-th percentile20220295
Q120220712
median20230625
Q320231031
95-th percentile20231222
Maximum20240130
Range29022
Interquartile range (IQR)10319.25

Descriptive statistics

Standard deviation5960.4184
Coefficient of variation (CV)0.00029467337
Kurtosis0.1621429
Mean20227204
Median Absolute Deviation (MAD)581.5
Skewness-0.84381196
Sum4.0049864 × 109
Variance35526587
MonotonicityNot monotonic
2024-03-14T19:15:09.582839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20231222 7
 
0.1%
20231220 4
 
< 0.1%
20231031 4
 
< 0.1%
20230327 3
 
< 0.1%
20220330 3
 
< 0.1%
20231215 3
 
< 0.1%
20230616 3
 
< 0.1%
20211209 3
 
< 0.1%
20220624 3
 
< 0.1%
20230926 2
 
< 0.1%
Other values (139) 163
 
1.6%
(Missing) 9802
98.0%
ValueCountFrequency (%)
20211108 1
 
< 0.1%
20211112 1
 
< 0.1%
20211207 1
 
< 0.1%
20211209 3
< 0.1%
20211213 1
 
< 0.1%
20211231 1
 
< 0.1%
20220127 1
 
< 0.1%
20220228 1
 
< 0.1%
20220307 1
 
< 0.1%
20220316 1
 
< 0.1%
ValueCountFrequency (%)
20240130 1
 
< 0.1%
20240129 1
 
< 0.1%
20240118 1
 
< 0.1%
20240109 1
 
< 0.1%
20231228 1
 
< 0.1%
20231227 2
 
< 0.1%
20231226 2
 
< 0.1%
20231222 7
0.1%
20231221 1
 
< 0.1%
20231220 4
< 0.1%

변경사유3
Text

MISSING 

Distinct93
Distinct (%)47.0%
Missing9802
Missing (%)98.0%
Memory size156.2 KiB
2024-03-14T19:15:10.222219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length25
Mean length12.994949
Min length1

Characters and Unicode

Total characters2573
Distinct characters123
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)33.3%

Sample

1st row실처리량 기준으로 정산
2nd row보험료정산에 따른 감액
3rd row보험료 정산에 따른 감액
4th row보험료 등 정산
5th row정산감액
ValueCountFrequency (%)
정산 112
16.4%
보험료 81
11.9%
61
 
8.9%
따른 59
 
8.6%
사후정산제에 45
 
6.6%
의거 40
 
5.9%
감액 37
 
5.4%
제경비 26
 
3.8%
정산에 21
 
3.1%
설계변경 14
 
2.0%
Other values (89) 187
27.4%
2024-03-14T19:15:11.550743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
489
19.0%
215
 
8.4%
209
 
8.1%
119
 
4.6%
101
 
3.9%
101
 
3.9%
98
 
3.8%
85
 
3.3%
73
 
2.8%
61
 
2.4%
Other values (113) 1022
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2023
78.6%
Space Separator 489
 
19.0%
Decimal Number 30
 
1.2%
Other Punctuation 11
 
0.4%
Close Punctuation 8
 
0.3%
Open Punctuation 8
 
0.3%
Dash Punctuation 3
 
0.1%
Control 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
215
 
10.6%
209
 
10.3%
119
 
5.9%
101
 
5.0%
101
 
5.0%
98
 
4.8%
85
 
4.2%
73
 
3.6%
61
 
3.0%
60
 
3.0%
Other values (97) 901
44.5%
Decimal Number
ValueCountFrequency (%)
2 10
33.3%
7 7
23.3%
0 3
 
10.0%
1 3
 
10.0%
8 2
 
6.7%
4 2
 
6.7%
3 1
 
3.3%
6 1
 
3.3%
5 1
 
3.3%
Other Punctuation
ValueCountFrequency (%)
. 7
63.6%
, 4
36.4%
Space Separator
ValueCountFrequency (%)
489
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2023
78.6%
Common 550
 
21.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
215
 
10.6%
209
 
10.3%
119
 
5.9%
101
 
5.0%
101
 
5.0%
98
 
4.8%
85
 
4.2%
73
 
3.6%
61
 
3.0%
60
 
3.0%
Other values (97) 901
44.5%
Common
ValueCountFrequency (%)
489
88.9%
2 10
 
1.8%
) 8
 
1.5%
( 8
 
1.5%
. 7
 
1.3%
7 7
 
1.3%
, 4
 
0.7%
0 3
 
0.5%
1 3
 
0.5%
- 3
 
0.5%
Other values (6) 8
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2023
78.6%
ASCII 550
 
21.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
489
88.9%
2 10
 
1.8%
) 8
 
1.5%
( 8
 
1.5%
. 7
 
1.3%
7 7
 
1.3%
, 4
 
0.7%
0 3
 
0.5%
1 3
 
0.5%
- 3
 
0.5%
Other values (6) 8
 
1.5%
Hangul
ValueCountFrequency (%)
215
 
10.6%
209
 
10.3%
119
 
5.9%
101
 
5.0%
101
 
5.0%
98
 
4.8%
85
 
4.2%
73
 
3.6%
61
 
3.0%
60
 
3.0%
Other values (97) 901
44.5%

예정가격
Real number (ℝ)

SKEWED  ZEROS 

Distinct3079
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41796217
Minimum0
Maximum1.5914089 × 1010
Zeros4990
Zeros (%)49.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:15:11.956974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median351000
Q315000000
95-th percentile1.044073 × 108
Maximum1.5914089 × 1010
Range1.5914089 × 1010
Interquartile range (IQR)15000000

Descriptive statistics

Standard deviation3.7044309 × 108
Coefficient of variation (CV)8.863077
Kurtosis1003.0317
Mean41796217
Median Absolute Deviation (MAD)351000
Skewness28.052215
Sum4.1796217 × 1011
Variance1.3722808 × 1017
MonotonicityNot monotonic
2024-03-14T19:15:12.418088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4990
49.9%
20000000.0 105
 
1.1%
22000000.0 82
 
0.8%
10000000.0 67
 
0.7%
15000000.0 58
 
0.6%
5000000.0 38
 
0.4%
4000000.0 36
 
0.4%
21000000.0 36
 
0.4%
19800000.0 35
 
0.4%
18000000.0 32
 
0.3%
Other values (3069) 4521
45.2%
ValueCountFrequency (%)
0.0 4990
49.9%
58054.23 1
 
< 0.1%
150000.0 1
 
< 0.1%
165000.0 2
 
< 0.1%
203000.0 1
 
< 0.1%
250000.0 1
 
< 0.1%
258000.0 1
 
< 0.1%
330000.0 1
 
< 0.1%
340000.0 1
 
< 0.1%
350000.0 1
 
< 0.1%
ValueCountFrequency (%)
15914089400.0 1
< 0.1%
15820000000.0 1
< 0.1%
12683294450.0 1
< 0.1%
11744641700.0 1
< 0.1%
10896297775.0 1
< 0.1%
6286076550.0 1
< 0.1%
5154916950.0 1
< 0.1%
4626052475.0 1
< 0.1%
4597438100.0 1
< 0.1%
3900000000.0 1
< 0.1%

낙찰율
Real number (ℝ)

ZEROS 

Distinct1105
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.455341
Minimum0
Maximum109
Zeros4935
Zeros (%)49.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:15:12.801309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median87
Q393.032
95-th percentile100
Maximum109
Range109
Interquartile range (IQR)93.032

Descriptive statistics

Standard deviation46.973251
Coefficient of variation (CV)0.98984118
Kurtosis-1.9820099
Mean47.455341
Median Absolute Deviation (MAD)13
Skewness-0.01105889
Sum474553.41
Variance2206.4863
MonotonicityNot monotonic
2024-03-14T19:15:13.109763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4935
49.4%
100.0 864
 
8.6%
88.0 473
 
4.7%
92.0 456
 
4.6%
90.0 329
 
3.3%
95.0 266
 
2.7%
97.0 167
 
1.7%
93.0 154
 
1.5%
98.0 139
 
1.4%
96.0 87
 
0.9%
Other values (1095) 2130
21.3%
ValueCountFrequency (%)
0.0 4935
49.4%
9.0 1
 
< 0.1%
9.005 1
 
< 0.1%
45.697 1
 
< 0.1%
60.0 1
 
< 0.1%
66.667 3
 
< 0.1%
68.057 1
 
< 0.1%
68.571 1
 
< 0.1%
75.0 2
 
< 0.1%
78.126 1
 
< 0.1%
ValueCountFrequency (%)
109.0 1
 
< 0.1%
100.0 864
8.6%
99.88 1
 
< 0.1%
99.851 1
 
< 0.1%
99.788 1
 
< 0.1%
99.583 1
 
< 0.1%
99.445 1
 
< 0.1%
99.415 1
 
< 0.1%
99.382 1
 
< 0.1%
99.237 1
 
< 0.1%

선급금액
Real number (ℝ)

MISSING 

Distinct370
Distinct (%)76.4%
Missing9516
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean1.2906076 × 108
Minimum315000
Maximum2.517 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:15:13.533131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum315000
5-th percentile9048750
Q127855000
median53587685
Q31.2 × 108
95-th percentile5.1105 × 108
Maximum2.517 × 109
Range2.516685 × 109
Interquartile range (IQR)92145000

Descriptive statistics

Standard deviation2.5060917 × 108
Coefficient of variation (CV)1.9417921
Kurtosis41.913126
Mean1.2906076 × 108
Median Absolute Deviation (MAD)34602315
Skewness5.6709044
Sum6.2465408 × 1010
Variance6.2804957 × 1016
MonotonicityNot monotonic
2024-03-14T19:15:13.981466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40000000 12
 
0.1%
30000000 10
 
0.1%
44000000 7
 
0.1%
50000000 7
 
0.1%
100000000 4
 
< 0.1%
24000000 4
 
< 0.1%
28000000 4
 
< 0.1%
45000000 4
 
< 0.1%
7385000 4
 
< 0.1%
25000000 3
 
< 0.1%
Other values (360) 425
 
4.2%
(Missing) 9516
95.2%
ValueCountFrequency (%)
315000 1
< 0.1%
600000 1
< 0.1%
1737450 1
< 0.1%
2400000 1
< 0.1%
3444000 1
< 0.1%
3660000 1
< 0.1%
4960200 1
< 0.1%
5055840 1
< 0.1%
5400000 1
< 0.1%
5440000 1
< 0.1%
ValueCountFrequency (%)
2517000000 1
< 0.1%
2390000000 1
< 0.1%
2133250000 1
< 0.1%
1551000000 1
< 0.1%
1300000000 1
< 0.1%
1081576520 1
< 0.1%
1006500000 1
< 0.1%
900000000 1
< 0.1%
855000000 1
< 0.1%
840000000 1
< 0.1%

선급금액2
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)100.0%
Missing9986
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean1.1087474 × 108
Minimum462000
Maximum5.5 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:15:14.344226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum462000
5-th percentile473700
Q110928700
median66883845
Q31.189757 × 108
95-th percentile3.7018564 × 108
Maximum5.5 × 108
Range5.49538 × 108
Interquartile range (IQR)1.08047 × 108

Descriptive statistics

Standard deviation1.4966218 × 108
Coefficient of variation (CV)1.3498311
Kurtosis5.5698321
Mean1.1087474 × 108
Median Absolute Deviation (MAD)58629200
Skewness2.2359328
Sum1.5522464 × 109
Variance2.2398769 × 1016
MonotonicityNot monotonic
2024-03-14T19:15:14.700338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
79080000 1
 
< 0.1%
126000000 1
 
< 0.1%
202000000 1
 
< 0.1%
89000000 1
 
< 0.1%
54687690 1
 
< 0.1%
17490000 1
 
< 0.1%
462000 1
 
< 0.1%
273362530 1
 
< 0.1%
550000000 1
 
< 0.1%
6000000 1
 
< 0.1%
Other values (4) 4
 
< 0.1%
(Missing) 9986
99.9%
ValueCountFrequency (%)
462000 1
< 0.1%
480000 1
< 0.1%
6000000 1
< 0.1%
8741600 1
< 0.1%
17490000 1
< 0.1%
47039800 1
< 0.1%
54687690 1
< 0.1%
79080000 1
< 0.1%
89000000 1
< 0.1%
97902810 1
< 0.1%
ValueCountFrequency (%)
550000000 1
< 0.1%
273362530 1
< 0.1%
202000000 1
< 0.1%
126000000 1
< 0.1%
97902810 1
< 0.1%
89000000 1
< 0.1%
79080000 1
< 0.1%
54687690 1
< 0.1%
47039800 1
< 0.1%
17490000 1
< 0.1%

선급금액3
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9999 
1960000
 
1

Length

Max length7
Median length4
Mean length4.0003
Min length4

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> 9999
> 99.9%
1960000 1
 
< 0.1%

Length

2024-03-14T19:15:15.108795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:15:15.424291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9999
> 99.9%
1960000 1
 
< 0.1%

기성금액
Real number (ℝ)

MISSING 

Distinct266
Distinct (%)94.3%
Missing9718
Missing (%)97.2%
Infinite0
Infinite (%)0.0%
Mean41314038
Minimum88000
Maximum1.181 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:15:15.763456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum88000
5-th percentile716750
Q12366250
median5708500
Q323802548
95-th percentile1.998564 × 108
Maximum1.181 × 109
Range1.180912 × 109
Interquartile range (IQR)21436298

Descriptive statistics

Standard deviation1.0667923 × 108
Coefficient of variation (CV)2.5821544
Kurtosis52.257412
Mean41314038
Median Absolute Deviation (MAD)4384750
Skewness6.1557401
Sum1.1650559 × 1010
Variance1.1380457 × 1016
MonotonicityNot monotonic
2024-03-14T19:15:16.217501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4950000 3
 
< 0.1%
1150000 3
 
< 0.1%
3000000 3
 
< 0.1%
6700000 2
 
< 0.1%
1644000 2
 
< 0.1%
4515000 2
 
< 0.1%
100000000 2
 
< 0.1%
1000000 2
 
< 0.1%
1780000 2
 
< 0.1%
1323750 2
 
< 0.1%
Other values (256) 259
 
2.6%
(Missing) 9718
97.2%
ValueCountFrequency (%)
88000 1
< 0.1%
100000 1
< 0.1%
147400 1
< 0.1%
198000 1
< 0.1%
255000 1
< 0.1%
264000 1
< 0.1%
307500 1
< 0.1%
470000 1
< 0.1%
475000 1
< 0.1%
500000 1
< 0.1%
ValueCountFrequency (%)
1181000000 1
< 0.1%
592020000 1
< 0.1%
584800000 1
< 0.1%
534820000 1
< 0.1%
424396000 1
< 0.1%
317103000 1
< 0.1%
295025000 1
< 0.1%
265848000 1
< 0.1%
239420000 1
< 0.1%
229858400 1
< 0.1%

기성금액2
Real number (ℝ)

MISSING 

Distinct108
Distinct (%)93.1%
Missing9884
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean36389873
Minimum73700
Maximum1.4004814 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:15:16.629038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum73700
5-th percentile184750
Q11317130
median3324705
Q38157150
95-th percentile1.9625 × 108
Maximum1.4004814 × 109
Range1.4004077 × 109
Interquartile range (IQR)6840020

Descriptive statistics

Standard deviation1.4229333 × 108
Coefficient of variation (CV)3.9102452
Kurtosis74.935294
Mean36389873
Median Absolute Deviation (MAD)2174705
Skewness8.0746856
Sum4.2212253 × 109
Variance2.0247391 × 1016
MonotonicityNot monotonic
2024-03-14T19:15:17.081149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1150000 3
 
< 0.1%
4950000 3
 
< 0.1%
100000 2
 
< 0.1%
1780000 2
 
< 0.1%
1323750 2
 
< 0.1%
4515000 2
 
< 0.1%
88000 1
 
< 0.1%
55557000 1
 
< 0.1%
6383000 1
 
< 0.1%
63000000 1
 
< 0.1%
Other values (98) 98
 
1.0%
(Missing) 9884
98.8%
ValueCountFrequency (%)
73700 1
< 0.1%
88000 1
< 0.1%
100000 2
< 0.1%
133000 1
< 0.1%
145000 1
< 0.1%
198000 1
< 0.1%
255000 1
< 0.1%
307500 1
< 0.1%
500000 1
< 0.1%
580000 1
< 0.1%
ValueCountFrequency (%)
1400481400 1
< 0.1%
417185300 1
< 0.1%
273000000 1
< 0.1%
232711000 1
< 0.1%
214400500 1
< 0.1%
200000000 1
< 0.1%
195000000 1
< 0.1%
179041640 1
< 0.1%
136537500 1
< 0.1%
99400000 1
< 0.1%

기성금액3
Real number (ℝ)

MISSING 

Distinct66
Distinct (%)95.7%
Missing9931
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean24422772
Minimum73700
Maximum2.7237336 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:15:17.530533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum73700
5-th percentile113200
Q11354250
median3935000
Q38615780
95-th percentile1.657374 × 108
Maximum2.7237336 × 108
Range2.7229966 × 108
Interquartile range (IQR)7261530

Descriptive statistics

Standard deviation56053687
Coefficient of variation (CV)2.2951403
Kurtosis9.0692709
Mean24422772
Median Absolute Deviation (MAD)2785000
Skewness3.0605364
Sum1.6851712 × 109
Variance3.1420158 × 1015
MonotonicityNot monotonic
2024-03-14T19:15:17.990137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4950000 2
 
< 0.1%
100000 2
 
< 0.1%
1150000 2
 
< 0.1%
145000 1
 
< 0.1%
16930000 1
 
< 0.1%
470000 1
 
< 0.1%
55557000 1
 
< 0.1%
6383000 1
 
< 0.1%
4405000 1
 
< 0.1%
3960000 1
 
< 0.1%
Other values (56) 56
 
0.6%
(Missing) 9931
99.3%
ValueCountFrequency (%)
73700 1
< 0.1%
88000 1
< 0.1%
100000 2
< 0.1%
133000 1
< 0.1%
145000 1
< 0.1%
470000 1
< 0.1%
580000 1
< 0.1%
800000 1
< 0.1%
822250 1
< 0.1%
832370 1
< 0.1%
ValueCountFrequency (%)
272373360 1
< 0.1%
231410000 1
< 0.1%
201625400 1
< 0.1%
185204000 1
< 0.1%
136537500 1
< 0.1%
99400000 1
< 0.1%
96517410 1
< 0.1%
63114330 1
< 0.1%
55557000 1
< 0.1%
48197430 1
< 0.1%

기성금액4
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)97.2%
Missing9964
Missing (%)99.6%
Infinite0
Infinite (%)0.0%
Mean14741982
Minimum73700
Maximum99400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:15:18.409548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum73700
5-th percentile97000
Q1937782.5
median2832555
Q312068020
95-th percentile71465100
Maximum99400000
Range99326300
Interquartile range (IQR)11130238

Descriptive statistics

Standard deviation26047182
Coefficient of variation (CV)1.7668711
Kurtosis4.5732483
Mean14741982
Median Absolute Deviation (MAD)2693555
Skewness2.2722346
Sum5.3071137 × 108
Variance6.7845571 × 1014
MonotonicityNot monotonic
2024-03-14T19:15:18.835042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
100000 2
 
< 0.1%
6383000 1
 
< 0.1%
470000 1
 
< 0.1%
16930000 1
 
< 0.1%
34410100 1
 
< 0.1%
1100000 1
 
< 0.1%
133000 1
 
< 0.1%
1611660 1
 
< 0.1%
28393100 1
 
< 0.1%
4794400 1
 
< 0.1%
Other values (25) 25
 
0.2%
(Missing) 9964
99.6%
ValueCountFrequency (%)
73700 1
< 0.1%
88000 1
< 0.1%
100000 2
< 0.1%
133000 1
< 0.1%
145000 1
< 0.1%
470000 1
< 0.1%
580000 1
< 0.1%
800000 1
< 0.1%
983710 1
< 0.1%
1100000 1
< 0.1%
ValueCountFrequency (%)
99400000 1
< 0.1%
96517410 1
< 0.1%
63114330 1
< 0.1%
55557000 1
< 0.1%
48197430 1
< 0.1%
34410100 1
< 0.1%
28393100 1
< 0.1%
17462500 1
< 0.1%
16930000 1
< 0.1%
10447360 1
< 0.1%

기성금액5
Real number (ℝ)

MISSING 

Distinct33
Distinct (%)100.0%
Missing9967
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean15050382
Minimum73700
Maximum99400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:15:19.253375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum73700
5-th percentile111016
Q1800000
median2792770
Q310224420
95-th percentile76475562
Maximum99400000
Range99326300
Interquartile range (IQR)9424420

Descriptive statistics

Standard deviation27009077
Coefficient of variation (CV)1.7945775
Kurtosis4.1224137
Mean15050382
Median Absolute Deviation (MAD)2452770
Skewness2.205556
Sum4.966626 × 108
Variance7.2949023 × 1014
MonotonicityNot monotonic
2024-03-14T19:15:19.675988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1611660 1
 
< 0.1%
55557000 1
 
< 0.1%
470000 1
 
< 0.1%
17980000 1
 
< 0.1%
34410100 1
 
< 0.1%
1100000 1
 
< 0.1%
133000 1
 
< 0.1%
19791200 1
 
< 0.1%
2872340 1
 
< 0.1%
4339400 1
 
< 0.1%
Other values (23) 23
 
0.2%
(Missing) 9967
99.7%
ValueCountFrequency (%)
73700 1
< 0.1%
100000 1
< 0.1%
118360 1
< 0.1%
133000 1
< 0.1%
145000 1
< 0.1%
340000 1
< 0.1%
470000 1
< 0.1%
580000 1
< 0.1%
800000 1
< 0.1%
1100000 1
< 0.1%
ValueCountFrequency (%)
99400000 1
< 0.1%
96517410 1
< 0.1%
63114330 1
< 0.1%
55557000 1
< 0.1%
48197430 1
< 0.1%
34410100 1
< 0.1%
19791200 1
< 0.1%
17980000 1
< 0.1%
10224420 1
< 0.1%
8942840 1
< 0.1%

기성금액6
Real number (ℝ)

MISSING 

Distinct30
Distinct (%)100.0%
Missing9970
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean15844273
Minimum44000
Maximum99400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:15:20.071346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum44000
5-th percentile85535
Q11112500
median2832555
Q39643545
95-th percentile81486024
Maximum99400000
Range99356000
Interquartile range (IQR)8531045

Descriptive statistics

Standard deviation28094857
Coefficient of variation (CV)1.7731869
Kurtosis3.5153611
Mean15844273
Median Absolute Deviation (MAD)2645055
Skewness2.09517
Sum4.7532819 × 108
Variance7.8932099 × 1014
MonotonicityNot monotonic
2024-03-14T19:15:20.491256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
145000 1
 
< 0.1%
8474400 1
 
< 0.1%
44000 1
 
< 0.1%
3989690 1
 
< 0.1%
1150000 1
 
< 0.1%
5267600 1
 
< 0.1%
1611660 1
 
< 0.1%
133000 1
 
< 0.1%
1100000 1
 
< 0.1%
34410100 1
 
< 0.1%
Other values (20) 20
 
0.2%
(Missing) 9970
99.7%
ValueCountFrequency (%)
44000 1
< 0.1%
73700 1
< 0.1%
100000 1
< 0.1%
133000 1
< 0.1%
145000 1
< 0.1%
230000 1
< 0.1%
800000 1
< 0.1%
1100000 1
< 0.1%
1150000 1
< 0.1%
1160000 1
< 0.1%
ValueCountFrequency (%)
99400000 1
< 0.1%
96517410 1
< 0.1%
63114330 1
< 0.1%
55557000 1
< 0.1%
48197430 1
< 0.1%
34410100 1
< 0.1%
17980000 1
< 0.1%
10033260 1
< 0.1%
8474400 1
< 0.1%
6383000 1
< 0.1%

기성금액7
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)100.0%
Missing9976
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean19605590
Minimum88000
Maximum99400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:15:20.885150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum88000
5-th percentile158050
Q11572570
median4072845
Q322087525
95-th percentile91506948
Maximum99400000
Range99312000
Interquartile range (IQR)20514955

Descriptive statistics

Standard deviation30396481
Coefficient of variation (CV)1.5503987
Kurtosis2.0527263
Mean19605590
Median Absolute Deviation (MAD)3372845
Skewness1.7491214
Sum4.7053415 × 108
Variance9.2394606 × 1014
MonotonicityNot monotonic
2024-03-14T19:15:21.477680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
55557000 1
 
< 0.1%
9357850 1
 
< 0.1%
88000 1
 
< 0.1%
3989690 1
 
< 0.1%
1150000 1
 
< 0.1%
4362800 1
 
< 0.1%
1611660 1
 
< 0.1%
133000 1
 
< 0.1%
1100000 1
 
< 0.1%
34410100 1
 
< 0.1%
Other values (14) 14
 
0.1%
(Missing) 9976
99.8%
ValueCountFrequency (%)
88000 1
< 0.1%
133000 1
< 0.1%
300000 1
< 0.1%
1100000 1
< 0.1%
1150000 1
< 0.1%
1455300 1
< 0.1%
1611660 1
< 0.1%
1644000 1
< 0.1%
2367200 1
< 0.1%
2792770 1
< 0.1%
ValueCountFrequency (%)
99400000 1
< 0.1%
96517410 1
< 0.1%
63114330 1
< 0.1%
55557000 1
< 0.1%
48197430 1
< 0.1%
34410100 1
< 0.1%
17980000 1
< 0.1%
13808270 1
< 0.1%
9357850 1
< 0.1%
4362800 1
< 0.1%

기성금액8
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)100.0%
Missing9993
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean8911571.4
Minimum133000
Maximum48197430
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:15:21.833599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum133000
5-th percentile576598
Q11627830
median2792770
Q34001070
95-th percentile35277141
Maximum48197430
Range48064430
Interquartile range (IQR)2373240

Descriptive statistics

Standard deviation17391387
Coefficient of variation (CV)1.9515511
Kurtosis6.82507
Mean8911571.4
Median Absolute Deviation (MAD)1181110
Skewness2.6029471
Sum62381000
Variance3.0246036 × 1014
MonotonicityNot monotonic
2024-03-14T19:15:22.201318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2872340 1
 
< 0.1%
2792770 1
 
< 0.1%
1644000 1
 
< 0.1%
48197430 1
 
< 0.1%
133000 1
 
< 0.1%
1611660 1
 
< 0.1%
5129800 1
 
< 0.1%
(Missing) 9993
99.9%
ValueCountFrequency (%)
133000 1
< 0.1%
1611660 1
< 0.1%
1644000 1
< 0.1%
2792770 1
< 0.1%
2872340 1
< 0.1%
5129800 1
< 0.1%
48197430 1
< 0.1%
ValueCountFrequency (%)
48197430 1
< 0.1%
5129800 1
< 0.1%
2872340 1
< 0.1%
2792770 1
< 0.1%
1644000 1
< 0.1%
1611660 1
< 0.1%
133000 1
< 0.1%

준공금액
Real number (ℝ)

MISSING 

Distinct4565
Distinct (%)56.2%
Missing1883
Missing (%)18.8%
Infinite0
Infinite (%)0.0%
Mean18793966
Minimum40480
Maximum1.15448 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:15:22.592833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40480
5-th percentile1154000
Q13920000
median9220000
Q318220000
95-th percentile69626000
Maximum1.15448 × 109
Range1.1544395 × 109
Interquartile range (IQR)14300000

Descriptive statistics

Standard deviation41452469
Coefficient of variation (CV)2.2056265
Kurtosis185.83411
Mean18793966
Median Absolute Deviation (MAD)6310000
Skewness10.389308
Sum1.5255062 × 1011
Variance1.7183072 × 1015
MonotonicityNot monotonic
2024-03-14T19:15:23.048343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18000000 77
 
0.8%
19800000 58
 
0.6%
3920000 51
 
0.5%
9200000 50
 
0.5%
4850000 43
 
0.4%
9700000 42
 
0.4%
4900000 38
 
0.4%
14250000 37
 
0.4%
2000000 33
 
0.3%
2200000 31
 
0.3%
Other values (4555) 7657
76.6%
(Missing) 1883
 
18.8%
ValueCountFrequency (%)
40480 1
 
< 0.1%
70000 1
 
< 0.1%
114000 1
 
< 0.1%
190000 5
0.1%
194000 1
 
< 0.1%
196000 1
 
< 0.1%
200000 2
 
< 0.1%
203000 1
 
< 0.1%
209000 1
 
< 0.1%
239000 1
 
< 0.1%
ValueCountFrequency (%)
1154480000 1
< 0.1%
1093470500 1
< 0.1%
859290700 1
< 0.1%
636033200 1
< 0.1%
586819480 1
< 0.1%
542259500 1
< 0.1%
534306490 1
< 0.1%
511137000 1
< 0.1%
510454000 1
< 0.1%
474056000 1
< 0.1%

업체명
Text

MISSING 

Distinct16
Distinct (%)84.2%
Missing9981
Missing (%)99.8%
Memory size156.2 KiB
2024-03-14T19:15:23.817624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length9
Mean length8.3684211
Min length5

Characters and Unicode

Total characters159
Distinct characters53
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)73.7%

Sample

1st row(주)삼현비앤이
2nd row일소건설(주)
3rd row주식회사 구마에스앤씨(S&C)
4th row(주)경우종합건설
5th row버드건설(주)
ValueCountFrequency (%)
3
 
12.0%
주식회사 3
 
12.0%
삼원씨엔이 3
 
12.0%
구마에스앤씨(s&c 2
 
8.0%
주)성림조경 1
 
4.0%
주)거양 1
 
4.0%
프레임건설 1
 
4.0%
주)도원에스이 1
 
4.0%
금정개발(주 1
 
4.0%
주)동서에코라인 1
 
4.0%
Other values (8) 8
32.0%
2024-03-14T19:15:24.672980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18
 
11.3%
( 17
 
10.7%
) 17
 
10.7%
8
 
5.0%
7
 
4.4%
6
 
3.8%
5
 
3.1%
5
 
3.1%
4
 
2.5%
4
 
2.5%
Other values (43) 68
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 113
71.1%
Open Punctuation 17
 
10.7%
Close Punctuation 17
 
10.7%
Space Separator 6
 
3.8%
Uppercase Letter 4
 
2.5%
Other Punctuation 2
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18
 
15.9%
8
 
7.1%
7
 
6.2%
5
 
4.4%
5
 
4.4%
4
 
3.5%
4
 
3.5%
4
 
3.5%
3
 
2.7%
3
 
2.7%
Other values (37) 52
46.0%
Uppercase Letter
ValueCountFrequency (%)
C 2
50.0%
S 2
50.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 113
71.1%
Common 42
 
26.4%
Latin 4
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18
 
15.9%
8
 
7.1%
7
 
6.2%
5
 
4.4%
5
 
4.4%
4
 
3.5%
4
 
3.5%
4
 
3.5%
3
 
2.7%
3
 
2.7%
Other values (37) 52
46.0%
Common
ValueCountFrequency (%)
( 17
40.5%
) 17
40.5%
6
 
14.3%
& 2
 
4.8%
Latin
ValueCountFrequency (%)
C 2
50.0%
S 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 113
71.1%
ASCII 46
28.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
18
 
15.9%
8
 
7.1%
7
 
6.2%
5
 
4.4%
5
 
4.4%
4
 
3.5%
4
 
3.5%
4
 
3.5%
3
 
2.7%
3
 
2.7%
Other values (37) 52
46.0%
ASCII
ValueCountFrequency (%)
( 17
37.0%
) 17
37.0%
6
 
13.0%
C 2
 
4.3%
& 2
 
4.3%
S 2
 
4.3%

계약대표자
Text

MISSING 

Distinct16
Distinct (%)84.2%
Missing9981
Missing (%)99.8%
Memory size156.2 KiB
2024-03-14T19:15:25.292120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.2105263
Min length3

Characters and Unicode

Total characters61
Distinct characters36
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)73.7%

Sample

1st row구자겸,최동남
2nd row김익홍
3rd row이태민
4th row서부원
5th row김정욱
ValueCountFrequency (%)
이병청 3
15.8%
이태민 2
 
10.5%
이경희 1
 
5.3%
김익홍 1
 
5.3%
서부원 1
 
5.3%
김정욱 1
 
5.3%
정제원 1
 
5.3%
구자겸,최동남 1
 
5.3%
도경준 1
 
5.3%
최병기 1
 
5.3%
Other values (6) 6
31.6%
2024-03-14T19:15:26.071367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8
 
13.1%
4
 
6.6%
3
 
4.9%
3
 
4.9%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
Other values (26) 31
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60
98.4%
Other Punctuation 1
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8
 
13.3%
4
 
6.7%
3
 
5.0%
3
 
5.0%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
Other values (25) 30
50.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60
98.4%
Common 1
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8
 
13.3%
4
 
6.7%
3
 
5.0%
3
 
5.0%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
Other values (25) 30
50.0%
Common
ValueCountFrequency (%)
, 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60
98.4%
ASCII 1
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
8
 
13.3%
4
 
6.7%
3
 
5.0%
3
 
5.0%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
2
 
3.3%
Other values (25) 30
50.0%
ASCII
ValueCountFrequency (%)
, 1
100.0%

공종
Text

MISSING 

Distinct13
Distinct (%)68.4%
Missing9981
Missing (%)99.8%
Memory size156.2 KiB
2024-03-14T19:15:26.652412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length9
Mean length7.4210526
Min length2

Characters and Unicode

Total characters141
Distinct characters55
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)52.6%

Sample

1st row철근콘크리트공사 PRECOM거더(라멘형) 제작 및 가설
2nd row철근콘크리트공사업
3rd row토공사
4th row토목공사업
5th row토공사
ValueCountFrequency (%)
토공사 4
16.7%
철근콘크리트공사 3
12.5%
철근콘크리트 3
12.5%
제작설치(특허 1
 
4.2%
조적,미장,방수,도장 1
 
4.2%
석면해체 1
 
4.2%
방수 1
 
4.2%
조경식재 1
 
4.2%
조경시설물공사 1
 
4.2%
토목공사업 1
 
4.2%
Other values (7) 7
29.2%
2024-03-14T19:15:27.511141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11
 
7.8%
11
 
7.8%
7
 
5.0%
7
 
5.0%
7
 
5.0%
7
 
5.0%
7
 
5.0%
7
 
5.0%
5
 
3.5%
5
 
3.5%
Other values (45) 67
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 120
85.1%
Uppercase Letter 9
 
6.4%
Space Separator 5
 
3.5%
Other Punctuation 3
 
2.1%
Close Punctuation 2
 
1.4%
Open Punctuation 2
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11
 
9.2%
11
 
9.2%
7
 
5.8%
7
 
5.8%
7
 
5.8%
7
 
5.8%
7
 
5.8%
7
 
5.8%
5
 
4.2%
4
 
3.3%
Other values (34) 47
39.2%
Uppercase Letter
ValueCountFrequency (%)
S 2
22.2%
P 2
22.2%
R 1
11.1%
M 1
11.1%
E 1
11.1%
C 1
11.1%
O 1
11.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 120
85.1%
Common 12
 
8.5%
Latin 9
 
6.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11
 
9.2%
11
 
9.2%
7
 
5.8%
7
 
5.8%
7
 
5.8%
7
 
5.8%
7
 
5.8%
7
 
5.8%
5
 
4.2%
4
 
3.3%
Other values (34) 47
39.2%
Latin
ValueCountFrequency (%)
S 2
22.2%
P 2
22.2%
R 1
11.1%
M 1
11.1%
E 1
11.1%
C 1
11.1%
O 1
11.1%
Common
ValueCountFrequency (%)
5
41.7%
, 3
25.0%
) 2
 
16.7%
( 2
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 120
85.1%
ASCII 21
 
14.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
11
 
9.2%
11
 
9.2%
7
 
5.8%
7
 
5.8%
7
 
5.8%
7
 
5.8%
7
 
5.8%
7
 
5.8%
5
 
4.2%
4
 
3.3%
Other values (34) 47
39.2%
ASCII
ValueCountFrequency (%)
5
23.8%
, 3
14.3%
) 2
 
9.5%
S 2
 
9.5%
P 2
 
9.5%
( 2
 
9.5%
R 1
 
4.8%
M 1
 
4.8%
E 1
 
4.8%
C 1
 
4.8%

하도급율
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)94.7%
Missing9981
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean89.062105
Minimum82
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:15:27.874178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum82
5-th percentile82.108
Q183.36
median86.82
Q394.94
95-th percentile99.451
Maximum100
Range18
Interquartile range (IQR)11.58

Descriptive statistics

Standard deviation6.5315309
Coefficient of variation (CV)0.073336812
Kurtosis-1.3418341
Mean89.062105
Median Absolute Deviation (MAD)4.59
Skewness0.52453031
Sum1692.18
Variance42.660895
MonotonicityNot monotonic
2024-03-14T19:15:28.253855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
85.0 2
 
< 0.1%
83.33 1
 
< 0.1%
92.0 1
 
< 0.1%
96.0 1
 
< 0.1%
98.5 1
 
< 0.1%
87.98 1
 
< 0.1%
93.88 1
 
< 0.1%
82.23 1
 
< 0.1%
82.12 1
 
< 0.1%
97.01 1
 
< 0.1%
Other values (8) 8
 
0.1%
(Missing) 9981
99.8%
ValueCountFrequency (%)
82.0 1
< 0.1%
82.12 1
< 0.1%
82.23 1
< 0.1%
82.52 1
< 0.1%
83.33 1
< 0.1%
83.39 1
< 0.1%
84.98 1
< 0.1%
85.0 2
< 0.1%
86.82 1
< 0.1%
87.98 1
< 0.1%
ValueCountFrequency (%)
100.0 1
< 0.1%
99.39 1
< 0.1%
98.5 1
< 0.1%
97.01 1
< 0.1%
96.0 1
< 0.1%
93.88 1
< 0.1%
92.0 1
< 0.1%
90.03 1
< 0.1%
87.98 1
< 0.1%
86.82 1
< 0.1%

업체명2
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing9992
Missing (%)99.9%
Memory size156.2 KiB
2024-03-14T19:15:28.925164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.25
Min length4

Characters and Unicode

Total characters58
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)100.0%

Sample

1st row삼원산업개발(주)
2nd row(주)태우건설
3rd row부건건설(주)
4th row(주)거양
5th row일류건설 주식회사
ValueCountFrequency (%)
삼원산업개발(주 1
11.1%
주)태우건설 1
11.1%
부건건설(주 1
11.1%
주)거양 1
11.1%
일류건설 1
11.1%
주식회사 1
11.1%
주)도원에스이 1
11.1%
부산유리 1
11.1%
주)신한에스엔지 1
11.1%
2024-03-14T19:15:29.974156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
 
12.1%
( 6
 
10.3%
) 6
 
10.3%
4
 
6.9%
3
 
5.2%
2
 
3.4%
2
 
3.4%
2
 
3.4%
2
 
3.4%
2
 
3.4%
Other values (22) 22
37.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45
77.6%
Open Punctuation 6
 
10.3%
Close Punctuation 6
 
10.3%
Space Separator 1
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7
 
15.6%
4
 
8.9%
3
 
6.7%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
1
 
2.2%
1
 
2.2%
Other values (19) 19
42.2%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45
77.6%
Common 13
 
22.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7
 
15.6%
4
 
8.9%
3
 
6.7%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
1
 
2.2%
1
 
2.2%
Other values (19) 19
42.2%
Common
ValueCountFrequency (%)
( 6
46.2%
) 6
46.2%
1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45
77.6%
ASCII 13
 
22.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
7
 
15.6%
4
 
8.9%
3
 
6.7%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
1
 
2.2%
1
 
2.2%
Other values (19) 19
42.2%
ASCII
ValueCountFrequency (%)
( 6
46.2%
) 6
46.2%
1
 
7.7%

계약대표자2
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing9992
Missing (%)99.9%
Memory size156.2 KiB
2024-03-14T19:15:30.635439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters24
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)100.0%

Sample

1st row이재환
2nd row정제원
3rd row이경희
4th row장연서
5th row지수민
ValueCountFrequency (%)
이재환 1
12.5%
정제원 1
12.5%
이경희 1
12.5%
장연서 1
12.5%
지수민 1
12.5%
이상은 1
12.5%
권오경 1
12.5%
최용성 1
12.5%
2024-03-14T19:15:31.650485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3
 
12.5%
2
 
8.3%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
Other values (11) 11
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
 
12.5%
2
 
8.3%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
Other values (11) 11
45.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
 
12.5%
2
 
8.3%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
Other values (11) 11
45.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3
 
12.5%
2
 
8.3%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
1
 
4.2%
Other values (11) 11
45.8%

공종2
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing9992
Missing (%)99.9%
Memory size156.2 KiB
2024-03-14T19:15:32.326287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length7
Mean length5.875
Min length2

Characters and Unicode

Total characters47
Distinct characters29
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)100.0%

Sample

1st row습식방수공사
2nd row토공사
3rd row철근콘크리트공사업
4th row조경시설물
5th row철거
ValueCountFrequency (%)
습식방수공사 1
12.5%
토공사 1
12.5%
철근콘크리트공사업 1
12.5%
조경시설물 1
12.5%
철거 1
12.5%
석공사 1
12.5%
건축,토목,기계,조경 1
12.5%
철강구조물공사업 1
12.5%
2024-03-14T19:15:33.348164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
 
10.6%
5
 
10.6%
3
 
6.4%
3
 
6.4%
, 3
 
6.4%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
1
 
2.1%
Other values (19) 19
40.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44
93.6%
Other Punctuation 3
 
6.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
 
11.4%
5
 
11.4%
3
 
6.8%
3
 
6.8%
2
 
4.5%
2
 
4.5%
2
 
4.5%
2
 
4.5%
1
 
2.3%
1
 
2.3%
Other values (18) 18
40.9%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44
93.6%
Common 3
 
6.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
 
11.4%
5
 
11.4%
3
 
6.8%
3
 
6.8%
2
 
4.5%
2
 
4.5%
2
 
4.5%
2
 
4.5%
1
 
2.3%
1
 
2.3%
Other values (18) 18
40.9%
Common
ValueCountFrequency (%)
, 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44
93.6%
ASCII 3
 
6.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5
 
11.4%
5
 
11.4%
3
 
6.8%
3
 
6.8%
2
 
4.5%
2
 
4.5%
2
 
4.5%
2
 
4.5%
1
 
2.3%
1
 
2.3%
Other values (18) 18
40.9%
ASCII
ValueCountFrequency (%)
, 3
100.0%

하도급율2
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)100.0%
Missing9992
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean87.63125
Minimum82.08
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T19:15:33.535470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum82.08
5-th percentile82.752
Q184.75
median86.095
Q388.445
95-th percentile96.423
Maximum100
Range17.92
Interquartile range (IQR)3.695

Descriptive statistics

Standard deviation5.5515698
Coefficient of variation (CV)0.063351484
Kurtosis3.9955831
Mean87.63125
Median Absolute Deviation (MAD)2
Skewness1.8334648
Sum701.05
Variance30.819927
MonotonicityNot monotonic
2024-03-14T19:15:33.725584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
84.0 1
 
< 0.1%
85.01 1
 
< 0.1%
100.0 1
 
< 0.1%
85.0 1
 
< 0.1%
82.08 1
 
< 0.1%
87.18 1
 
< 0.1%
89.78 1
 
< 0.1%
88.0 1
 
< 0.1%
(Missing) 9992
99.9%
ValueCountFrequency (%)
82.08 1
< 0.1%
84.0 1
< 0.1%
85.0 1
< 0.1%
85.01 1
< 0.1%
87.18 1
< 0.1%
88.0 1
< 0.1%
89.78 1
< 0.1%
100.0 1
< 0.1%
ValueCountFrequency (%)
100.0 1
< 0.1%
89.78 1
< 0.1%
88.0 1
< 0.1%
87.18 1
< 0.1%
85.01 1
< 0.1%
85.0 1
< 0.1%
84.0 1
< 0.1%
82.08 1
< 0.1%

업체명3
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing9997
Missing (%)> 99.9%
Memory size156.2 KiB
2024-03-14T19:15:34.196193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.3333333
Min length5

Characters and Unicode

Total characters22
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row(주)하림이에스티
2nd row(주)대길
3rd row(주)다성이엔지
ValueCountFrequency (%)
주)하림이에스티 1
33.3%
주)대길 1
33.3%
주)다성이엔지 1
33.3%
2024-03-14T19:15:34.902479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 3
13.6%
3
13.6%
) 3
13.6%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (5) 5
22.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
72.7%
Open Punctuation 3
 
13.6%
Close Punctuation 3
 
13.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
18.8%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (3) 3
18.8%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
72.7%
Common 6
 
27.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
18.8%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (3) 3
18.8%
Common
ValueCountFrequency (%)
( 3
50.0%
) 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
72.7%
ASCII 6
 
27.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 3
50.0%
) 3
50.0%
Hangul
ValueCountFrequency (%)
3
18.8%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (3) 3
18.8%

계약대표자3
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing9997
Missing (%)> 99.9%
Memory size156.2 KiB
2024-03-14T19:15:35.367803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.6666667
Min length2

Characters and Unicode

Total characters8
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row백승훈
2nd row송순구
3rd row정호
ValueCountFrequency (%)
백승훈 1
33.3%
송순구 1
33.3%
정호 1
33.3%
2024-03-14T19:15:36.299393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%

공종3
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing9997
Missing (%)> 99.9%
Memory size156.2 KiB
2024-03-14T19:15:36.736061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.3333333
Min length4

Characters and Unicode

Total characters16
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row보링그라우팅
2nd row포장공사
3rd row기계설비공사
ValueCountFrequency (%)
보링그라우팅 1
33.3%
포장공사 1
33.3%
기계설비공사 1
33.3%
2024-03-14T19:15:37.428126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
12.5%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (4) 4
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
12.5%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (4) 4
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
12.5%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (4) 4
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2
12.5%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (4) 4
25.0%

하도급율3
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9997 
83.0
 
1
138.6
 
1
87.0
 
1

Length

Max length5
Median length4
Mean length4.0001
Min length4

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9997
> 99.9%
83.0 1
 
< 0.1%
138.6 1
 
< 0.1%
87.0 1
 
< 0.1%

Length

2024-03-14T19:15:37.642729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:15:37.833390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9997
> 99.9%
83.0 1
 
< 0.1%
138.6 1
 
< 0.1%
87.0 1
 
< 0.1%

Sample

번호계약관서계약명계약종류계약유형계약방법계약일자최초계약금액계약금액착공일자준공일자계약상대자대표자주소감독공무원계약사유변경금액증감액변경일자변경사유변경금액2증감액2변경일자2변경사유2변경금액3증감액3변경일자3변경사유3예정가격낙찰율선급금액선급금액2선급금액3기성금액기성금액2기성금액3기성금액4기성금액5기성금액6기성금액7기성금액8준공금액업체명계약대표자공종하도급율업체명2계약대표자2공종2하도급율2업체명3계약대표자3공종3하도급율3
16231624화랑마을어울마당 주변 정비 공사공사종합수의1인견적2021-10-09475000047500002021-10-192021-11-17(주)경주조경견제필경상북도 경주시 양정로 227(동천동)<NA>「건설산업기본법」외의 공사 관련 법령에 따른 공사로서 추정가격이 8천만원 이하인 공사에 대한 계약(제25조제1항제5호가목)475000002021-10-19최초생성<NA><NA><NA><NA><NA><NA><NA><NA>0.00.0<NA><NA><NA>4750000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
68946895강동면왕신2리 농로포장공사 시행공사전문수의1인견적2022-05-03760000076000002022-05-042022-05-23미래건설석재한영진경상북도 경주시 백률로58번길 15(동천동)<NA>「건설산업기본법」에 따른 건설공사로 추정가격 2억원 이하의 공사, 같은 법에 따른 전문공사로 추정가격 1억원 이하의 공사 계약(제25조제1항제5호가목)760000002022-05-03최초생성<NA><NA><NA><NA><NA><NA><NA><NA>0.00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>7600000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1470814709본청모화일반산업단지 상수도 관로 개선 공사 폐기물 운반용역용역폐기물수의2인이상견적2023-10-3111127830125000002023-11-012024-01-29영남개발(주)조민재경상북도 경주시 천북면 신당소티고개길 86-18배무한추정가격 2천만원 이하의 물품의 제조·구매계약 또는 용역계약(제25조제1항제5호나목)1112783002023-10-31최초생성1250000013721702023-12-20물량변경에 따른 변경<NA><NA><NA><NA>12500000.0100.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>12500000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28192820본청2021년 버스승강장 발열의자 전기 인입공사공사전기수의1인견적2021-12-03663000066300002021-12-032021-12-12(주)성보전력최영삼경상북도 경주시 천북면 천북로 61황태웅「건설산업기본법」에 따른 건설공사로 추정가격 2억원 이하의 공사, 같은 법에 따른 전문공사로 추정가격 1억원 이하의 공사 계약(제25조제1항제5호가목)663000002021-12-03최초생성<NA><NA><NA><NA><NA><NA><NA><NA>6900000.096.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6630000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1426714268본청건천읍 신평1리 돈지들 용배수로 정비공사공사전문수의2인이상견적2023-11-211216011901296100002023-11-272024-05-24(주)영민토건손복호경상북도 경주시 백률로8번길 7 (동천동)이다혁「건설산업기본법」에 따른 건설공사로 추정가격 4억원 이하의 공사, 같은 법에 따른 전문공사로 추정가격 2억원 이하의 공사 계약(제25조제1항제5호가목)12160119002023-11-21최초생성12961000080088102023-12-18설계변경 및 제경비 정산<NA><NA><NA><NA>137126100.088.678<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1016910170본청충효 소하천 주변 경관조명 마무리공사공사전문수의1인견적2022-12-2813890000138900002022-12-292023-01-22선광전기윤은희경상북도 경주시 원효로173번길 10(황오동)김준성추정가격 2천만원 이하 공사,물품의 제조·구매·용역. 다만,「여성기업지원에 관한 법률」에 따른 여성기업,「장애인기업활동 촉진법」에 따른 장애인기업과 계약은 추정가격 5천만원 이하로 함(제30조제1항제2호)1389000002022-12-28최초생성<NA><NA><NA><NA><NA><NA><NA><NA>15091000.092.042<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>13890000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
97859786본청보덕 모차골소하천(중류부) 재해복구사업 실시설계 용역용역기술수의1인견적2022-12-1313800000138000002022-12-162023-01-14(주)인덕엔지니어링김인덕경상북도 경주시 동천동787-13강동일추정가격 2천만원 이하의 물품의 제조·구매계약 또는 용역계약(제25조제1항제5호나목)1380000002022-12-13최초생성<NA><NA><NA><NA><NA><NA><NA><NA>15000000.092.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>13800000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12491250월성동망덕길 확장공사 실시설계용역 시행용역일반수의1인견적2021-10-06196000019600002021-10-062021-10-25(주)상신엔지니어링최병욱경상북도 경주시 양정로 275, 401호(동천동)공동석추정가격 2천만원 이하 공사,물품의 제조·구매·용역. 다만,「여성기업지원에 관한 법률」에 따른 여성기업,「장애인기업활동 촉진법」에 따른 장애인기업과 계약은 추정가격 5천만원 이하로 함(제30조제1항제2호)196000002021-10-06최초생성<NA><NA><NA><NA><NA><NA><NA><NA>0.00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1960000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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번호계약관서계약명계약종류계약유형계약방법계약일자최초계약금액계약금액착공일자준공일자계약상대자대표자주소감독공무원계약사유변경금액증감액변경일자변경사유변경금액2증감액2변경일자2변경사유2변경금액3증감액3변경일자3변경사유3예정가격낙찰율선급금액선급금액2선급금액3기성금액기성금액2기성금액3기성금액4기성금액5기성금액6기성금액7기성금액8준공금액업체명계약대표자공종하도급율업체명2계약대표자2공종2하도급율2업체명3계약대표자3공종3하도급율3
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98839884본청경주시 시가지 자전거도로 개선사업 폐기물처리 용역용역폐기물수의2인이상견적2022-12-1921609530216095302022-12-222023-08-25대림산업(주)대림산업(주)경상북도 경주시 천북면 화산공단길52-52공동석추정가격 2천만원 초과 5천만원 이하의 학술연구·원가계산 등과 관련된 특수한 지식을 요하는 물품의 제조·구매 또는 용역계약(제25조제1항제5호라목)2160953002022-12-19최초생성<NA><NA><NA><NA><NA><NA><NA><NA>24427550.088.463<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>21609530<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1353913540본청건천 화천리 장지(저수지) 재해복구사업 관급자재(저수지용 수문) 구입물품구매수의1인견적2023-03-1376921007692100<NA>2023-07-11대성공업사유병희대구광역시 달서구 장동43-1<NA>추정가격 2천만원 이하의 물품의 제조·구매계약 또는 용역계약(제25조제1항제5호나목)769210002023-03-13최초생성<NA><NA><NA><NA><NA><NA><NA><NA>0.00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>