Overview

Dataset statistics

Number of variables14
Number of observations2198
Missing cells15701
Missing cells (%)51.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory255.6 KiB
Average record size in memory119.1 B

Variable types

Numeric7
Text7

Dataset

Description인검증 환경신기술 활용 실적 목록 현황(2020-10-26 기준 / 기술명, 실적제출년도, 적용건수, 사용공정, 사용제품명 등)
Author한국환경산업기술원
URLhttps://www.data.go.kr/data/15071532/fileData.do

Alerts

활용실적 순번 is highly overall correlated with 신청서ID and 1 other fieldsHigh correlation
신청서ID is highly overall correlated with 활용실적 순번 and 1 other fieldsHigh correlation
실적제출년도 is highly overall correlated with 활용실적 순번 and 1 other fieldsHigh correlation
2.신기술_총적용건수 is highly overall correlated with 총계약금액High correlation
총계약금액 is highly overall correlated with 2.신기술_총적용건수High correlation
제품 연매출액 is highly overall correlated with 홍보물 발행수량High correlation
홍보물 발행수량 is highly overall correlated with 제품 연매출액High correlation
2.신기술_총적용건수 has 39 (1.8%) missing valuesMissing
총계약금액 has 675 (30.7%) missing valuesMissing
활용실적 없는 사유 has 2029 (92.3%) missing valuesMissing
3.NET마크사용_시설 has 2150 (97.8%) missing valuesMissing
사용공정 has 2165 (98.5%) missing valuesMissing
사용제품명 has 2139 (97.3%) missing valuesMissing
제품 연매출액 has 1108 (50.4%) missing valuesMissing
홍보물종류 has 2096 (95.4%) missing valuesMissing
홍보물 발행수량 has 1390 (63.2%) missing valuesMissing
사용효과 has 1905 (86.7%) missing valuesMissing
총계약금액 is highly skewed (γ1 = 37.08149542)Skewed
활용실적 순번 has unique valuesUnique
2.신기술_총적용건수 has 256 (11.6%) zerosZeros
총계약금액 has 273 (12.4%) zerosZeros
제품 연매출액 has 1049 (47.7%) zerosZeros
홍보물 발행수량 has 718 (32.7%) zerosZeros

Reproduction

Analysis started2023-12-12 12:59:45.247720
Analysis finished2023-12-12 12:59:53.545046
Duration8.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

활용실적 순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2198
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2072.4181
Minimum1
Maximum3994
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.4 KiB
2023-12-12T21:59:53.632776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile110.85
Q1551.25
median2229.5
Q33440.75
95-th percentile3883.15
Maximum3994
Range3993
Interquartile range (IQR)2889.5

Descriptive statistics

Standard deviation1394.0053
Coefficient of variation (CV)0.67264676
Kurtosis-1.5928241
Mean2072.4181
Median Absolute Deviation (MAD)1358
Skewness-0.1236387
Sum4555175
Variance1943250.8
MonotonicityNot monotonic
2023-12-12T21:59:53.819010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1466 1
 
< 0.1%
448 1
 
< 0.1%
442 1
 
< 0.1%
443 1
 
< 0.1%
444 1
 
< 0.1%
445 1
 
< 0.1%
446 1
 
< 0.1%
447 1
 
< 0.1%
449 1
 
< 0.1%
411 1
 
< 0.1%
Other values (2188) 2188
99.5%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
3994 1
< 0.1%
3993 1
< 0.1%
3992 1
< 0.1%
3991 1
< 0.1%
3990 1
< 0.1%
3989 1
< 0.1%
3988 1
< 0.1%
3987 1
< 0.1%
3986 1
< 0.1%
3985 1
< 0.1%

신청서ID
Real number (ℝ)

HIGH CORRELATION 

Distinct768
Distinct (%)34.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5740.6442
Minimum4
Maximum15703
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.4 KiB
2023-12-12T21:59:54.007973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile61
Q1489.25
median4161
Q311684
95-th percentile15348.15
Maximum15703
Range15699
Interquartile range (IQR)11194.75

Descriptive statistics

Standard deviation5593.0522
Coefficient of variation (CV)0.97428999
Kurtosis-1.3320289
Mean5740.6442
Median Absolute Deviation (MAD)3930
Skewness0.48211607
Sum12617936
Variance31282233
MonotonicityNot monotonic
2023-12-12T21:59:54.147352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9181 15
 
0.7%
14209 13
 
0.6%
12800 13
 
0.6%
9319 12
 
0.5%
11839 11
 
0.5%
12052 11
 
0.5%
7940 10
 
0.5%
14497 9
 
0.4%
11528 9
 
0.4%
4815 9
 
0.4%
Other values (758) 2086
94.9%
ValueCountFrequency (%)
4 4
0.2%
5 1
 
< 0.1%
7 1
 
< 0.1%
9 4
0.2%
11 1
 
< 0.1%
12 3
 
0.1%
13 5
0.2%
15 7
0.3%
18 2
 
0.1%
21 8
0.4%
ValueCountFrequency (%)
15703 1
 
< 0.1%
15631 1
 
< 0.1%
15626 1
 
< 0.1%
15625 2
0.1%
15622 2
0.1%
15621 2
0.1%
15615 1
 
< 0.1%
15611 1
 
< 0.1%
15598 4
0.2%
15596 1
 
< 0.1%
Distinct756
Distinct (%)34.5%
Missing5
Missing (%)0.2%
Memory size17.3 KiB
2023-12-12T21:59:54.414154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length149
Median length84
Mean length46.951664
Min length1

Characters and Unicode

Total characters102965
Distinct characters596
Distinct categories11 ?
Distinct scripts5 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique208 ?
Unique (%)9.5%

Sample

1st row오일순환 윤활방식으로 개량한 Direct Drive Cone Crusher를 이용한 순환잔골재의 품질향상 기술
2nd row건식 집진커터와 알루미늄드럼 팩커를 이용한 맨홀철개 인상 보수공법
3rd row연속반응식 인제거여과기(IPRTM-Process)를 이용한 하폐수 고도처리기술
4th row더블캠 샤프트 피더스크린과 이중 원통형 이물질 분리장치를 이용한 건설폐기물 선별기술
5th row부유 및 부착성장(EPS 여재) 미생물을 이용한 접촉안정형 영양염류 처리 하이브리드 공정
ValueCountFrequency (%)
이용한 1359
 
6.4%
666
 
3.1%
기술 656
 
3.1%
생산기술 212
 
1.0%
콘크리트용 211
 
1.0%
순환골재 206
 
1.0%
비굴착 179
 
0.8%
순환 156
 
0.7%
이용하여 153
 
0.7%
장착된 144
 
0.7%
Other values (3213) 17285
81.4%
2023-12-12T21:59:54.872892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19205
 
18.7%
3079
 
3.0%
2619
 
2.5%
2442
 
2.4%
2029
 
2.0%
1852
 
1.8%
1784
 
1.7%
1531
 
1.5%
1453
 
1.4%
1358
 
1.3%
Other values (586) 65613
63.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74762
72.6%
Space Separator 19205
 
18.7%
Lowercase Letter 3457
 
3.4%
Uppercase Letter 3241
 
3.1%
Open Punctuation 629
 
0.6%
Close Punctuation 626
 
0.6%
Other Punctuation 575
 
0.6%
Dash Punctuation 242
 
0.2%
Decimal Number 198
 
0.2%
Letter Number 20
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3079
 
4.1%
2619
 
3.5%
2442
 
3.3%
2029
 
2.7%
1852
 
2.5%
1784
 
2.4%
1531
 
2.0%
1453
 
1.9%
1358
 
1.8%
977
 
1.3%
Other values (508) 55638
74.4%
Lowercase Letter
ValueCountFrequency (%)
e 503
14.6%
i 288
 
8.3%
r 283
 
8.2%
s 267
 
7.7%
t 236
 
6.8%
o 234
 
6.8%
n 232
 
6.7%
a 231
 
6.7%
l 230
 
6.7%
c 136
 
3.9%
Other values (17) 817
23.6%
Uppercase Letter
ValueCountFrequency (%)
S 498
15.4%
R 315
 
9.7%
B 304
 
9.4%
P 290
 
8.9%
C 210
 
6.5%
M 197
 
6.1%
T 171
 
5.3%
A 161
 
5.0%
F 140
 
4.3%
E 133
 
4.1%
Other values (15) 822
25.4%
Other Punctuation
ValueCountFrequency (%)
, 173
30.1%
· 161
28.0%
/ 116
20.2%
. 78
13.6%
: 32
 
5.6%
; 11
 
1.9%
& 2
 
0.3%
# 2
 
0.3%
Decimal Number
ValueCountFrequency (%)
2 112
56.6%
3 45
22.7%
4 17
 
8.6%
1 15
 
7.6%
8 4
 
2.0%
0 4
 
2.0%
5 1
 
0.5%
Other Symbol
ValueCountFrequency (%)
® 7
70.0%
2
 
20.0%
1
 
10.0%
Open Punctuation
ValueCountFrequency (%)
( 628
99.8%
[ 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 625
99.8%
] 1
 
0.2%
Letter Number
ValueCountFrequency (%)
16
80.0%
4
 
20.0%
Space Separator
ValueCountFrequency (%)
19205
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74739
72.6%
Common 21485
 
20.9%
Latin 6713
 
6.5%
Han 23
 
< 0.1%
Greek 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3079
 
4.1%
2619
 
3.5%
2442
 
3.3%
2029
 
2.7%
1852
 
2.5%
1784
 
2.4%
1531
 
2.0%
1453
 
1.9%
1358
 
1.8%
977
 
1.3%
Other values (501) 55615
74.4%
Latin
ValueCountFrequency (%)
e 503
 
7.5%
S 498
 
7.4%
R 315
 
4.7%
B 304
 
4.5%
P 290
 
4.3%
i 288
 
4.3%
r 283
 
4.2%
s 267
 
4.0%
t 236
 
3.5%
o 234
 
3.5%
Other values (43) 3495
52.1%
Common
ValueCountFrequency (%)
19205
89.4%
( 628
 
2.9%
) 625
 
2.9%
- 242
 
1.1%
, 173
 
0.8%
· 161
 
0.7%
/ 116
 
0.5%
2 112
 
0.5%
. 78
 
0.4%
3 45
 
0.2%
Other values (14) 100
 
0.5%
Han
ValueCountFrequency (%)
5
21.7%
5
21.7%
5
21.7%
3
13.0%
3
13.0%
1
 
4.3%
1
 
4.3%
Greek
ValueCountFrequency (%)
γ 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74720
72.6%
ASCII 28003
 
27.2%
None 177
 
0.2%
Number Forms 20
 
< 0.1%
Compat Jamo 19
 
< 0.1%
CJK 18
 
< 0.1%
CJK Compat Ideographs 5
 
< 0.1%
Enclosed Alphanum 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19205
68.6%
( 628
 
2.2%
) 625
 
2.2%
e 503
 
1.8%
S 498
 
1.8%
R 315
 
1.1%
B 304
 
1.1%
P 290
 
1.0%
i 288
 
1.0%
r 283
 
1.0%
Other values (59) 5064
 
18.1%
Hangul
ValueCountFrequency (%)
3079
 
4.1%
2619
 
3.5%
2442
 
3.3%
2029
 
2.7%
1852
 
2.5%
1784
 
2.4%
1531
 
2.0%
1453
 
1.9%
1358
 
1.8%
977
 
1.3%
Other values (500) 55596
74.4%
None
ValueCountFrequency (%)
· 161
91.0%
® 7
 
4.0%
γ 5
 
2.8%
2
 
1.1%
2
 
1.1%
Compat Jamo
ValueCountFrequency (%)
19
100.0%
Number Forms
ValueCountFrequency (%)
16
80.0%
4
 
20.0%
CJK
ValueCountFrequency (%)
5
27.8%
5
27.8%
3
16.7%
3
16.7%
1
 
5.6%
1
 
5.6%
CJK Compat Ideographs
ValueCountFrequency (%)
5
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
2
66.7%
1
33.3%

실적제출년도
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2012.3289
Minimum1999
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.4 KiB
2023-12-12T21:59:55.011305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1999
5-th percentile2003
Q12009
median2013
Q32016
95-th percentile2020
Maximum2020
Range21
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.973264
Coefficient of variation (CV)0.0024713971
Kurtosis-0.77983089
Mean2012.3289
Median Absolute Deviation (MAD)4
Skewness-0.38639464
Sum4423099
Variance24.733354
MonotonicityNot monotonic
2023-12-12T21:59:55.123220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
2016 214
 
9.7%
2017 191
 
8.7%
2010 177
 
8.1%
2015 151
 
6.9%
2018 149
 
6.8%
2012 128
 
5.8%
2014 124
 
5.6%
2013 119
 
5.4%
2020 117
 
5.3%
2011 115
 
5.2%
Other values (12) 713
32.4%
ValueCountFrequency (%)
1999 2
 
0.1%
2000 8
 
0.4%
2001 21
 
1.0%
2002 41
 
1.9%
2003 43
2.0%
2004 49
2.2%
2005 77
3.5%
2006 95
4.3%
2007 92
4.2%
2008 103
4.7%
ValueCountFrequency (%)
2020 117
5.3%
2019 80
 
3.6%
2018 149
6.8%
2017 191
8.7%
2016 214
9.7%
2015 151
6.9%
2014 124
5.6%
2013 119
5.4%
2012 128
5.8%
2011 115
5.2%

2.신기술_총적용건수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct148
Distinct (%)6.9%
Missing39
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean16.003705
Minimum0
Maximum1210
Zeros256
Zeros (%)11.6%
Negative0
Negative (%)0.0%
Memory size19.4 KiB
2023-12-12T21:59:55.271533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q313
95-th percentile70
Maximum1210
Range1210
Interquartile range (IQR)12

Descriptive statistics

Standard deviation44.383648
Coefficient of variation (CV)2.7733357
Kurtosis270.66123
Mean16.003705
Median Absolute Deviation (MAD)3
Skewness12.491081
Sum34552
Variance1969.9082
MonotonicityNot monotonic
2023-12-12T21:59:55.422886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 375
17.1%
0 256
 
11.6%
2 208
 
9.5%
3 146
 
6.6%
4 126
 
5.7%
5 111
 
5.1%
6 93
 
4.2%
7 61
 
2.8%
8 58
 
2.6%
9 50
 
2.3%
Other values (138) 675
30.7%
ValueCountFrequency (%)
0 256
11.6%
1 375
17.1%
2 208
9.5%
3 146
 
6.6%
4 126
 
5.7%
5 111
 
5.1%
6 93
 
4.2%
7 61
 
2.8%
8 58
 
2.6%
9 50
 
2.3%
ValueCountFrequency (%)
1210 1
< 0.1%
643 1
< 0.1%
413 1
< 0.1%
318 1
< 0.1%
306 1
< 0.1%
295 1
< 0.1%
291 1
< 0.1%
285 1
< 0.1%
258 1
< 0.1%
254 1
< 0.1%

총계약금액
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct1228
Distinct (%)80.6%
Missing675
Missing (%)30.7%
Infinite0
Infinite (%)0.0%
Mean3739358.3
Minimum0
Maximum1.111 × 109
Zeros273
Zeros (%)12.4%
Negative0
Negative (%)0.0%
Memory size19.4 KiB
2023-12-12T21:59:55.559101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1162879
median1257754
Q33538257.5
95-th percentile11981497
Maximum1.111 × 109
Range1.111 × 109
Interquartile range (IQR)3375378.5

Descriptive statistics

Standard deviation28886371
Coefficient of variation (CV)7.7249539
Kurtosis1421.092
Mean3739358.3
Median Absolute Deviation (MAD)1257754
Skewness37.081495
Sum5.6950427 × 109
Variance8.344224 × 1014
MonotonicityNot monotonic
2023-12-12T21:59:55.700742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 273
 
12.4%
1830311 4
 
0.2%
2665689 2
 
0.1%
1500278 2
 
0.1%
4124708 2
 
0.1%
220000 2
 
0.1%
1230539 2
 
0.1%
1420000 2
 
0.1%
1800 2
 
0.1%
1754500 2
 
0.1%
Other values (1218) 1230
56.0%
(Missing) 675
30.7%
ValueCountFrequency (%)
0 273
12.4%
1 1
 
< 0.1%
1800 2
 
0.1%
3300 1
 
< 0.1%
3924 1
 
< 0.1%
5016 1
 
< 0.1%
5681 1
 
< 0.1%
6800 1
 
< 0.1%
8000 1
 
< 0.1%
8830 1
 
< 0.1%
ValueCountFrequency (%)
1111000000 1
< 0.1%
78553000 1
< 0.1%
56870000 1
< 0.1%
41072157 1
< 0.1%
40904540 1
< 0.1%
35471971 1
< 0.1%
34187000 1
< 0.1%
33767338 1
< 0.1%
30787494 1
< 0.1%
30000000 1
< 0.1%
Distinct147
Distinct (%)87.0%
Missing2029
Missing (%)92.3%
Memory size17.3 KiB
2023-12-12T21:59:56.014290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length232
Median length93
Mean length32.017751
Min length1

Characters and Unicode

Total characters5411
Distinct characters344
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique133 ?
Unique (%)78.7%

Sample

1st row홍보인력부족과 운영자금의 부족으로 실적발생 안됨
2nd row수주사업 없음
3rd row신기술 적용을 위한 사업화 준비 단계 중에 있음.
4th row 계약 실적이 없음
5th row해당 기술 관련하여 처리 공법이 선정(1건)되었으나, 공사 계약 관련해서 2016년에 진행될 예정으로, 당해년도 활용실적이 없음
ValueCountFrequency (%)
없음 36
 
2.8%
신기술 24
 
1.9%
계약 15
 
1.2%
13
 
1.0%
사업 10
 
0.8%
10
 
0.8%
사업화 10
 
0.8%
실적없음 9
 
0.7%
관련 9
 
0.7%
있음 9
 
0.7%
Other values (782) 1123
88.6%
2023-12-12T21:59:56.481349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1126
 
20.8%
126
 
2.3%
99
 
1.8%
92
 
1.7%
88
 
1.6%
82
 
1.5%
80
 
1.5%
80
 
1.5%
80
 
1.5%
78
 
1.4%
Other values (334) 3480
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3959
73.2%
Space Separator 1126
 
20.8%
Decimal Number 168
 
3.1%
Other Punctuation 109
 
2.0%
Uppercase Letter 15
 
0.3%
Close Punctuation 11
 
0.2%
Open Punctuation 11
 
0.2%
Dash Punctuation 7
 
0.1%
Lowercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
126
 
3.2%
99
 
2.5%
92
 
2.3%
88
 
2.2%
82
 
2.1%
80
 
2.0%
80
 
2.0%
80
 
2.0%
78
 
2.0%
72
 
1.8%
Other values (300) 3082
77.8%
Decimal Number
ValueCountFrequency (%)
1 49
29.2%
2 47
28.0%
0 36
21.4%
6 9
 
5.4%
5 9
 
5.4%
3 7
 
4.2%
4 4
 
2.4%
7 4
 
2.4%
9 2
 
1.2%
8 1
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
O 2
13.3%
U 2
13.3%
P 2
13.3%
B 2
13.3%
M 2
13.3%
C 1
6.7%
F 1
6.7%
K 1
6.7%
S 1
6.7%
L 1
6.7%
Other Punctuation
ValueCountFrequency (%)
. 66
60.6%
, 31
28.4%
" 8
 
7.3%
: 2
 
1.8%
' 1
 
0.9%
/ 1
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
f 2
40.0%
s 1
20.0%
u 1
20.0%
l 1
20.0%
Space Separator
ValueCountFrequency (%)
1126
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3959
73.2%
Common 1432
 
26.5%
Latin 20
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
126
 
3.2%
99
 
2.5%
92
 
2.3%
88
 
2.2%
82
 
2.1%
80
 
2.0%
80
 
2.0%
80
 
2.0%
78
 
2.0%
72
 
1.8%
Other values (300) 3082
77.8%
Common
ValueCountFrequency (%)
1126
78.6%
. 66
 
4.6%
1 49
 
3.4%
2 47
 
3.3%
0 36
 
2.5%
, 31
 
2.2%
) 11
 
0.8%
( 11
 
0.8%
6 9
 
0.6%
5 9
 
0.6%
Other values (10) 37
 
2.6%
Latin
ValueCountFrequency (%)
O 2
10.0%
U 2
10.0%
P 2
10.0%
B 2
10.0%
f 2
10.0%
M 2
10.0%
C 1
 
5.0%
s 1
 
5.0%
u 1
 
5.0%
l 1
 
5.0%
Other values (4) 4
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3959
73.2%
ASCII 1452
 
26.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1126
77.5%
. 66
 
4.5%
1 49
 
3.4%
2 47
 
3.2%
0 36
 
2.5%
, 31
 
2.1%
) 11
 
0.8%
( 11
 
0.8%
6 9
 
0.6%
5 9
 
0.6%
Other values (24) 57
 
3.9%
Hangul
ValueCountFrequency (%)
126
 
3.2%
99
 
2.5%
92
 
2.3%
88
 
2.2%
82
 
2.1%
80
 
2.0%
80
 
2.0%
80
 
2.0%
78
 
2.0%
72
 
1.8%
Other values (300) 3082
77.8%
Distinct41
Distinct (%)85.4%
Missing2150
Missing (%)97.8%
Memory size17.3 KiB
2023-12-12T21:59:56.760878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length19
Mean length12.083333
Min length1

Characters and Unicode

Total characters580
Distinct characters182
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)72.9%

Sample

1st row제품(토양개량제) 포장지에 인쇄
2nd row수위 대응형 생태둠벙 시스템
3rd row건설폐기물재활용플랜트
4th row건설폐기물 중간처리시설
5th row과천시 환경사업소 유기성슬러지 에너지화 설비
ValueCountFrequency (%)
4
 
3.7%
동부이엔티(주 3
 
2.8%
1개소 3
 
2.8%
건설폐기물재활용플랜트 3
 
2.8%
0 3
 
2.8%
인쇄 3
 
2.8%
제1공장 2
 
1.8%
시스템 2
 
1.8%
공장 2
 
1.8%
지열 2
 
1.8%
Other values (72) 82
75.2%
2023-12-12T21:59:57.230596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
64
 
11.0%
18
 
3.1%
15
 
2.6%
14
 
2.4%
12
 
2.1%
11
 
1.9%
( 11
 
1.9%
) 11
 
1.9%
10
 
1.7%
10
 
1.7%
Other values (172) 404
69.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 428
73.8%
Space Separator 64
 
11.0%
Lowercase Letter 40
 
6.9%
Decimal Number 13
 
2.2%
Open Punctuation 11
 
1.9%
Close Punctuation 11
 
1.9%
Other Punctuation 5
 
0.9%
Math Symbol 4
 
0.7%
Uppercase Letter 4
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18
 
4.2%
15
 
3.5%
14
 
3.3%
12
 
2.8%
11
 
2.6%
10
 
2.3%
10
 
2.3%
9
 
2.1%
9
 
2.1%
9
 
2.1%
Other values (137) 311
72.7%
Lowercase Letter
ValueCountFrequency (%)
t 6
15.0%
c 4
10.0%
i 4
10.0%
o 4
10.0%
e 3
7.5%
l 3
7.5%
p 3
7.5%
r 3
7.5%
s 2
 
5.0%
n 2
 
5.0%
Other values (5) 6
15.0%
Decimal Number
ValueCountFrequency (%)
1 6
46.2%
0 3
23.1%
3 1
 
7.7%
5 1
 
7.7%
9 1
 
7.7%
2 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
. 1
20.0%
/ 1
20.0%
; 1
20.0%
& 1
20.0%
, 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
25.0%
K 1
25.0%
B 1
25.0%
S 1
25.0%
Math Symbol
ValueCountFrequency (%)
< 2
50.0%
> 2
50.0%
Space Separator
ValueCountFrequency (%)
64
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 428
73.8%
Common 108
 
18.6%
Latin 44
 
7.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18
 
4.2%
15
 
3.5%
14
 
3.3%
12
 
2.8%
11
 
2.6%
10
 
2.3%
10
 
2.3%
9
 
2.1%
9
 
2.1%
9
 
2.1%
Other values (137) 311
72.7%
Latin
ValueCountFrequency (%)
t 6
13.6%
c 4
 
9.1%
i 4
 
9.1%
o 4
 
9.1%
e 3
 
6.8%
l 3
 
6.8%
p 3
 
6.8%
r 3
 
6.8%
s 2
 
4.5%
n 2
 
4.5%
Other values (9) 10
22.7%
Common
ValueCountFrequency (%)
64
59.3%
( 11
 
10.2%
) 11
 
10.2%
1 6
 
5.6%
0 3
 
2.8%
< 2
 
1.9%
> 2
 
1.9%
3 1
 
0.9%
. 1
 
0.9%
5 1
 
0.9%
Other values (6) 6
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 428
73.8%
ASCII 152
 
26.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
64
42.1%
( 11
 
7.2%
) 11
 
7.2%
1 6
 
3.9%
t 6
 
3.9%
c 4
 
2.6%
i 4
 
2.6%
o 4
 
2.6%
e 3
 
2.0%
l 3
 
2.0%
Other values (25) 36
23.7%
Hangul
ValueCountFrequency (%)
18
 
4.2%
15
 
3.5%
14
 
3.3%
12
 
2.8%
11
 
2.6%
10
 
2.3%
10
 
2.3%
9
 
2.1%
9
 
2.1%
9
 
2.1%
Other values (137) 311
72.7%

사용공정
Text

MISSING 

Distinct29
Distinct (%)87.9%
Missing2165
Missing (%)98.5%
Memory size17.3 KiB
2023-12-12T21:59:57.530724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length17
Mean length11.939394
Min length1

Characters and Unicode

Total characters394
Distinct characters127
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

Unique26 ?
Unique (%)78.8%

Sample

1st row생태복원
2nd row건설폐기물재활용플랜트공정설비
3rd row이물질제거 중간처리설비
4th row진공유중건조공정
5th row0
ValueCountFrequency (%)
0 3
 
3.8%
공정 3
 
3.8%
건설폐기물재활용플랜트공정설비 2
 
2.5%
오염방지 2
 
2.5%
지중열교환기 2
 
2.5%
2
 
2.5%
분리시설 2
 
2.5%
팜플렛 2
 
2.5%
중간처리 2
 
2.5%
중1개소 2
 
2.5%
Other values (57) 58
72.5%
2023-12-12T21:59:57.995184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49
 
12.4%
12
 
3.0%
11
 
2.8%
11
 
2.8%
10
 
2.5%
10
 
2.5%
10
 
2.5%
10
 
2.5%
7
 
1.8%
7
 
1.8%
Other values (117) 257
65.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 314
79.7%
Space Separator 49
 
12.4%
Decimal Number 11
 
2.8%
Uppercase Letter 10
 
2.5%
Other Punctuation 5
 
1.3%
Dash Punctuation 3
 
0.8%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12
 
3.8%
11
 
3.5%
11
 
3.5%
10
 
3.2%
10
 
3.2%
10
 
3.2%
10
 
3.2%
7
 
2.2%
7
 
2.2%
7
 
2.2%
Other values (102) 219
69.7%
Uppercase Letter
ValueCountFrequency (%)
E 3
30.0%
C 2
20.0%
P 2
20.0%
T 1
 
10.0%
F 1
 
10.0%
R 1
 
10.0%
Decimal Number
ValueCountFrequency (%)
0 5
45.5%
1 5
45.5%
2 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
. 1
 
20.0%
Space Separator
ValueCountFrequency (%)
49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 314
79.7%
Common 70
 
17.8%
Latin 10
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12
 
3.8%
11
 
3.5%
11
 
3.5%
10
 
3.2%
10
 
3.2%
10
 
3.2%
10
 
3.2%
7
 
2.2%
7
 
2.2%
7
 
2.2%
Other values (102) 219
69.7%
Common
ValueCountFrequency (%)
49
70.0%
0 5
 
7.1%
1 5
 
7.1%
, 4
 
5.7%
- 3
 
4.3%
( 1
 
1.4%
2 1
 
1.4%
. 1
 
1.4%
) 1
 
1.4%
Latin
ValueCountFrequency (%)
E 3
30.0%
C 2
20.0%
P 2
20.0%
T 1
 
10.0%
F 1
 
10.0%
R 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 314
79.7%
ASCII 80
 
20.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49
61.3%
0 5
 
6.2%
1 5
 
6.2%
, 4
 
5.0%
- 3
 
3.8%
E 3
 
3.8%
C 2
 
2.5%
P 2
 
2.5%
( 1
 
1.2%
2 1
 
1.2%
Other values (5) 5
 
6.2%
Hangul
ValueCountFrequency (%)
12
 
3.8%
11
 
3.5%
11
 
3.5%
10
 
3.2%
10
 
3.2%
10
 
3.2%
10
 
3.2%
7
 
2.2%
7
 
2.2%
7
 
2.2%
Other values (102) 219
69.7%

사용제품명
Text

MISSING 

Distinct41
Distinct (%)69.5%
Missing2139
Missing (%)97.3%
Memory size17.3 KiB
2023-12-12T21:59:58.320139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length27
Mean length10.694915
Min length1

Characters and Unicode

Total characters631
Distinct characters202
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)50.8%

Sample

1st row토양개량제(바이오그로)
2nd row생태둠벙시스템
3rd row맨틀과 콘케이브 표면의 사선형 요철과 익센트릭의 기울기를 조절한 고속회전 콘크라셔
4th row조류제거제
5th row초미세먼지채취기
ValueCountFrequency (%)
조류제거제 5
 
4.1%
순환골재 4
 
3.3%
콘크라셔 4
 
3.3%
측정기 3
 
2.4%
수지파형강관 3
 
2.4%
모듈 3
 
2.4%
센서 3
 
2.4%
지열시스템 3
 
2.4%
토양개량제(바이오그로 3
 
2.4%
그린네트 3
 
2.4%
Other values (71) 89
72.4%
2023-12-12T21:59:58.790884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
65
 
10.3%
15
 
2.4%
13
 
2.1%
13
 
2.1%
12
 
1.9%
11
 
1.7%
10
 
1.6%
10
 
1.6%
9
 
1.4%
9
 
1.4%
Other values (192) 464
73.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 462
73.2%
Space Separator 65
 
10.3%
Uppercase Letter 40
 
6.3%
Lowercase Letter 22
 
3.5%
Decimal Number 14
 
2.2%
Other Punctuation 11
 
1.7%
Open Punctuation 6
 
1.0%
Close Punctuation 6
 
1.0%
Dash Punctuation 5
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
15
 
3.2%
13
 
2.8%
13
 
2.8%
12
 
2.6%
11
 
2.4%
10
 
2.2%
10
 
2.2%
9
 
1.9%
9
 
1.9%
7
 
1.5%
Other values (149) 353
76.4%
Uppercase Letter
ValueCountFrequency (%)
C 5
12.5%
R 5
12.5%
A 4
10.0%
P 4
10.0%
F 3
 
7.5%
O 3
 
7.5%
E 3
 
7.5%
S 2
 
5.0%
T 2
 
5.0%
H 1
 
2.5%
Other values (8) 8
20.0%
Lowercase Letter
ValueCountFrequency (%)
t 3
13.6%
a 3
13.6%
s 2
 
9.1%
u 2
 
9.1%
e 2
 
9.1%
h 1
 
4.5%
c 1
 
4.5%
r 1
 
4.5%
i 1
 
4.5%
g 1
 
4.5%
Other values (5) 5
22.7%
Other Punctuation
ValueCountFrequency (%)
, 8
72.7%
. 2
 
18.2%
& 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
0 7
50.0%
2 4
28.6%
1 3
21.4%
Space Separator
ValueCountFrequency (%)
65
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 462
73.2%
Common 107
 
17.0%
Latin 62
 
9.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
15
 
3.2%
13
 
2.8%
13
 
2.8%
12
 
2.6%
11
 
2.4%
10
 
2.2%
10
 
2.2%
9
 
1.9%
9
 
1.9%
7
 
1.5%
Other values (149) 353
76.4%
Latin
ValueCountFrequency (%)
C 5
 
8.1%
R 5
 
8.1%
A 4
 
6.5%
P 4
 
6.5%
F 3
 
4.8%
t 3
 
4.8%
O 3
 
4.8%
a 3
 
4.8%
E 3
 
4.8%
s 2
 
3.2%
Other values (23) 27
43.5%
Common
ValueCountFrequency (%)
65
60.7%
, 8
 
7.5%
0 7
 
6.5%
( 6
 
5.6%
) 6
 
5.6%
- 5
 
4.7%
2 4
 
3.7%
1 3
 
2.8%
. 2
 
1.9%
& 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 462
73.2%
ASCII 169
 
26.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
65
38.5%
, 8
 
4.7%
0 7
 
4.1%
( 6
 
3.6%
) 6
 
3.6%
C 5
 
3.0%
R 5
 
3.0%
- 5
 
3.0%
2 4
 
2.4%
A 4
 
2.4%
Other values (33) 54
32.0%
Hangul
ValueCountFrequency (%)
15
 
3.2%
13
 
2.8%
13
 
2.8%
12
 
2.6%
11
 
2.4%
10
 
2.2%
10
 
2.2%
9
 
1.9%
9
 
1.9%
7
 
1.5%
Other values (149) 353
76.4%

제품 연매출액
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct40
Distinct (%)3.7%
Missing1108
Missing (%)50.4%
Infinite0
Infinite (%)0.0%
Mean132109.38
Minimum0
Maximum25000000
Zeros1049
Zeros (%)47.7%
Negative0
Negative (%)0.0%
Memory size19.4 KiB
2023-12-12T21:59:58.945136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum25000000
Range25000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1219799.7
Coefficient of variation (CV)9.2332558
Kurtosis219.89184
Mean132109.38
Median Absolute Deviation (MAD)0
Skewness13.551954
Sum1.4399923 × 108
Variance1.4879114 × 1012
MonotonicityNot monotonic
2023-12-12T21:59:59.145272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0 1049
47.7%
10000000 2
 
0.1%
10000 2
 
0.1%
649667 1
 
< 0.1%
370805 1
 
< 0.1%
275177 1
 
< 0.1%
4500000 1
 
< 0.1%
1355318 1
 
< 0.1%
17689000 1
 
< 0.1%
100000 1
 
< 0.1%
Other values (30) 30
 
1.4%
(Missing) 1108
50.4%
ValueCountFrequency (%)
0 1049
47.7%
240 1
 
< 0.1%
1800 1
 
< 0.1%
10000 2
 
0.1%
44788 1
 
< 0.1%
100000 1
 
< 0.1%
171436 1
 
< 0.1%
243029 1
 
< 0.1%
275177 1
 
< 0.1%
281380 1
 
< 0.1%
ValueCountFrequency (%)
25000000 1
< 0.1%
17689000 1
< 0.1%
11500000 1
< 0.1%
10404000 1
< 0.1%
10000000 2
0.1%
8900000 1
< 0.1%
7200000 1
< 0.1%
4596000 1
< 0.1%
4500000 1
< 0.1%
4343091 1
< 0.1%

홍보물종류
Text

MISSING 

Distinct58
Distinct (%)56.9%
Missing2096
Missing (%)95.4%
Memory size17.3 KiB
2023-12-12T21:59:59.470263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length26
Mean length7.9117647
Min length1

Characters and Unicode

Total characters807
Distinct characters126
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)44.1%

Sample

1st row카달로그 발송
2nd row제품 포장지
3rd row카다로그 발송
4th row카다록 및 기술설명자료
5th row국내 및 외국어 제품카달로그, 해외 온라인마켓시장, 명함, 우편봉투, 정기 간행물, 인보이스, 견적서, 각종 홍보물
ValueCountFrequency (%)
카다로그 29
 
15.4%
카달로그 11
 
5.9%
카탈로그 11
 
5.9%
8
 
4.3%
제품 5
 
2.7%
포장지 5
 
2.7%
브로셔 4
 
2.1%
기술자료집 4
 
2.1%
견적서 4
 
2.1%
발송 4
 
2.1%
Other values (72) 103
54.8%
2023-12-12T21:59:59.915523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
88
 
10.9%
64
 
7.9%
60
 
7.4%
57
 
7.1%
, 38
 
4.7%
32
 
4.0%
20
 
2.5%
20
 
2.5%
17
 
2.1%
17
 
2.1%
Other values (116) 394
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 653
80.9%
Space Separator 88
 
10.9%
Other Punctuation 39
 
4.8%
Decimal Number 16
 
2.0%
Uppercase Letter 7
 
0.9%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
64
 
9.8%
60
 
9.2%
57
 
8.7%
32
 
4.9%
20
 
3.1%
20
 
3.1%
17
 
2.6%
17
 
2.6%
14
 
2.1%
14
 
2.1%
Other values (100) 338
51.8%
Uppercase Letter
ValueCountFrequency (%)
P 2
28.6%
C 1
14.3%
D 1
14.3%
I 1
14.3%
E 1
14.3%
T 1
14.3%
Decimal Number
ValueCountFrequency (%)
0 6
37.5%
1 5
31.2%
7 2
 
12.5%
2 2
 
12.5%
3 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 38
97.4%
& 1
 
2.6%
Space Separator
ValueCountFrequency (%)
88
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 653
80.9%
Common 147
 
18.2%
Latin 7
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
64
 
9.8%
60
 
9.2%
57
 
8.7%
32
 
4.9%
20
 
3.1%
20
 
3.1%
17
 
2.6%
17
 
2.6%
14
 
2.1%
14
 
2.1%
Other values (100) 338
51.8%
Common
ValueCountFrequency (%)
88
59.9%
, 38
25.9%
0 6
 
4.1%
1 5
 
3.4%
) 2
 
1.4%
( 2
 
1.4%
7 2
 
1.4%
2 2
 
1.4%
& 1
 
0.7%
3 1
 
0.7%
Latin
ValueCountFrequency (%)
P 2
28.6%
C 1
14.3%
D 1
14.3%
I 1
14.3%
E 1
14.3%
T 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 653
80.9%
ASCII 154
 
19.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
88
57.1%
, 38
24.7%
0 6
 
3.9%
1 5
 
3.2%
) 2
 
1.3%
( 2
 
1.3%
P 2
 
1.3%
7 2
 
1.3%
2 2
 
1.3%
C 1
 
0.6%
Other values (6) 6
 
3.9%
Hangul
ValueCountFrequency (%)
64
 
9.8%
60
 
9.2%
57
 
8.7%
32
 
4.9%
20
 
3.1%
20
 
3.1%
17
 
2.6%
17
 
2.6%
14
 
2.1%
14
 
2.1%
Other values (100) 338
51.8%

홍보물 발행수량
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct27
Distinct (%)3.3%
Missing1390
Missing (%)63.2%
Infinite0
Infinite (%)0.0%
Mean646.9505
Minimum0
Maximum114837
Zeros718
Zeros (%)32.7%
Negative0
Negative (%)0.0%
Memory size19.4 KiB
2023-12-12T22:00:00.085202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1000
Maximum114837
Range114837
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6103.2695
Coefficient of variation (CV)9.433905
Kurtosis254.73622
Mean646.9505
Median Absolute Deviation (MAD)0
Skewness15.252037
Sum522736
Variance37249899
MonotonicityNot monotonic
2023-12-12T22:00:00.225488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 718
32.7%
1000 15
 
0.7%
500 13
 
0.6%
2000 8
 
0.4%
300 6
 
0.3%
20000 5
 
0.2%
1 5
 
0.2%
4000 4
 
0.2%
100 4
 
0.2%
200 4
 
0.2%
Other values (17) 26
 
1.2%
(Missing) 1390
63.2%
ValueCountFrequency (%)
0 718
32.7%
1 5
 
0.2%
3 1
 
< 0.1%
4 1
 
< 0.1%
10 1
 
< 0.1%
15 1
 
< 0.1%
50 1
 
< 0.1%
52 1
 
< 0.1%
100 4
 
0.2%
200 4
 
0.2%
ValueCountFrequency (%)
114837 1
 
< 0.1%
100000 1
 
< 0.1%
66000 1
 
< 0.1%
20000 5
0.2%
15000 1
 
< 0.1%
10000 3
0.1%
7200 2
 
0.1%
5000 4
0.2%
4000 4
0.2%
3000 1
 
< 0.1%

사용효과
Text

MISSING 

Distinct87
Distinct (%)29.7%
Missing1905
Missing (%)86.7%
Memory size17.3 KiB
2023-12-12T22:00:00.548368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length692
Median length393
Mean length27.617747
Min length1

Characters and Unicode

Total characters8092
Distinct characters405
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)22.9%

Sample

1st row신기술 협약 및 시설, 공정에의 적용 증대 효과.
2nd row실적 없음
3rd row실적없음
4th row제품 품질에 대한 인지도 향상
5th row실적없음
ValueCountFrequency (%)
없음 152
 
7.7%
57
 
2.9%
실적없음 53
 
2.7%
실적 37
 
1.9%
기술 25
 
1.3%
대한 24
 
1.2%
17
 
0.9%
16
 
0.8%
홍보 15
 
0.8%
국내 15
 
0.8%
Other values (849) 1570
79.3%
2023-12-12T22:00:01.064048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1710
 
21.1%
221
 
2.7%
220
 
2.7%
211
 
2.6%
157
 
1.9%
142
 
1.8%
119
 
1.5%
112
 
1.4%
104
 
1.3%
102
 
1.3%
Other values (395) 4994
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5956
73.6%
Space Separator 1710
 
21.1%
Other Punctuation 237
 
2.9%
Uppercase Letter 61
 
0.8%
Decimal Number 57
 
0.7%
Lowercase Letter 23
 
0.3%
Close Punctuation 21
 
0.3%
Dash Punctuation 11
 
0.1%
Open Punctuation 10
 
0.1%
Control 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
221
 
3.7%
220
 
3.7%
211
 
3.5%
157
 
2.6%
142
 
2.4%
119
 
2.0%
112
 
1.9%
104
 
1.7%
102
 
1.7%
92
 
1.5%
Other values (354) 4476
75.2%
Uppercase Letter
ValueCountFrequency (%)
E 17
27.9%
T 15
24.6%
N 13
21.3%
C 4
 
6.6%
P 2
 
3.3%
W 2
 
3.3%
K 2
 
3.3%
S 1
 
1.6%
B 1
 
1.6%
O 1
 
1.6%
Other values (3) 3
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 87
36.7%
, 81
34.2%
* 32
 
13.5%
" 20
 
8.4%
' 4
 
1.7%
% 3
 
1.3%
& 3
 
1.3%
; 3
 
1.3%
/ 2
 
0.8%
2
 
0.8%
Decimal Number
ValueCountFrequency (%)
2 15
26.3%
1 15
26.3%
3 10
17.5%
0 8
14.0%
4 6
 
10.5%
5 3
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
e 5
21.7%
t 5
21.7%
a 4
17.4%
r 4
17.4%
g 3
13.0%
o 2
 
8.7%
Space Separator
ValueCountFrequency (%)
1710
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Control
ValueCountFrequency (%)
4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5956
73.6%
Common 2052
 
25.4%
Latin 84
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
221
 
3.7%
220
 
3.7%
211
 
3.5%
157
 
2.6%
142
 
2.4%
119
 
2.0%
112
 
1.9%
104
 
1.7%
102
 
1.7%
92
 
1.5%
Other values (354) 4476
75.2%
Common
ValueCountFrequency (%)
1710
83.3%
. 87
 
4.2%
, 81
 
3.9%
* 32
 
1.6%
) 21
 
1.0%
" 20
 
1.0%
2 15
 
0.7%
1 15
 
0.7%
- 11
 
0.5%
3 10
 
0.5%
Other values (12) 50
 
2.4%
Latin
ValueCountFrequency (%)
E 17
20.2%
T 15
17.9%
N 13
15.5%
e 5
 
6.0%
t 5
 
6.0%
a 4
 
4.8%
r 4
 
4.8%
C 4
 
4.8%
g 3
 
3.6%
P 2
 
2.4%
Other values (9) 12
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5936
73.4%
ASCII 2134
 
26.4%
Compat Jamo 20
 
0.2%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1710
80.1%
. 87
 
4.1%
, 81
 
3.8%
* 32
 
1.5%
) 21
 
1.0%
" 20
 
0.9%
E 17
 
0.8%
2 15
 
0.7%
1 15
 
0.7%
T 15
 
0.7%
Other values (30) 121
 
5.7%
Hangul
ValueCountFrequency (%)
221
 
3.7%
220
 
3.7%
211
 
3.6%
157
 
2.6%
142
 
2.4%
119
 
2.0%
112
 
1.9%
104
 
1.8%
102
 
1.7%
92
 
1.5%
Other values (353) 4456
75.1%
Compat Jamo
ValueCountFrequency (%)
20
100.0%
Punctuation
ValueCountFrequency (%)
2
100.0%

Interactions

2023-12-12T21:59:51.881038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:47.036163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:47.868860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:48.771204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:49.567469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:50.263792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:51.003207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:52.012296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:47.150715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:48.011150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:48.884810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:49.667736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:50.393500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:51.159694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:52.132065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:47.291661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:48.146958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:49.006048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:49.760120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:50.495053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:51.274850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:52.258602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:47.388278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:48.244935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:49.113442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:49.850563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:50.590629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:51.402229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:52.351697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:47.497267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:48.350097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:49.237668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:49.942841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:50.684806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:51.518367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:52.474679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:47.623523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:48.500164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:49.358784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:50.036503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:50.776022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:51.653109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:52.570152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:47.739999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:48.632374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:49.474227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:50.131393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:50.872847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:59:51.764790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:00:01.211116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
활용실적 순번신청서ID실적제출년도2.신기술_총적용건수총계약금액3.NET마크사용_시설사용공정사용제품명제품 연매출액홍보물종류홍보물 발행수량사용효과
활용실적 순번1.0000.8510.9770.1210.1490.8950.9400.6720.2290.8450.5300.927
신청서ID0.8511.0000.8420.0340.0000.8690.5220.9550.0920.8670.3440.901
실적제출년도0.9770.8421.0000.1250.0000.9550.8680.6290.0870.8240.2350.942
2.신기술_총적용건수0.1210.0340.1251.0000.0001.0001.0001.0000.0001.0000.0000.000
총계약금액0.1490.0000.0000.0001.000NaNNaNNaN0.000NaNNaN0.000
3.NET마크사용_시설0.8950.8690.9551.000NaN1.0000.9990.9930.9860.9950.0000.993
사용공정0.9400.5220.8681.000NaN0.9991.0000.9840.9600.9481.0001.000
사용제품명0.6720.9550.6291.000NaN0.9930.9841.0000.0000.9950.0000.998
제품 연매출액0.2290.0920.0870.0000.0000.9860.9600.0001.0000.7400.2440.974
홍보물종류0.8450.8670.8241.000NaN0.9950.9480.9950.7401.0000.8140.995
홍보물 발행수량0.5300.3440.2350.000NaN0.0001.0000.0000.2440.8141.0001.000
사용효과0.9270.9010.9420.0000.0000.9931.0000.9980.9740.9951.0001.000
2023-12-12T22:00:01.701200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
활용실적 순번신청서ID실적제출년도2.신기술_총적용건수총계약금액제품 연매출액홍보물 발행수량
활용실적 순번1.0000.9450.9960.0130.041-0.122-0.333
신청서ID0.9451.0000.9460.0060.018-0.126-0.309
실적제출년도0.9960.9461.0000.0110.039-0.124-0.341
2.신기술_총적용건수0.0130.0060.0111.0000.6980.0880.040
총계약금액0.0410.0180.0390.6981.000-0.005-0.053
제품 연매출액-0.122-0.126-0.1240.088-0.0051.0000.616
홍보물 발행수량-0.333-0.309-0.3410.040-0.0530.6161.000

Missing values

2023-12-12T21:59:52.742341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:59:52.946747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T21:59:53.431512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

활용실적 순번신청서ID기술명실적제출년도2.신기술_총적용건수총계약금액활용실적 없는 사유3.NET마크사용_시설사용공정사용제품명제품 연매출액홍보물종류홍보물 발행수량사용효과
01466698오일순환 윤활방식으로 개량한 Direct Drive Cone Crusher를 이용한 순환잔골재의 품질향상 기술20111221261216<NA><NA><NA><NA><NA>카달로그 발송240신기술 협약 및 시설, 공정에의 적용 증대 효과.
11488977건식 집진커터와 알루미늄드럼 팩커를 이용한 맨홀철개 인상 보수공법2011433159098<NA><NA><NA><NA><NA><NA><NA>실적 없음
21503956연속반응식 인제거여과기(IPRTM-Process)를 이용한 하폐수 고도처리기술2011158619850<NA><NA><NA><NA><NA><NA><NA><NA>
316101459더블캠 샤프트 피더스크린과 이중 원통형 이물질 분리장치를 이용한 건설폐기물 선별기술20115913242313<NA><NA><NA><NA><NA><NA><NA><NA>
416121196부유 및 부착성장(EPS 여재) 미생물을 이용한 접촉안정형 영양염류 처리 하이브리드 공정20112557878<NA><NA><NA><NA><NA><NA><NA><NA>
51667993다단 수평 해머가 장착된 수직형 크러셔를 이용하여 폐콘크리트로부터 도로공사용 순환골재를 생산하는 중간처리기술2011193908043<NA><NA><NA><NA><NA><NA><NA><NA>
61615899중력식 섬유여과기(GFF-FILTER)를 이용한 하수처리장 생물학적 처리수의 부유물질 제거 기술201131378000<NA><NA><NA><NA>0<NA><NA>실적없음
716181960저서성 패류양식장 해저토질 개선기술201100홍보인력부족과 운영자금의 부족으로 실적발생 안됨<NA><NA><NA><NA><NA><NA><NA>
816362986실시간 계측데이터 기반의 상수관망 블록 관리 시스템201112354000<NA><NA><NA><NA><NA><NA><NA><NA>
917584435환경친화적 토양개량제(바이오그로)를 이용한 불용(不用) 토양의 자원화를 통한 환경 생태 복원 기술201272836015<NA>제품(토양개량제) 포장지에 인쇄<NA>토양개량제(바이오그로)835775제품 포장지100000제품 품질에 대한 인지도 향상
활용실적 순번신청서ID기술명실적제출년도2.신기술_총적용건수총계약금액활용실적 없는 사유3.NET마크사용_시설사용공정사용제품명제품 연매출액홍보물종류홍보물 발행수량사용효과
2188391115021버켓 방식의 드럼과 타격박리기를 적용한 콘크리트용 순환 굵은골재 생산기술202000<NA><NA><NA><NA>0<NA>0<NA>
2189391515622알루미늄계 슬러지의 수열합성을 적용한 악취제거용 흡착제 제조기술202025402228<NA><NA><NA><NA>0<NA>0<NA>
2190391912081타원형 기류차단기와 무한궤도가 장착된 반전기를 이용한 연속반전삽입 하수관로 비굴착 전체 보수기술202094359060<NA><NA><NA><NA>0<NA>0<NA>
2191392113249원죠-원롤과 해머크러셔를 일체화 시킨 파쇄장치를 이용하여 콘크리트용 순환 굵은골재를 생산하는 기술2020112509953<NA><NA><NA><NA>0<NA>0<NA>
2192393415429양면융착 보강튜브 제조시스템과 경화시간을 단축하는 레진을 이용한 하수관 비굴착 보수기술20201512256864<NA><NA><NA><NA>0<NA>0<NA>
2193393615490평면식 샤프트형 선별스크린과 토사내 이물질 분리장치를 이용한 폐기물 선별ㆍ분리기술202011107296<NA><NA><NA><NA>0<NA>0<NA>
2194393715526다수의 교차 회전날개가 부착되어 있는 드럼으로 구성된 장치와 밀폐형 송풍/집진 및 분리 장치를 결합시킨 순환골재 모르타르 박리·제거기술2020221503590<NA><NA><NA><NA>0<NA>0<NA>
219539519181순환골재 생산공정에서 프레임 일체형 T-angle bar와 스프링유닛 및 분할스크린보드에 의해 진동이 유도되는 트롬멜을 이용하여 토사를 분리하는 기술202091357337<NA><NA><NA><NA>0카탈로그1<NA>
2196395315552다층 레이어시스템을 이용한 하수관거 보수너비 조절 비굴착 부분 보수 기술2020186867892<NA><NA><NA><NA>0<NA>0<NA>
2197395515560장력 저감 반전장치와 정온정압 유지장치를 이용한 하수관거 비굴착 전체보수 공법20203588880<NA><NA><NA><NA>0<NA>0<NA>