Overview

Dataset statistics

Number of variables18
Number of observations10000
Missing cells79
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory156.0 B

Variable types

Numeric3
Text9
DateTime2
Categorical4

Dataset

Description문서고유id,제목,부서명,전화번호,작성자,등록일,해당년도,해당월,문서url,구분(시장실만 사용),전체부서명,집행일시,집행장소,집행목적,집행대상,결제방법,집행금액,비목
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-22156/S/1/datasetView.do

Alerts

구분(시장실만 사용) is highly overall correlated with 해당년도 and 1 other fieldsHigh correlation
비목 is highly overall correlated with 구분(시장실만 사용)High correlation
해당년도 is highly overall correlated with 문서고유id and 1 other fieldsHigh correlation
문서고유id is highly overall correlated with 해당월 and 1 other fieldsHigh correlation
해당월 is highly overall correlated with 문서고유idHigh correlation
해당년도 is highly imbalanced (99.7%)Imbalance
구분(시장실만 사용) is highly imbalanced (94.2%)Imbalance
집행금액 is highly skewed (γ1 = 26.71073664)Skewed

Reproduction

Analysis started2024-05-18 00:05:17.698265
Analysis finished2024-05-18 00:05:27.793490
Duration10.1 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

문서고유id
Real number (ℝ)

HIGH CORRELATION 

Distinct1082
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29494646
Minimum27764949
Maximum30704840
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T09:05:28.114775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27764949
5-th percentile28823285
Q129183573
median29580235
Q329869141
95-th percentile30115387
Maximum30704840
Range2939891
Interquartile range (IQR)685568

Descriptive statistics

Standard deviation463559.25
Coefficient of variation (CV)0.015716725
Kurtosis0.49449902
Mean29494646
Median Absolute Deviation (MAD)356310
Skewness-0.62088919
Sum2.9494646 × 1011
Variance2.1488718 × 1011
MonotonicityNot monotonic
2024-05-18T09:05:28.727735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29870441 111
 
1.1%
29656005 99
 
1.0%
30115434 95
 
0.9%
28823285 93
 
0.9%
29225070 89
 
0.9%
29406101 80
 
0.8%
29394605 46
 
0.5%
30072887 45
 
0.4%
29858221 45
 
0.4%
29223887 45
 
0.4%
Other values (1072) 9252
92.5%
ValueCountFrequency (%)
27764949 7
0.1%
27774815 5
 
0.1%
27813408 10
0.1%
27821205 1
 
< 0.1%
27821292 7
0.1%
27821309 14
0.1%
27822607 7
0.1%
27831344 3
 
< 0.1%
27831381 8
0.1%
27912495 5
 
0.1%
ValueCountFrequency (%)
30704840 1
 
< 0.1%
30301295 1
 
< 0.1%
30267889 6
0.1%
30182993 7
0.1%
30165566 11
0.1%
30148992 10
0.1%
30139672 14
0.1%
30139471 6
0.1%
30137967 6
0.1%
30130754 2
 
< 0.1%

제목
Text

Distinct1082
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T09:05:29.557957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length55
Mean length47.8741
Min length33

Characters and Unicode

Total characters478741
Distinct characters222
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)0.4%

Sample

1st row2023년 8월 서울시본청 기획조정실 재정기획관 재정담당관 업무추진비 - 시책추진 부서운영
2nd row2023년 9월 서울시본청 도시교통실 교통기획관 교통정책과 업무추진비 - 기관운영 시책추진 부서운영
3rd row2023년 9월 서울시본청 행정국 인사과 업무추진비 - 시책추진 부서운영
4th row2023년 8월 서울시본청 디자인정책관 디자인정책담당관 업무추진비 - 기관운영 시책추진 부서운영
5th row2023년 11월 서울시본청 여성가족정책실 아동담당관 업무추진비 - 시책추진 부서운영
ValueCountFrequency (%)
10000
 
10.6%
서울시본청 10000
 
10.6%
업무추진비 10000
 
10.6%
2023년 9998
 
10.6%
시책추진 8381
 
8.9%
부서운영 7101
 
7.5%
기관운영 4265
 
4.5%
12월 1888
 
2.0%
11월 1626
 
1.7%
8월 1528
 
1.6%
Other values (226) 29399
31.2%
2024-05-18T09:05:31.077887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
84186
 
17.6%
2 22092
 
4.6%
21156
 
4.4%
18847
 
3.9%
18805
 
3.9%
17234
 
3.6%
13659
 
2.9%
12180
 
2.5%
0 11507
 
2.4%
11457
 
2.4%
Other values (212) 247618
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 329117
68.7%
Space Separator 84186
 
17.6%
Decimal Number 55346
 
11.6%
Dash Punctuation 10000
 
2.1%
Uppercase Letter 92
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
21156
 
6.4%
18847
 
5.7%
18805
 
5.7%
17234
 
5.2%
13659
 
4.2%
12180
 
3.7%
11457
 
3.5%
11438
 
3.5%
11345
 
3.4%
11023
 
3.3%
Other values (198) 181973
55.3%
Decimal Number
ValueCountFrequency (%)
2 22092
39.9%
0 11507
20.8%
3 10069
18.2%
1 6871
 
12.4%
8 1554
 
2.8%
9 1327
 
2.4%
7 1089
 
2.0%
6 626
 
1.1%
5 122
 
0.2%
4 89
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
I 46
50.0%
A 46
50.0%
Space Separator
ValueCountFrequency (%)
84186
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 329117
68.7%
Common 149532
31.2%
Latin 92
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
21156
 
6.4%
18847
 
5.7%
18805
 
5.7%
17234
 
5.2%
13659
 
4.2%
12180
 
3.7%
11457
 
3.5%
11438
 
3.5%
11345
 
3.4%
11023
 
3.3%
Other values (198) 181973
55.3%
Common
ValueCountFrequency (%)
84186
56.3%
2 22092
 
14.8%
0 11507
 
7.7%
3 10069
 
6.7%
- 10000
 
6.7%
1 6871
 
4.6%
8 1554
 
1.0%
9 1327
 
0.9%
7 1089
 
0.7%
6 626
 
0.4%
Other values (2) 211
 
0.1%
Latin
ValueCountFrequency (%)
I 46
50.0%
A 46
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 329117
68.7%
ASCII 149624
31.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
84186
56.3%
2 22092
 
14.8%
0 11507
 
7.7%
3 10069
 
6.7%
- 10000
 
6.7%
1 6871
 
4.6%
8 1554
 
1.0%
9 1327
 
0.9%
7 1089
 
0.7%
6 626
 
0.4%
Other values (4) 303
 
0.2%
Hangul
ValueCountFrequency (%)
21156
 
6.4%
18847
 
5.7%
18805
 
5.7%
17234
 
5.2%
13659
 
4.2%
12180
 
3.7%
11457
 
3.5%
11438
 
3.5%
11345
 
3.4%
11023
 
3.3%
Other values (198) 181973
55.3%
Distinct216
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T09:05:31.916616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length7.1487
Min length1

Characters and Unicode

Total characters71487
Distinct characters210
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row재정담당관
2nd row도시교통실 교통정책과
3rd row인사과
4th row디자인정책담당관
5th row아동담당관
ValueCountFrequency (%)
총무과 570
 
4.7%
홍보담당관 379
 
3.1%
경제정책실 369
 
3.0%
재난안전정책과 268
 
2.2%
언론담당관 266
 
2.2%
교통정책과 196
 
1.6%
기획조정실 180
 
1.5%
양성평등담당관 178
 
1.5%
도시교통실 178
 
1.5%
주택정책실 177
 
1.5%
Other values (198) 9366
77.2%
2024-05-18T09:05:33.225520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6244
 
8.7%
4148
 
5.8%
3953
 
5.5%
3286
 
4.6%
3107
 
4.3%
3107
 
4.3%
2133
 
3.0%
1405
 
2.0%
1322
 
1.8%
1187
 
1.7%
Other values (200) 41595
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69090
96.6%
Space Separator 2133
 
3.0%
Decimal Number 194
 
0.3%
Uppercase Letter 70
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6244
 
9.0%
4148
 
6.0%
3953
 
5.7%
3286
 
4.8%
3107
 
4.5%
3107
 
4.5%
1405
 
2.0%
1322
 
1.9%
1187
 
1.7%
1146
 
1.7%
Other values (194) 40185
58.2%
Decimal Number
ValueCountFrequency (%)
1 142
73.2%
8 26
 
13.4%
3 26
 
13.4%
Uppercase Letter
ValueCountFrequency (%)
A 35
50.0%
I 35
50.0%
Space Separator
ValueCountFrequency (%)
2133
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 69090
96.6%
Common 2327
 
3.3%
Latin 70
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6244
 
9.0%
4148
 
6.0%
3953
 
5.7%
3286
 
4.8%
3107
 
4.5%
3107
 
4.5%
1405
 
2.0%
1322
 
1.9%
1187
 
1.7%
1146
 
1.7%
Other values (194) 40185
58.2%
Common
ValueCountFrequency (%)
2133
91.7%
1 142
 
6.1%
8 26
 
1.1%
3 26
 
1.1%
Latin
ValueCountFrequency (%)
A 35
50.0%
I 35
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 69090
96.6%
ASCII 2397
 
3.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6244
 
9.0%
4148
 
6.0%
3953
 
5.7%
3286
 
4.8%
3107
 
4.5%
3107
 
4.5%
1405
 
2.0%
1322
 
1.9%
1187
 
1.7%
1146
 
1.7%
Other values (194) 40185
58.2%
ASCII
ValueCountFrequency (%)
2133
89.0%
1 142
 
5.9%
A 35
 
1.5%
I 35
 
1.5%
8 26
 
1.1%
3 26
 
1.1%
Distinct246
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T09:05:34.164829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length12
Mean length11.44
Min length9

Characters and Unicode

Total characters114400
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row02-2133-6864
2nd row02-2133-2214
3rd row02-2133-5705
4th row02-2133-2705
5th row2133-35165
ValueCountFrequency (%)
02-2133-6412 379
 
3.8%
02-2133-5611 286
 
2.9%
02-2133-8016 268
 
2.7%
02-2133-6230 221
 
2.2%
02-2133-5265 189
 
1.9%
02-2133-5013 178
 
1.8%
02-2133-5218 146
 
1.5%
2133-3915 146
 
1.5%
02-2133-6617 126
 
1.3%
02-2133-2214 122
 
1.2%
Other values (236) 7939
79.4%
2024-05-18T09:05:35.571963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 23525
20.6%
2 22742
19.9%
- 18072
15.8%
1 15254
13.3%
0 10871
9.5%
5 5744
 
5.0%
6 5163
 
4.5%
4 3863
 
3.4%
8 3862
 
3.4%
7 3201
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 96328
84.2%
Dash Punctuation 18072
 
15.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 23525
24.4%
2 22742
23.6%
1 15254
15.8%
0 10871
11.3%
5 5744
 
6.0%
6 5163
 
5.4%
4 3863
 
4.0%
8 3862
 
4.0%
7 3201
 
3.3%
9 2103
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 18072
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 114400
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 23525
20.6%
2 22742
19.9%
- 18072
15.8%
1 15254
13.3%
0 10871
9.5%
5 5744
 
5.0%
6 5163
 
4.5%
4 3863
 
3.4%
8 3862
 
3.4%
7 3201
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 114400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 23525
20.6%
2 22742
19.9%
- 18072
15.8%
1 15254
13.3%
0 10871
9.5%
5 5744
 
5.0%
6 5163
 
4.5%
4 3863
 
3.4%
8 3862
 
3.4%
7 3201
 
2.8%
Distinct193
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T09:05:36.595184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.0759
Min length2

Characters and Unicode

Total characters30759
Distinct characters130
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st row김유나
2nd row최준혁
3rd row강한성
4th row서민주
5th row강현지
ValueCountFrequency (%)
김두영 477
 
4.7%
최원준 379
 
3.7%
박성규 268
 
2.6%
정상영 266
 
2.6%
나소정 189
 
1.8%
주무관 184
 
1.8%
천은진 178
 
1.7%
최준혁 177
 
1.7%
정다은 146
 
1.4%
최준호 146
 
1.4%
Other values (185) 7824
76.5%
2024-05-18T09:05:37.990836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1911
 
6.2%
1654
 
5.4%
1580
 
5.1%
1327
 
4.3%
1010
 
3.3%
932
 
3.0%
855
 
2.8%
849
 
2.8%
835
 
2.7%
773
 
2.5%
Other values (120) 19033
61.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30525
99.2%
Space Separator 234
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1911
 
6.3%
1654
 
5.4%
1580
 
5.2%
1327
 
4.3%
1010
 
3.3%
932
 
3.1%
855
 
2.8%
849
 
2.8%
835
 
2.7%
773
 
2.5%
Other values (119) 18799
61.6%
Space Separator
ValueCountFrequency (%)
234
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30525
99.2%
Common 234
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1911
 
6.3%
1654
 
5.4%
1580
 
5.2%
1327
 
4.3%
1010
 
3.3%
932
 
3.1%
855
 
2.8%
849
 
2.8%
835
 
2.7%
773
 
2.5%
Other values (119) 18799
61.6%
Common
ValueCountFrequency (%)
234
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30525
99.2%
ASCII 234
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1911
 
6.3%
1654
 
5.4%
1580
 
5.2%
1327
 
4.3%
1010
 
3.3%
932
 
3.1%
855
 
2.8%
849
 
2.8%
835
 
2.7%
773
 
2.5%
Other values (119) 18799
61.6%
ASCII
ValueCountFrequency (%)
234
100.0%
Distinct151
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-02-02 00:00:00
Maximum2024-04-08 00:00:00
2024-05-18T09:05:38.516133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:05:38.963093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

해당년도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023
9998 
2024
 
2

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2023 9998
> 99.9%
2024 2
 
< 0.1%

Length

2024-05-18T09:05:39.501128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:05:39.909451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 9998
> 99.9%
2024 2
 
< 0.1%

해당월
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.2479
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T09:05:40.226848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q18
median10
Q311
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.2468534
Coefficient of variation (CV)0.24295823
Kurtosis0.84904608
Mean9.2479
Median Absolute Deviation (MAD)2
Skewness-0.83575259
Sum92479
Variance5.0483504
MonotonicityNot monotonic
2024-05-18T09:05:40.610410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
12 1888
18.9%
11 1626
16.3%
8 1528
15.3%
10 1507
15.1%
9 1327
13.3%
7 1089
10.9%
6 626
 
6.3%
5 122
 
1.2%
4 87
 
0.9%
1 82
 
0.8%
Other values (2) 118
 
1.2%
ValueCountFrequency (%)
1 82
 
0.8%
2 73
 
0.7%
3 45
 
0.4%
4 87
 
0.9%
5 122
 
1.2%
6 626
6.3%
7 1089
10.9%
8 1528
15.3%
9 1327
13.3%
10 1507
15.1%
ValueCountFrequency (%)
12 1888
18.9%
11 1626
16.3%
10 1507
15.1%
9 1327
13.3%
8 1528
15.3%
7 1089
10.9%
6 626
 
6.3%
5 122
 
1.2%
4 87
 
0.9%
3 45
 
0.4%
Distinct1082
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T09:05:41.562305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length44
Mean length44
Min length44

Characters and Unicode

Total characters440000
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)0.4%

Sample

1st rowhttps://opengov.seoul.go.kr/expense/29224991
2nd rowhttps://opengov.seoul.go.kr/expense/29382074
3rd rowhttps://opengov.seoul.go.kr/expense/29369281
4th rowhttps://opengov.seoul.go.kr/expense/29196324
5th rowhttps://opengov.seoul.go.kr/expense/29822413
ValueCountFrequency (%)
https://opengov.seoul.go.kr/expense/29870441 111
 
1.1%
https://opengov.seoul.go.kr/expense/29656005 99
 
1.0%
https://opengov.seoul.go.kr/expense/30115434 95
 
0.9%
https://opengov.seoul.go.kr/expense/28823285 93
 
0.9%
https://opengov.seoul.go.kr/expense/29225070 89
 
0.9%
https://opengov.seoul.go.kr/expense/29406101 80
 
0.8%
https://opengov.seoul.go.kr/expense/29394605 46
 
0.5%
https://opengov.seoul.go.kr/expense/30072887 45
 
0.4%
https://opengov.seoul.go.kr/expense/29858221 45
 
0.4%
https://opengov.seoul.go.kr/expense/29223887 45
 
0.4%
Other values (1072) 9252
92.5%
2024-05-18T09:05:42.564848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 50000
 
11.4%
/ 40000
 
9.1%
o 40000
 
9.1%
p 30000
 
6.8%
s 30000
 
6.8%
. 30000
 
6.8%
n 20000
 
4.5%
g 20000
 
4.5%
t 20000
 
4.5%
2 14292
 
3.2%
Other values (17) 145708
33.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 280000
63.6%
Other Punctuation 80000
 
18.2%
Decimal Number 80000
 
18.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 50000
17.9%
o 40000
14.3%
p 30000
10.7%
s 30000
10.7%
n 20000
 
7.1%
g 20000
 
7.1%
t 20000
 
7.1%
h 10000
 
3.6%
r 10000
 
3.6%
x 10000
 
3.6%
Other values (4) 40000
14.3%
Decimal Number
ValueCountFrequency (%)
2 14292
17.9%
9 12371
15.5%
0 8932
11.2%
8 8182
10.2%
3 7351
9.2%
1 6412
8.0%
6 6372
8.0%
4 5948
7.4%
5 5418
 
6.8%
7 4722
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/ 40000
50.0%
. 30000
37.5%
: 10000
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 280000
63.6%
Common 160000
36.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 50000
17.9%
o 40000
14.3%
p 30000
10.7%
s 30000
10.7%
n 20000
 
7.1%
g 20000
 
7.1%
t 20000
 
7.1%
h 10000
 
3.6%
r 10000
 
3.6%
x 10000
 
3.6%
Other values (4) 40000
14.3%
Common
ValueCountFrequency (%)
/ 40000
25.0%
. 30000
18.8%
2 14292
 
8.9%
9 12371
 
7.7%
: 10000
 
6.2%
0 8932
 
5.6%
8 8182
 
5.1%
3 7351
 
4.6%
1 6412
 
4.0%
6 6372
 
4.0%
Other values (3) 16088
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 440000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 50000
 
11.4%
/ 40000
 
9.1%
o 40000
 
9.1%
p 30000
 
6.8%
s 30000
 
6.8%
. 30000
 
6.8%
n 20000
 
4.5%
g 20000
 
4.5%
t 20000
 
4.5%
2 14292
 
3.2%
Other values (17) 145708
33.1%

구분(시장실만 사용)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9898 
시정 관련 간담회 등
 
58
현업-우수부서 격려 등
 
44

Length

Max length12
Median length4
Mean length4.0758
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9898
99.0%
시정 관련 간담회 등 58
 
0.6%
현업-우수부서 격려 등 44
 
0.4%

Length

2024-05-18T09:05:42.919098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:05:43.296646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9898
96.5%
102
 
1.0%
시정 58
 
0.6%
관련 58
 
0.6%
간담회 58
 
0.6%
현업-우수부서 44
 
0.4%
격려 44
 
0.4%
Distinct189
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T09:05:43.787040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length11.9654
Min length5

Characters and Unicode

Total characters119654
Distinct characters217
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st row기획조정실 재정담당관
2nd row도시교통실 교통정책과
3rd row행정국 인사과
4th row디자인정책관 디자인정책담당관
5th row여성가족정책실 아동담당관
ValueCountFrequency (%)
행정국 935
 
4.8%
경제정책실 677
 
3.5%
기획조정실 610
 
3.1%
총무과 570
 
2.9%
도시교통실 503
 
2.6%
재난안전관리실 395
 
2.0%
기후환경본부 393
 
2.0%
여성가족정책실 360
 
1.9%
시민건강국 352
 
1.8%
주택정책실 343
 
1.8%
Other values (207) 14318
73.6%
2024-05-18T09:05:44.848711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9591
 
8.0%
7713
 
6.4%
6210
 
5.2%
5648
 
4.7%
4967
 
4.2%
3703
 
3.1%
2905
 
2.4%
2905
 
2.4%
2890
 
2.4%
2622
 
2.2%
Other values (207) 70500
58.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 109298
91.3%
Space Separator 9591
 
8.0%
Decimal Number 325
 
0.3%
Other Punctuation 184
 
0.2%
Uppercase Letter 92
 
0.1%
Close Punctuation 82
 
0.1%
Open Punctuation 82
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7713
 
7.1%
6210
 
5.7%
5648
 
5.2%
4967
 
4.5%
3703
 
3.4%
2905
 
2.7%
2905
 
2.7%
2890
 
2.6%
2622
 
2.4%
2618
 
2.4%
Other values (197) 67117
61.4%
Decimal Number
ValueCountFrequency (%)
1 142
43.7%
2 130
40.0%
3 27
 
8.3%
8 26
 
8.0%
Uppercase Letter
ValueCountFrequency (%)
I 46
50.0%
A 46
50.0%
Space Separator
ValueCountFrequency (%)
9591
100.0%
Other Punctuation
ValueCountFrequency (%)
? 184
100.0%
Close Punctuation
ValueCountFrequency (%)
) 82
100.0%
Open Punctuation
ValueCountFrequency (%)
( 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 109298
91.3%
Common 10264
 
8.6%
Latin 92
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7713
 
7.1%
6210
 
5.7%
5648
 
5.2%
4967
 
4.5%
3703
 
3.4%
2905
 
2.7%
2905
 
2.7%
2890
 
2.6%
2622
 
2.4%
2618
 
2.4%
Other values (197) 67117
61.4%
Common
ValueCountFrequency (%)
9591
93.4%
? 184
 
1.8%
1 142
 
1.4%
2 130
 
1.3%
) 82
 
0.8%
( 82
 
0.8%
3 27
 
0.3%
8 26
 
0.3%
Latin
ValueCountFrequency (%)
I 46
50.0%
A 46
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 109298
91.3%
ASCII 10356
 
8.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9591
92.6%
? 184
 
1.8%
1 142
 
1.4%
2 130
 
1.3%
) 82
 
0.8%
( 82
 
0.8%
I 46
 
0.4%
A 46
 
0.4%
3 27
 
0.3%
8 26
 
0.3%
Hangul
ValueCountFrequency (%)
7713
 
7.1%
6210
 
5.7%
5648
 
5.2%
4967
 
4.5%
3703
 
3.4%
2905
 
2.7%
2905
 
2.7%
2890
 
2.6%
2622
 
2.4%
2618
 
2.4%
Other values (197) 67117
61.4%
Distinct8641
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1970-01-01 09:00:00
Maximum2024-03-20 14:58:00
2024-05-18T09:05:45.263575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:05:45.745779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct5567
Distinct (%)55.9%
Missing40
Missing (%)0.4%
Memory size156.2 KiB
2024-05-18T09:05:46.370859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length50
Mean length22.435542
Min length1

Characters and Unicode

Total characters223458
Distinct characters790
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3983 ?
Unique (%)40.0%

Sample

1st row초류향(서울 중구 다동길 24-10)
2nd row더샌드위치샵(서울특별시 중구 서소문로 115)
3rd row담솥서울시청점(서울 중구 무교로 13)
4th row창고43(중구 덕수궁길 7)
5th row정동집(중구 정동길 41-3)
ValueCountFrequency (%)
중구 4592
 
11.6%
세종대로 1401
 
3.5%
서소문로 1232
 
3.1%
무교로 879
 
2.2%
136 446
 
1.1%
124 421
 
1.1%
주식회사 391
 
1.0%
남대문로9길 382
 
1.0%
종로구 360
 
0.9%
덕수궁길 311
 
0.8%
Other values (6083) 29188
73.7%
2024-05-18T09:05:47.674630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30243
 
13.5%
( 10356
 
4.6%
) 10333
 
4.6%
9794
 
4.4%
9363
 
4.2%
1 9003
 
4.0%
8115
 
3.6%
7644
 
3.4%
5564
 
2.5%
2 4696
 
2.1%
Other values (780) 118347
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 138098
61.8%
Space Separator 30243
 
13.5%
Decimal Number 29389
 
13.2%
Open Punctuation 10357
 
4.6%
Close Punctuation 10334
 
4.6%
Dash Punctuation 1811
 
0.8%
Uppercase Letter 1601
 
0.7%
Other Punctuation 807
 
0.4%
Lowercase Letter 640
 
0.3%
Other Symbol 162
 
0.1%
Other values (2) 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9794
 
7.1%
9363
 
6.8%
8115
 
5.9%
7644
 
5.5%
5564
 
4.0%
4425
 
3.2%
4235
 
3.1%
4184
 
3.0%
3676
 
2.7%
3364
 
2.4%
Other values (702) 77734
56.3%
Uppercase Letter
ValueCountFrequency (%)
C 200
12.5%
A 152
 
9.5%
S 124
 
7.7%
F 114
 
7.1%
I 103
 
6.4%
R 102
 
6.4%
N 101
 
6.3%
B 88
 
5.5%
L 85
 
5.3%
E 82
 
5.1%
Other values (15) 450
28.1%
Lowercase Letter
ValueCountFrequency (%)
i 80
12.5%
a 80
12.5%
e 74
11.6%
h 59
9.2%
s 48
 
7.5%
c 40
 
6.2%
f 37
 
5.8%
o 34
 
5.3%
r 31
 
4.8%
t 26
 
4.1%
Other values (14) 131
20.5%
Decimal Number
ValueCountFrequency (%)
1 9003
30.6%
2 4696
16.0%
3 3139
 
10.7%
4 2672
 
9.1%
6 2086
 
7.1%
0 1955
 
6.7%
9 1841
 
6.3%
5 1516
 
5.2%
7 1385
 
4.7%
8 1096
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 707
87.6%
& 29
 
3.6%
/ 29
 
3.6%
. 22
 
2.7%
! 8
 
1.0%
? 4
 
0.5%
' 4
 
0.5%
2
 
0.2%
* 1
 
0.1%
: 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 10356
> 99.9%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 10333
> 99.9%
] 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
30243
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1811
100.0%
Other Symbol
ValueCountFrequency (%)
162
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 138250
61.9%
Common 82957
37.1%
Latin 2241
 
1.0%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9794
 
7.1%
9363
 
6.8%
8115
 
5.9%
7644
 
5.5%
5564
 
4.0%
4425
 
3.2%
4235
 
3.1%
4184
 
3.0%
3676
 
2.7%
3364
 
2.4%
Other values (700) 77886
56.3%
Latin
ValueCountFrequency (%)
C 200
 
8.9%
A 152
 
6.8%
S 124
 
5.5%
F 114
 
5.1%
I 103
 
4.6%
R 102
 
4.6%
N 101
 
4.5%
B 88
 
3.9%
L 85
 
3.8%
E 82
 
3.7%
Other values (39) 1090
48.6%
Common
ValueCountFrequency (%)
30243
36.5%
( 10356
 
12.5%
) 10333
 
12.5%
1 9003
 
10.9%
2 4696
 
5.7%
3 3139
 
3.8%
4 2672
 
3.2%
6 2086
 
2.5%
0 1955
 
2.4%
9 1841
 
2.2%
Other values (18) 6633
 
8.0%
Han
ValueCountFrequency (%)
4
40.0%
4
40.0%
2
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 138087
61.8%
ASCII 85196
38.1%
None 164
 
0.1%
CJK 10
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30243
35.5%
( 10356
 
12.2%
) 10333
 
12.1%
1 9003
 
10.6%
2 4696
 
5.5%
3 3139
 
3.7%
4 2672
 
3.1%
6 2086
 
2.4%
0 1955
 
2.3%
9 1841
 
2.2%
Other values (66) 8872
 
10.4%
Hangul
ValueCountFrequency (%)
9794
 
7.1%
9363
 
6.8%
8115
 
5.9%
7644
 
5.5%
5564
 
4.0%
4425
 
3.2%
4235
 
3.1%
4184
 
3.0%
3676
 
2.7%
3364
 
2.4%
Other values (698) 77723
56.3%
None
ValueCountFrequency (%)
162
98.8%
2
 
1.2%
CJK
ValueCountFrequency (%)
4
40.0%
4
40.0%
2
20.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Distinct8030
Distinct (%)80.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T09:05:48.599464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length50
Mean length24.22
Min length6

Characters and Unicode

Total characters242200
Distinct characters761
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7252 ?
Unique (%)72.5%

Sample

1st row지방재정분석 현지 실사 관련 간담회비 지급
2nd row부서 현안업무 추진직원 간식 구매 비용 지급
3rd row찾아가는 인사상담 관련 간담회비 지급
4th rowDDP 유구전시장 디자인 명소화 추진 관련 간담회 비용 지급
5th row인생버디 100인 멘토단 운영을 위한 간담회
ValueCountFrequency (%)
간담회 5624
 
9.2%
관련 5146
 
8.4%
지급 4314
 
7.0%
비용 2783
 
4.5%
추진 1320
 
2.2%
간담회비 1255
 
2.0%
직원 1115
 
1.8%
격려 1035
 
1.7%
검토 821
 
1.3%
위한 821
 
1.3%
Other values (8764) 37095
60.5%
2024-05-18T09:05:50.060509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
51372
 
21.2%
8787
 
3.6%
7631
 
3.2%
7226
 
3.0%
7194
 
3.0%
7023
 
2.9%
6419
 
2.7%
5453
 
2.3%
5252
 
2.2%
4376
 
1.8%
Other values (751) 131467
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 179433
74.1%
Space Separator 51372
 
21.2%
Decimal Number 6300
 
2.6%
Other Punctuation 1697
 
0.7%
Close Punctuation 1241
 
0.5%
Open Punctuation 1241
 
0.5%
Uppercase Letter 738
 
0.3%
Lowercase Letter 103
 
< 0.1%
Dash Punctuation 47
 
< 0.1%
Math Symbol 19
 
< 0.1%
Other values (4) 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8787
 
4.9%
7631
 
4.3%
7226
 
4.0%
7194
 
4.0%
7023
 
3.9%
6419
 
3.6%
5453
 
3.0%
5252
 
2.9%
4376
 
2.4%
3386
 
1.9%
Other values (670) 116686
65.0%
Uppercase Letter
ValueCountFrequency (%)
C 71
 
9.6%
S 71
 
9.6%
A 61
 
8.3%
T 59
 
8.0%
I 56
 
7.6%
M 56
 
7.6%
D 54
 
7.3%
P 50
 
6.8%
E 42
 
5.7%
G 39
 
5.3%
Other values (15) 179
24.3%
Lowercase Letter
ValueCountFrequency (%)
a 12
11.7%
r 11
10.7%
o 10
 
9.7%
e 10
 
9.7%
t 8
 
7.8%
s 7
 
6.8%
n 6
 
5.8%
p 5
 
4.9%
i 5
 
4.9%
y 4
 
3.9%
Other values (13) 25
24.3%
Decimal Number
ValueCountFrequency (%)
2 2108
33.5%
1 1145
18.2%
0 906
14.4%
3 727
 
11.5%
4 378
 
6.0%
8 252
 
4.0%
7 236
 
3.7%
9 231
 
3.7%
6 184
 
2.9%
5 133
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 1485
87.5%
, 84
 
4.9%
? 83
 
4.9%
' 37
 
2.2%
/ 4
 
0.2%
: 3
 
0.2%
* 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1204
97.0%
] 28
 
2.3%
8
 
0.6%
1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1204
97.0%
[ 28
 
2.3%
8
 
0.6%
1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 15
78.9%
+ 4
 
21.1%
Space Separator
ValueCountFrequency (%)
51372
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%
Final Punctuation
ValueCountFrequency (%)
5
100.0%
Initial Punctuation
ValueCountFrequency (%)
2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 179431
74.1%
Common 61926
 
25.6%
Latin 841
 
0.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8787
 
4.9%
7631
 
4.3%
7226
 
4.0%
7194
 
4.0%
7023
 
3.9%
6419
 
3.6%
5453
 
3.0%
5252
 
2.9%
4376
 
2.4%
3386
 
1.9%
Other values (668) 116684
65.0%
Latin
ValueCountFrequency (%)
C 71
 
8.4%
S 71
 
8.4%
A 61
 
7.3%
T 59
 
7.0%
I 56
 
6.7%
M 56
 
6.7%
D 54
 
6.4%
P 50
 
5.9%
E 42
 
5.0%
G 39
 
4.6%
Other values (38) 282
33.5%
Common
ValueCountFrequency (%)
51372
83.0%
2 2108
 
3.4%
. 1485
 
2.4%
) 1204
 
1.9%
( 1204
 
1.9%
1 1145
 
1.8%
0 906
 
1.5%
3 727
 
1.2%
4 378
 
0.6%
8 252
 
0.4%
Other values (23) 1145
 
1.8%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 179431
74.1%
ASCII 62742
 
25.9%
None 18
 
< 0.1%
Punctuation 7
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
51372
81.9%
2 2108
 
3.4%
. 1485
 
2.4%
) 1204
 
1.9%
( 1204
 
1.9%
1 1145
 
1.8%
0 906
 
1.4%
3 727
 
1.2%
4 378
 
0.6%
8 252
 
0.4%
Other values (65) 1961
 
3.1%
Hangul
ValueCountFrequency (%)
8787
 
4.9%
7631
 
4.3%
7226
 
4.0%
7194
 
4.0%
7023
 
3.9%
6419
 
3.6%
5453
 
3.0%
5252
 
2.9%
4376
 
2.4%
3386
 
1.9%
Other values (668) 116684
65.0%
None
ValueCountFrequency (%)
8
44.4%
8
44.4%
1
 
5.6%
1
 
5.6%
Punctuation
ValueCountFrequency (%)
5
71.4%
2
 
28.6%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct4023
Distinct (%)40.4%
Missing39
Missing (%)0.4%
Memory size156.2 KiB
2024-05-18T09:05:50.705459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length38
Mean length12.016866
Min length2

Characters and Unicode

Total characters119700
Distinct characters384
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2221 ?
Unique (%)22.3%

Sample

1st row재정총괄팀장 외 7명
2nd row교통정책과 직원 등 41명
3rd row기술인사팀장 등 6명
4th row디자인정책담당관 외 2명
5th row아동정책팀장 외 2명
ValueCountFrequency (%)
4309
 
14.2%
4122
 
13.6%
4명 1503
 
4.9%
3명 1358
 
4.5%
5명 1120
 
3.7%
6명 978
 
3.2%
2명 779
 
2.6%
직원 702
 
2.3%
7명 541
 
1.8%
8명 456
 
1.5%
Other values (1571) 14513
47.8%
2024-05-18T09:05:52.097975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20459
 
17.1%
8691
 
7.3%
6481
 
5.4%
4717
 
3.9%
4399
 
3.7%
3703
 
3.1%
3296
 
2.8%
3118
 
2.6%
2034
 
1.7%
4 1913
 
1.6%
Other values (374) 60889
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 87047
72.7%
Space Separator 20459
 
17.1%
Decimal Number 11273
 
9.4%
Other Punctuation 370
 
0.3%
Open Punctuation 225
 
0.2%
Close Punctuation 225
 
0.2%
Uppercase Letter 96
 
0.1%
Other Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8691
 
10.0%
6481
 
7.4%
4717
 
5.4%
4399
 
5.1%
3703
 
4.3%
3296
 
3.8%
3118
 
3.6%
2034
 
2.3%
1670
 
1.9%
1622
 
1.9%
Other values (345) 47316
54.4%
Uppercase Letter
ValueCountFrequency (%)
I 40
41.7%
A 39
40.6%
B 5
 
5.2%
C 4
 
4.2%
T 2
 
2.1%
R 1
 
1.0%
E 1
 
1.0%
P 1
 
1.0%
U 1
 
1.0%
M 1
 
1.0%
Decimal Number
ValueCountFrequency (%)
4 1913
17.0%
3 1882
16.7%
1 1450
12.9%
5 1420
12.6%
2 1411
12.5%
6 1153
10.2%
7 672
 
6.0%
8 633
 
5.6%
0 417
 
3.7%
9 322
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 356
96.2%
? 9
 
2.4%
. 4
 
1.1%
: 1
 
0.3%
Space Separator
ValueCountFrequency (%)
20459
100.0%
Open Punctuation
ValueCountFrequency (%)
( 225
100.0%
Close Punctuation
ValueCountFrequency (%)
) 225
100.0%
Other Symbol
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 87047
72.7%
Common 32557
 
27.2%
Latin 96
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8691
 
10.0%
6481
 
7.4%
4717
 
5.4%
4399
 
5.1%
3703
 
4.3%
3296
 
3.8%
3118
 
3.6%
2034
 
2.3%
1670
 
1.9%
1622
 
1.9%
Other values (345) 47316
54.4%
Common
ValueCountFrequency (%)
20459
62.8%
4 1913
 
5.9%
3 1882
 
5.8%
1 1450
 
4.5%
5 1420
 
4.4%
2 1411
 
4.3%
6 1153
 
3.5%
7 672
 
2.1%
8 633
 
1.9%
0 417
 
1.3%
Other values (8) 1147
 
3.5%
Latin
ValueCountFrequency (%)
I 40
41.7%
A 39
40.6%
B 5
 
5.2%
C 4
 
4.2%
T 2
 
2.1%
R 1
 
1.0%
E 1
 
1.0%
P 1
 
1.0%
U 1
 
1.0%
M 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 87028
72.7%
ASCII 32648
 
27.3%
Compat Jamo 19
 
< 0.1%
Geometric Shapes 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20459
62.7%
4 1913
 
5.9%
3 1882
 
5.8%
1 1450
 
4.4%
5 1420
 
4.3%
2 1411
 
4.3%
6 1153
 
3.5%
7 672
 
2.1%
8 633
 
1.9%
0 417
 
1.3%
Other values (18) 1238
 
3.8%
Hangul
ValueCountFrequency (%)
8691
 
10.0%
6481
 
7.4%
4717
 
5.4%
4399
 
5.1%
3703
 
4.3%
3296
 
3.8%
3118
 
3.6%
2034
 
2.3%
1670
 
1.9%
1622
 
1.9%
Other values (344) 47297
54.3%
Compat Jamo
ValueCountFrequency (%)
19
100.0%
Geometric Shapes
ValueCountFrequency (%)
5
100.0%

결제방법
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
카드
7347 
제로페이
2577 
현금
 
76

Length

Max length4
Median length2
Mean length2.5154
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row카드
2nd row카드
3rd row제로페이
4th row카드
5th row제로페이

Common Values

ValueCountFrequency (%)
카드 7347
73.5%
제로페이 2577
 
25.8%
현금 76
 
0.8%

Length

2024-05-18T09:05:52.623601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:05:52.987699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
카드 7347
73.5%
제로페이 2577
 
25.8%
현금 76
 
0.8%

집행금액
Real number (ℝ)

SKEWED 

Distinct1699
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126868.63
Minimum0
Maximum9632000
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T09:05:53.525746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile24000
Q155000
median90000
Q3150000
95-th percentile338300
Maximum9632000
Range9632000
Interquartile range (IQR)95000

Descriptive statistics

Standard deviation209875.99
Coefficient of variation (CV)1.654278
Kurtosis1033.377
Mean126868.63
Median Absolute Deviation (MAD)42000
Skewness26.710737
Sum1.2686863 × 109
Variance4.4047933 × 1010
MonotonicityNot monotonic
2024-05-18T09:05:54.088919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60000 152
 
1.5%
50000 149
 
1.5%
100000 145
 
1.5%
90000 125
 
1.2%
80000 125
 
1.2%
150000 116
 
1.2%
72000 90
 
0.9%
36000 90
 
0.9%
120000 89
 
0.9%
84000 86
 
0.9%
Other values (1689) 8833
88.3%
ValueCountFrequency (%)
0 1
< 0.1%
2500 1
< 0.1%
3000 1
< 0.1%
3700 1
< 0.1%
3760 1
< 0.1%
3800 1
< 0.1%
4000 2
< 0.1%
4100 1
< 0.1%
4200 1
< 0.1%
4800 2
< 0.1%
ValueCountFrequency (%)
9632000 1
< 0.1%
9355500 1
< 0.1%
7310000 1
< 0.1%
6248000 1
< 0.1%
3622300 1
< 0.1%
3528000 1
< 0.1%
3362000 1
< 0.1%
3000000 2
< 0.1%
2500000 1
< 0.1%
2057000 1
< 0.1%

비목
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
시책
7551 
부서
1218 
기관
1135 
정원
 
96

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시책
2nd row부서
3rd row시책
4th row시책
5th row부서

Common Values

ValueCountFrequency (%)
시책 7551
75.5%
부서 1218
 
12.2%
기관 1135
 
11.3%
정원 96
 
1.0%

Length

2024-05-18T09:05:54.738354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:05:55.125890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시책 7551
75.5%
부서 1218
 
12.2%
기관 1135
 
11.3%
정원 96
 
1.0%

Interactions

2024-05-18T09:05:25.116712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:05:23.563930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:05:24.342376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:05:25.386975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:05:23.833626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:05:24.618806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:05:25.656265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:05:24.051413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:05:24.879723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T09:05:55.472043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
문서고유id해당년도해당월구분(시장실만 사용)결제방법집행금액비목
문서고유id1.0000.8740.9850.1220.1100.0000.076
해당년도0.8741.0000.150NaN0.0480.0000.054
해당월0.9850.1501.0000.0000.1130.0000.078
구분(시장실만 사용)0.122NaN0.0001.0000.1720.4721.000
결제방법0.1100.0480.1130.1721.0000.2390.186
집행금액0.0000.0000.0000.4720.2391.0000.093
비목0.0760.0540.0781.0000.1860.0931.000
2024-05-18T09:05:55.868032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분(시장실만 사용)비목결제방법해당년도
구분(시장실만 사용)1.0000.9950.2821.000
비목0.9951.0000.1760.036
결제방법0.2820.1761.0000.079
해당년도1.0000.0360.0791.000
2024-05-18T09:05:56.438856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
문서고유id해당월집행금액해당년도구분(시장실만 사용)결제방법비목
문서고유id1.0000.9830.0770.7080.0830.0670.046
해당월0.9831.0000.0770.1150.0000.0670.047
집행금액0.0770.0771.0000.0000.3330.1640.064
해당년도0.7080.1150.0001.0001.0000.0790.036
구분(시장실만 사용)0.0830.0000.3331.0001.0000.2820.995
결제방법0.0670.0670.1640.0790.2821.0000.176
비목0.0460.0470.0640.0360.9950.1761.000

Missing values

2024-05-18T09:05:26.091004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T09:05:27.090447image/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.
2024-05-18T09:05:27.573831image/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

문서고유id제목부서명전화번호작성자등록일해당년도해당월문서url구분(시장실만 사용)전체부서명집행일시집행장소집행목적집행대상결제방법집행금액비목
15916292249912023년 8월 서울시본청 기획조정실 재정기획관 재정담당관 업무추진비 - 시책추진 부서운영재정담당관02-2133-6864김유나2023-09-0820238https://opengov.seoul.go.kr/expense/29224991<NA>기획조정실 재정담당관2023-08-25 12:34초류향(서울 중구 다동길 24-10)지방재정분석 현지 실사 관련 간담회비 지급재정총괄팀장 외 7명카드136000시책
12611293820742023년 9월 서울시본청 도시교통실 교통기획관 교통정책과 업무추진비 - 기관운영 시책추진 부서운영도시교통실 교통정책과02-2133-2214최준혁2023-10-0520239https://opengov.seoul.go.kr/expense/29382074<NA>도시교통실 교통정책과2023-09-27 09:06더샌드위치샵(서울특별시 중구 서소문로 115)부서 현안업무 추진직원 간식 구매 비용 지급교통정책과 직원 등 41명카드150000부서
8455293692812023년 9월 서울시본청 행정국 인사과 업무추진비 - 시책추진 부서운영인사과02-2133-5705강한성2023-10-0420239https://opengov.seoul.go.kr/expense/29369281<NA>행정국 인사과2023-09-15 19:18담솥서울시청점(서울 중구 무교로 13)찾아가는 인사상담 관련 간담회비 지급기술인사팀장 등 6명제로페이83000시책
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문서고유id제목부서명전화번호작성자등록일해당년도해당월문서url구분(시장실만 사용)전체부서명집행일시집행장소집행목적집행대상결제방법집행금액비목
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19950296467522023년 10월 서울시본청 기획조정실 정책기획관 기획담당관 업무추진비 - 기관운영 시책추진기획담당관02-2133-6617정희수2023-11-09202310https://opengov.seoul.go.kr/expense/29646752<NA>기획조정실 기획담당관2023-10-20 12:43롯데쇼핑㈜ (서울 중구 소공동)국정감사 관련 현안업무 추진 직원 격려 다과 구입비 지급기획담당관 등 40명카드75100시책
20868290382772023년 7월 서울시본청 경제정책실 경제일자리기획관 경제정책과 업무추진비 - 기관운영 시책추진경제정책실 경제일자리기획관 경제정책과02-2133-5218최준호 주무관2023-08-1020237https://opengov.seoul.go.kr/expense/29038277<NA>경제정책실 경제정책과2023-07-13 22:24디스트릭트 엠(서울특별시 중구 삼일대로 343)수서 로봇 클러스터 조성 관련 간담회 비용 지급경제정책실장 등 8명카드230000시책
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6312298029652023년 11월 서울시본청 문화본부 문화재관리과 업무추진비 - 시책추진 부서운영문화재관리과02-2133-2654조하영2023-12-01202311https://opengov.seoul.go.kr/expense/29802965<NA>문화본부 문화재관리과2023-11-10 12:34오복수산참치 광화문점(중구 무교로 21)신규 직원 격려 간담회문화재관리과장 등 7인카드153000시책
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894301154132023년 12월 서울시본청 재난안전관리실 안전총괄관 재난안전예방과 업무추진비 - 기관운영 시책추진 부서운영재난안전관리실 재난안전예방과02-2133-8522심정흠2024-01-10202312https://opengov.seoul.go.kr/expense/30115413<NA>재난안전관리실 재난안전예방과2023-12-20 12:08서울삼계탕(서울 중구 태평로2가)한파 등 현안업무 추진 직원 격려 비용 지급6명(재난안전예방과장 외5)카드108000부서