Overview

Dataset statistics

Number of variables20
Number of observations10000
Missing cells119592
Missing cells (%)59.8%
Duplicate rows55
Duplicate rows (%)0.5%
Total size in memory1.6 MiB
Average record size in memory169.0 B

Variable types

Numeric1
DateTime5
Unsupported1
Boolean1
Text12

Dataset

Description23~25 공공데이터 중장기 개방계획에 의한 생활민원처리시스템 DB개방자료로서 발송이력정보,생활민원처리정보,이관정보,협조부서정보 등의 테이블을 합성하여 개방함
Author충청남도 아산시
URLhttps://www.data.go.kr/data/15122610/fileData.do

Alerts

Dataset has 55 (0.5%) duplicate rowsDuplicates
이관요청일시 has 5612 (56.1%) missing valuesMissing
알림예약일시 has 9535 (95.3%) missing valuesMissing
배정자부서명 has 8754 (87.5%) missing valuesMissing
배정자팀명 has 8764 (87.6%) missing valuesMissing
이관처리부서명 has 5621 (56.2%) missing valuesMissing
이관처리팀명 has 5628 (56.3%) missing valuesMissing
이관시의견 has 7862 (78.6%) missing valuesMissing
이관부서명 has 7852 (78.5%) missing valuesMissing
협조요청일시 has 9982 (99.8%) missing valuesMissing
협조부서명 has 9982 (99.8%) missing valuesMissing
협조상위부서명 has 9991 (99.9%) missing valuesMissing
협조팀명 has 9982 (99.8%) missing valuesMissing
중장기연장처리예정일 has 9996 (> 99.9%) missing valuesMissing
중장기연장처리사유 has 9996 (> 99.9%) missing valuesMissing
발송일시 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 13:10:08.038180
Analysis finished2023-12-12 13:10:10.988127
Duration2.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

생활민원번호
Real number (ℝ)

Distinct9112
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0193706 × 1010
Minimum2.0180427 × 1010
Maximum2.0210324 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:10:11.058770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0180427 × 1010
5-th percentile2.0180621 × 1010
Q12.0190122 × 1010
median2.0191014 × 1010
Q32.020081 × 1010
95-th percentile2.0210218 × 1010
Maximum2.0210324 × 1010
Range29897058
Interquartile range (IQR)10688042

Descriptive statistics

Standard deviation9336613.5
Coefficient of variation (CV)0.00046235264
Kurtosis-1.0194383
Mean2.0193706 × 1010
Median Absolute Deviation (MAD)9790014
Skewness0.072924121
Sum2.0193706 × 1014
Variance8.7172353 × 1013
MonotonicityNot monotonic
2023-12-12T22:10:11.239875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190420004 5
 
0.1%
20190522006 4
 
< 0.1%
20180802023 4
 
< 0.1%
20190719010 4
 
< 0.1%
20210304044 4
 
< 0.1%
20200731065 4
 
< 0.1%
20190909089 4
 
< 0.1%
20200622040 3
 
< 0.1%
20190909001 3
 
< 0.1%
20180801021 3
 
< 0.1%
Other values (9102) 9962
99.6%
ValueCountFrequency (%)
20180427020 1
< 0.1%
20180428011 1
< 0.1%
20180428016 1
< 0.1%
20180429012 1
< 0.1%
20180430004 1
< 0.1%
20180430018 1
< 0.1%
20180430020 1
< 0.1%
20180430034 1
< 0.1%
20180502025 1
< 0.1%
20180503017 1
< 0.1%
ValueCountFrequency (%)
20210324078 1
< 0.1%
20210324075 1
< 0.1%
20210324072 1
< 0.1%
20210324071 1
< 0.1%
20210324069 1
< 0.1%
20210324068 1
< 0.1%
20210324064 2
< 0.1%
20210324058 1
< 0.1%
20210324041 1
< 0.1%
20210324033 2
< 0.1%
Distinct8732
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-05-07 13:12:00
Maximum2021-05-20 17:42:00
2023-12-12T22:10:11.398064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:11.527024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

발송일시
Unsupported

REJECTED  UNSUPPORTED 

Missing16
Missing (%)0.2%
Memory size156.2 KiB
Distinct2
Distinct (%)< 0.1%
Missing19
Missing (%)0.2%
Memory size97.7 KiB
True
5014 
False
4967 
(Missing)
 
19
ValueCountFrequency (%)
True 5014
50.1%
False 4967
49.7%
(Missing) 19
 
0.2%
2023-12-12T22:10:11.651970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Distinct3896
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T22:10:11.959321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length8.6765
Min length1

Characters and Unicode

Total characters86765
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3002 ?
Unique (%)30.0%

Sample

1st row2018-09-27 11:30
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
10:00 589
 
5.8%
14:00 532
 
5.2%
15:00 399
 
3.9%
09:00 355
 
3.5%
11:00 327
 
3.2%
16:00 280
 
2.7%
13:00 204
 
2.0%
17:00 181
 
1.8%
10:30 163
 
1.6%
15:30 141
 
1.4%
Other values (1022) 7064
69.0%
2023-12-12T22:10:12.398688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22590
26.0%
1 13090
15.1%
2 10406
12.0%
- 10230
11.8%
10000
11.5%
: 5125
 
5.9%
9 3280
 
3.8%
8 2735
 
3.2%
3 2618
 
3.0%
5 2082
 
2.4%
Other values (3) 4609
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61410
70.8%
Dash Punctuation 10230
 
11.8%
Space Separator 10000
 
11.5%
Other Punctuation 5125
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22590
36.8%
1 13090
21.3%
2 10406
16.9%
9 3280
 
5.3%
8 2735
 
4.5%
3 2618
 
4.3%
5 2082
 
3.4%
4 1785
 
2.9%
6 1451
 
2.4%
7 1373
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 10230
100.0%
Space Separator
ValueCountFrequency (%)
10000
100.0%
Other Punctuation
ValueCountFrequency (%)
: 5125
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 86765
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22590
26.0%
1 13090
15.1%
2 10406
12.0%
- 10230
11.8%
10000
11.5%
: 5125
 
5.9%
9 3280
 
3.8%
8 2735
 
3.2%
3 2618
 
3.0%
5 2082
 
2.4%
Other values (3) 4609
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 86765
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22590
26.0%
1 13090
15.1%
2 10406
12.0%
- 10230
11.8%
10000
11.5%
: 5125
 
5.9%
9 3280
 
3.8%
8 2735
 
3.2%
3 2618
 
3.0%
5 2082
 
2.4%
Other values (3) 4609
 
5.3%
Distinct8918
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T22:10:12.726010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length15.97
Min length1

Characters and Unicode

Total characters159700
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7947 ?
Unique (%)79.5%

Sample

1st row2018-09-28 17:40
2nd row2021-01-24 19:10
3rd row2021-01-27 17:21
4th row2020-11-30 09:08
5th row2019-01-21 11:44
ValueCountFrequency (%)
2020-08-10 52
 
0.3%
2020-08-11 50
 
0.3%
2020-08-18 46
 
0.2%
2020-08-12 42
 
0.2%
09:04 41
 
0.2%
2021-03-24 40
 
0.2%
2019-09-09 40
 
0.2%
09:06 40
 
0.2%
2019-09-02 37
 
0.2%
09:22 37
 
0.2%
Other values (1786) 19535
97.9%
2023-12-12T22:10:13.241995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 32122
20.1%
1 25697
16.1%
2 23193
14.5%
- 19960
12.5%
10000
 
6.3%
: 9980
 
6.2%
9 7893
 
4.9%
8 6803
 
4.3%
3 5779
 
3.6%
5 5081
 
3.2%
Other values (3) 13192
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 119760
75.0%
Dash Punctuation 19960
 
12.5%
Space Separator 10000
 
6.3%
Other Punctuation 9980
 
6.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 32122
26.8%
1 25697
21.5%
2 23193
19.4%
9 7893
 
6.6%
8 6803
 
5.7%
3 5779
 
4.8%
5 5081
 
4.2%
4 4687
 
3.9%
7 4426
 
3.7%
6 4079
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 19960
100.0%
Space Separator
ValueCountFrequency (%)
10000
100.0%
Other Punctuation
ValueCountFrequency (%)
: 9980
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 159700
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 32122
20.1%
1 25697
16.1%
2 23193
14.5%
- 19960
12.5%
10000
 
6.3%
: 9980
 
6.2%
9 7893
 
4.9%
8 6803
 
4.3%
3 5779
 
3.6%
5 5081
 
3.2%
Other values (3) 13192
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 159700
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 32122
20.1%
1 25697
16.1%
2 23193
14.5%
- 19960
12.5%
10000
 
6.3%
: 9980
 
6.2%
9 7893
 
4.9%
8 6803
 
4.3%
3 5779
 
3.6%
5 5081
 
3.2%
Other values (3) 13192
8.3%

이관요청일시
Date

MISSING 

Distinct3934
Distinct (%)89.7%
Missing5612
Missing (%)56.1%
Memory size156.2 KiB
Minimum2019-12-31 01:02:00
Maximum2021-03-25 16:57:00
2023-12-12T22:10:13.389297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:13.555817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

알림예약일시
Date

MISSING 

Distinct248
Distinct (%)53.3%
Missing9535
Missing (%)95.3%
Memory size156.2 KiB
Minimum2019-12-31 09:00:00
Maximum2021-03-25 09:05:00
2023-12-12T22:10:13.699960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:13.919674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

배정자부서명
Text

MISSING 

Distinct63
Distinct (%)5.1%
Missing8754
Missing (%)87.5%
Memory size156.2 KiB
2023-12-12T22:10:14.167764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.3908507
Min length3

Characters and Unicode

Total characters5471
Distinct characters120
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

Unique7 ?
Unique (%)0.6%

Sample

1st row민원봉사과
2nd row자치행정과
3rd row건축과
4th row위생과
5th row회계과
ValueCountFrequency (%)
민원봉사과 206
 
16.5%
도로과 75
 
6.0%
허가담당관 60
 
4.8%
환경보전과 59
 
4.7%
자원순환과 57
 
4.6%
교통행정과 51
 
4.1%
건설과 43
 
3.5%
건축과 42
 
3.4%
산림과 40
 
3.2%
주택과 37
 
3.0%
Other values (53) 576
46.2%
2023-12-12T22:10:14.897722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1096
 
20.0%
300
 
5.5%
243
 
4.4%
210
 
3.8%
206
 
3.8%
147
 
2.7%
128
 
2.3%
116
 
2.1%
113
 
2.1%
108
 
2.0%
Other values (110) 2804
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5460
99.8%
Decimal Number 11
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1096
 
20.1%
300
 
5.5%
243
 
4.5%
210
 
3.8%
206
 
3.8%
147
 
2.7%
128
 
2.3%
116
 
2.1%
113
 
2.1%
108
 
2.0%
Other values (105) 2793
51.2%
Decimal Number
ValueCountFrequency (%)
3 3
27.3%
5 3
27.3%
4 3
27.3%
6 1
 
9.1%
2 1
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5460
99.8%
Common 11
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1096
 
20.1%
300
 
5.5%
243
 
4.5%
210
 
3.8%
206
 
3.8%
147
 
2.7%
128
 
2.3%
116
 
2.1%
113
 
2.1%
108
 
2.0%
Other values (105) 2793
51.2%
Common
ValueCountFrequency (%)
3 3
27.3%
5 3
27.3%
4 3
27.3%
6 1
 
9.1%
2 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5460
99.8%
ASCII 11
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1096
 
20.1%
300
 
5.5%
243
 
4.5%
210
 
3.8%
206
 
3.8%
147
 
2.7%
128
 
2.3%
116
 
2.1%
113
 
2.1%
108
 
2.0%
Other values (105) 2793
51.2%
ASCII
ValueCountFrequency (%)
3 3
27.3%
5 3
27.3%
4 3
27.3%
6 1
 
9.1%
2 1
 
9.1%

배정자팀명
Text

MISSING 

Distinct165
Distinct (%)13.3%
Missing8764
Missing (%)87.6%
Memory size156.2 KiB
2023-12-12T22:10:15.231886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length5
Mean length5.1658576
Min length2

Characters and Unicode

Total characters6385
Distinct characters166
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

Unique23 ?
Unique (%)1.9%

Sample

1st row민원콜센터팀
2nd row대외협력팀
3rd row건축지도팀
4th row위생행정팀
5th row청렴계약팀
ValueCountFrequency (%)
민원콜센터팀 181
 
14.6%
건축지도팀 37
 
3.0%
청소행정팀 35
 
2.8%
도로관리팀 35
 
2.8%
산업개발팀 31
 
2.5%
환경지도팀 28
 
2.3%
민원행정팀 24
 
1.9%
주택개발팀 22
 
1.8%
위생지도팀 22
 
1.8%
하천관리팀 19
 
1.5%
Other values (155) 802
64.9%
2023-12-12T22:10:15.735901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1208
 
18.9%
253
 
4.0%
222
 
3.5%
219
 
3.4%
207
 
3.2%
185
 
2.9%
185
 
2.9%
182
 
2.9%
182
 
2.9%
181
 
2.8%
Other values (156) 3361
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6344
99.4%
Uppercase Letter 18
 
0.3%
Decimal Number 15
 
0.2%
Other Punctuation 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1208
 
19.0%
253
 
4.0%
222
 
3.5%
219
 
3.5%
207
 
3.3%
185
 
2.9%
185
 
2.9%
182
 
2.9%
182
 
2.9%
181
 
2.9%
Other values (151) 3320
52.3%
Decimal Number
ValueCountFrequency (%)
2 10
66.7%
1 5
33.3%
Uppercase Letter
ValueCountFrequency (%)
T 9
50.0%
F 9
50.0%
Other Punctuation
ValueCountFrequency (%)
/ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6344
99.4%
Common 23
 
0.4%
Latin 18
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1208
 
19.0%
253
 
4.0%
222
 
3.5%
219
 
3.5%
207
 
3.3%
185
 
2.9%
185
 
2.9%
182
 
2.9%
182
 
2.9%
181
 
2.9%
Other values (151) 3320
52.3%
Common
ValueCountFrequency (%)
2 10
43.5%
/ 8
34.8%
1 5
21.7%
Latin
ValueCountFrequency (%)
T 9
50.0%
F 9
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6344
99.4%
ASCII 41
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1208
 
19.0%
253
 
4.0%
222
 
3.5%
219
 
3.5%
207
 
3.3%
185
 
2.9%
185
 
2.9%
182
 
2.9%
182
 
2.9%
181
 
2.9%
Other values (151) 3320
52.3%
ASCII
ValueCountFrequency (%)
2 10
24.4%
T 9
22.0%
F 9
22.0%
/ 8
19.5%
1 5
12.2%

이관처리부서명
Text

MISSING 

Distinct67
Distinct (%)1.5%
Missing5621
Missing (%)56.2%
Memory size156.2 KiB
2023-12-12T22:10:16.023984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.3749715
Min length3

Characters and Unicode

Total characters19158
Distinct characters125
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

Unique5 ?
Unique (%)0.1%

Sample

1st row경로장애인과
2nd row기후변화대책과
3rd row대중교통과
4th row기후변화대책과
5th row배방읍
ValueCountFrequency (%)
도로과 645
 
14.7%
기후변화대책과 392
 
9.0%
자원순환과 347
 
7.9%
교통행정과 346
 
7.9%
대중교통과 267
 
6.1%
위생과 182
 
4.2%
환경보전과 165
 
3.8%
질병예방과 140
 
3.2%
상수도과 137
 
3.1%
배방읍 129
 
2.9%
Other values (57) 1629
37.2%
2023-12-12T22:10:16.502917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3788
 
19.8%
1037
 
5.4%
661
 
3.5%
659
 
3.4%
622
 
3.2%
617
 
3.2%
556
 
2.9%
512
 
2.7%
459
 
2.4%
445
 
2.3%
Other values (115) 9802
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19050
99.4%
Decimal Number 108
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3788
 
19.9%
1037
 
5.4%
661
 
3.5%
659
 
3.5%
622
 
3.3%
617
 
3.2%
556
 
2.9%
512
 
2.7%
459
 
2.4%
445
 
2.3%
Other values (109) 9694
50.9%
Decimal Number
ValueCountFrequency (%)
6 33
30.6%
5 25
23.1%
3 18
16.7%
2 13
 
12.0%
4 10
 
9.3%
1 9
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19050
99.4%
Common 108
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3788
 
19.9%
1037
 
5.4%
661
 
3.5%
659
 
3.5%
622
 
3.3%
617
 
3.2%
556
 
2.9%
512
 
2.7%
459
 
2.4%
445
 
2.3%
Other values (109) 9694
50.9%
Common
ValueCountFrequency (%)
6 33
30.6%
5 25
23.1%
3 18
16.7%
2 13
 
12.0%
4 10
 
9.3%
1 9
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19050
99.4%
ASCII 108
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3788
 
19.9%
1037
 
5.4%
661
 
3.5%
659
 
3.5%
622
 
3.3%
617
 
3.2%
556
 
2.9%
512
 
2.7%
459
 
2.4%
445
 
2.3%
Other values (109) 9694
50.9%
ASCII
ValueCountFrequency (%)
6 33
30.6%
5 25
23.1%
3 18
16.7%
2 13
 
12.0%
4 10
 
9.3%
1 9
 
8.3%

이관처리팀명
Text

MISSING 

Distinct164
Distinct (%)3.8%
Missing5628
Missing (%)56.3%
Memory size156.2 KiB
2023-12-12T22:10:16.849776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length5
Mean length5.023559
Min length2

Characters and Unicode

Total characters21963
Distinct characters170
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

Unique39 ?
Unique (%)0.9%

Sample

1st row경로복지팀
2nd row미세먼지대책팀
3rd row운수지도팀
4th row생활환경팀
5th row산업개발팀
ValueCountFrequency (%)
도로관리팀 501
 
11.5%
산업개발팀 300
 
6.9%
청소행정팀 296
 
6.8%
생활환경팀 229
 
5.2%
운수지도팀 210
 
4.8%
교통지도팀 177
 
4.0%
위생지도팀 171
 
3.9%
미세먼지대책팀 160
 
3.7%
교통시설팀 126
 
2.9%
총무팀 123
 
2.8%
Other values (154) 2079
47.6%
2023-12-12T22:10:17.367085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4347
19.8%
1396
 
6.4%
1010
 
4.6%
997
 
4.5%
996
 
4.5%
699
 
3.2%
664
 
3.0%
486
 
2.2%
448
 
2.0%
438
 
2.0%
Other values (160) 10482
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21875
99.6%
Uppercase Letter 62
 
0.3%
Other Punctuation 20
 
0.1%
Decimal Number 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4347
19.9%
1396
 
6.4%
1010
 
4.6%
997
 
4.6%
996
 
4.6%
699
 
3.2%
664
 
3.0%
486
 
2.2%
448
 
2.0%
438
 
2.0%
Other values (155) 10394
47.5%
Uppercase Letter
ValueCountFrequency (%)
F 31
50.0%
T 31
50.0%
Decimal Number
ValueCountFrequency (%)
1 3
50.0%
2 3
50.0%
Other Punctuation
ValueCountFrequency (%)
/ 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21875
99.6%
Latin 62
 
0.3%
Common 26
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4347
19.9%
1396
 
6.4%
1010
 
4.6%
997
 
4.6%
996
 
4.6%
699
 
3.2%
664
 
3.0%
486
 
2.2%
448
 
2.0%
438
 
2.0%
Other values (155) 10394
47.5%
Common
ValueCountFrequency (%)
/ 20
76.9%
1 3
 
11.5%
2 3
 
11.5%
Latin
ValueCountFrequency (%)
F 31
50.0%
T 31
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21875
99.6%
ASCII 88
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4347
19.9%
1396
 
6.4%
1010
 
4.6%
997
 
4.6%
996
 
4.6%
699
 
3.2%
664
 
3.0%
486
 
2.2%
448
 
2.0%
438
 
2.0%
Other values (155) 10394
47.5%
ASCII
ValueCountFrequency (%)
F 31
35.2%
T 31
35.2%
/ 20
22.7%
1 3
 
3.4%
2 3
 
3.4%

이관시의견
Text

MISSING 

Distinct912
Distinct (%)42.7%
Missing7862
Missing (%)78.6%
Memory size156.2 KiB
2023-12-12T22:10:17.729870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length111
Median length81
Mean length12.048644
Min length1

Characters and Unicode

Total characters25760
Distinct characters483
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique675 ?
Unique (%)31.6%

Sample

1st row담당자 변경
2nd row담당자 재지정
3rd row담당자 배정오류
4th row담당자 변경
5th row담당부서 이관
ValueCountFrequency (%)
담당자 523
 
8.5%
변경 487
 
8.0%
이관 365
 
6.0%
담당부서 296
 
4.8%
재지정 119
 
1.9%
관련 96
 
1.6%
담당자에게 83
 
1.4%
담당부서로 60
 
1.0%
담당자변경 59
 
1.0%
소관 57
 
0.9%
Other values (1758) 3977
65.0%
2023-12-12T22:10:18.226851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4089
 
15.9%
1266
 
4.9%
1232
 
4.8%
959
 
3.7%
844
 
3.3%
676
 
2.6%
676
 
2.6%
669
 
2.6%
644
 
2.5%
589
 
2.3%
Other values (473) 14116
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20644
80.1%
Space Separator 4089
 
15.9%
Decimal Number 328
 
1.3%
Other Punctuation 268
 
1.0%
Open Punctuation 181
 
0.7%
Close Punctuation 181
 
0.7%
Dash Punctuation 37
 
0.1%
Uppercase Letter 27
 
0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1266
 
6.1%
1232
 
6.0%
959
 
4.6%
844
 
4.1%
676
 
3.3%
676
 
3.3%
669
 
3.2%
644
 
3.1%
589
 
2.9%
536
 
2.6%
Other values (439) 12553
60.8%
Decimal Number
ValueCountFrequency (%)
1 65
19.8%
2 58
17.7%
0 46
14.0%
5 33
10.1%
4 33
10.1%
3 27
8.2%
6 21
 
6.4%
7 20
 
6.1%
9 13
 
4.0%
8 12
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
C 7
25.9%
T 5
18.5%
L 4
14.8%
V 3
11.1%
H 3
11.1%
F 2
 
7.4%
D 1
 
3.7%
E 1
 
3.7%
P 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
. 201
75.0%
, 37
 
13.8%
: 13
 
4.9%
/ 12
 
4.5%
' 2
 
0.7%
" 2
 
0.7%
1
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 180
99.4%
1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 180
99.4%
1
 
0.6%
Math Symbol
ValueCountFrequency (%)
~ 3
60.0%
> 2
40.0%
Space Separator
ValueCountFrequency (%)
4089
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20644
80.1%
Common 5089
 
19.8%
Latin 27
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1266
 
6.1%
1232
 
6.0%
959
 
4.6%
844
 
4.1%
676
 
3.3%
676
 
3.3%
669
 
3.2%
644
 
3.1%
589
 
2.9%
536
 
2.6%
Other values (439) 12553
60.8%
Common
ValueCountFrequency (%)
4089
80.3%
. 201
 
3.9%
( 180
 
3.5%
) 180
 
3.5%
1 65
 
1.3%
2 58
 
1.1%
0 46
 
0.9%
, 37
 
0.7%
- 37
 
0.7%
5 33
 
0.6%
Other values (15) 163
 
3.2%
Latin
ValueCountFrequency (%)
C 7
25.9%
T 5
18.5%
L 4
14.8%
V 3
11.1%
H 3
11.1%
F 2
 
7.4%
D 1
 
3.7%
E 1
 
3.7%
P 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20644
80.1%
ASCII 5113
 
19.8%
None 2
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4089
80.0%
. 201
 
3.9%
( 180
 
3.5%
) 180
 
3.5%
1 65
 
1.3%
2 58
 
1.1%
0 46
 
0.9%
, 37
 
0.7%
- 37
 
0.7%
5 33
 
0.6%
Other values (21) 187
 
3.7%
Hangul
ValueCountFrequency (%)
1266
 
6.1%
1232
 
6.0%
959
 
4.6%
844
 
4.1%
676
 
3.3%
676
 
3.3%
669
 
3.2%
644
 
3.1%
589
 
2.9%
536
 
2.6%
Other values (439) 12553
60.8%
Punctuation
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
1
50.0%
1
50.0%

이관부서명
Text

MISSING 

Distinct65
Distinct (%)3.0%
Missing7852
Missing (%)78.5%
Memory size156.2 KiB
2023-12-12T22:10:18.481898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.4553073
Min length3

Characters and Unicode

Total characters9570
Distinct characters118
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

Unique10 ?
Unique (%)0.5%

Sample

1st row민원봉사과
2nd row민원봉사과
3rd row공원녹지과
4th row민원봉사과
5th row위생과
ValueCountFrequency (%)
민원봉사과 516
24.0%
도로과 197
 
9.2%
교통행정과 110
 
5.1%
공원녹지과 107
 
5.0%
자원순환과 92
 
4.3%
하수도과 79
 
3.7%
환경보전과 78
 
3.6%
상수도과 72
 
3.4%
허가담당관 67
 
3.1%
민원봉사담당관 65
 
3.0%
Other values (55) 765
35.6%
2023-12-12T22:10:18.868984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1786
18.7%
789
 
8.2%
596
 
6.2%
592
 
6.2%
581
 
6.1%
390
 
4.1%
200
 
2.1%
174
 
1.8%
174
 
1.8%
171
 
1.8%
Other values (108) 4117
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9506
99.3%
Decimal Number 64
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1786
18.8%
789
 
8.3%
596
 
6.3%
592
 
6.2%
581
 
6.1%
390
 
4.1%
200
 
2.1%
174
 
1.8%
174
 
1.8%
171
 
1.8%
Other values (102) 4053
42.6%
Decimal Number
ValueCountFrequency (%)
6 17
26.6%
3 15
23.4%
1 15
23.4%
4 9
14.1%
5 6
 
9.4%
2 2
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9506
99.3%
Common 64
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1786
18.8%
789
 
8.3%
596
 
6.3%
592
 
6.2%
581
 
6.1%
390
 
4.1%
200
 
2.1%
174
 
1.8%
174
 
1.8%
171
 
1.8%
Other values (102) 4053
42.6%
Common
ValueCountFrequency (%)
6 17
26.6%
3 15
23.4%
1 15
23.4%
4 9
14.1%
5 6
 
9.4%
2 2
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9506
99.3%
ASCII 64
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1786
18.8%
789
 
8.3%
596
 
6.3%
592
 
6.2%
581
 
6.1%
390
 
4.1%
200
 
2.1%
174
 
1.8%
174
 
1.8%
171
 
1.8%
Other values (102) 4053
42.6%
ASCII
ValueCountFrequency (%)
6 17
26.6%
3 15
23.4%
1 15
23.4%
4 9
14.1%
5 6
 
9.4%
2 2
 
3.1%

협조요청일시
Date

MISSING 

Distinct15
Distinct (%)83.3%
Missing9982
Missing (%)99.8%
Memory size156.2 KiB
Minimum2018-11-20 13:11:00
Maximum2021-03-23 12:51:00
2023-12-12T22:10:19.020737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:19.181772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)

협조부서명
Text

MISSING 

Distinct11
Distinct (%)61.1%
Missing9982
Missing (%)99.8%
Memory size156.2 KiB
2023-12-12T22:10:19.412656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.3888889
Min length3

Characters and Unicode

Total characters79
Distinct characters33
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

Unique7 ?
Unique (%)38.9%

Sample

1st row환경보전과
2nd row축수산과
3rd row교통행정과
4th row농정과
5th row환경보전과
ValueCountFrequency (%)
환경보전과 4
22.2%
축수산과 3
16.7%
교통행정과 2
11.1%
도로과 2
11.1%
농정과 1
 
5.6%
정보통신과 1
 
5.6%
민원봉사담당관 1
 
5.6%
징수과 1
 
5.6%
주택과 1
 
5.6%
건축과 1
 
5.6%
2023-12-12T22:10:19.779647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17
21.5%
5
 
6.3%
4
 
5.1%
4
 
5.1%
4
 
5.1%
4
 
5.1%
4
 
5.1%
4
 
5.1%
3
 
3.8%
3
 
3.8%
Other values (23) 27
34.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
17
21.5%
5
 
6.3%
4
 
5.1%
4
 
5.1%
4
 
5.1%
4
 
5.1%
4
 
5.1%
4
 
5.1%
3
 
3.8%
3
 
3.8%
Other values (23) 27
34.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
17
21.5%
5
 
6.3%
4
 
5.1%
4
 
5.1%
4
 
5.1%
4
 
5.1%
4
 
5.1%
4
 
5.1%
3
 
3.8%
3
 
3.8%
Other values (23) 27
34.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
17
21.5%
5
 
6.3%
4
 
5.1%
4
 
5.1%
4
 
5.1%
4
 
5.1%
4
 
5.1%
4
 
5.1%
3
 
3.8%
3
 
3.8%
Other values (23) 27
34.2%

협조상위부서명
Text

MISSING 

Distinct6
Distinct (%)66.7%
Missing9991
Missing (%)99.9%
Memory size156.2 KiB
2023-12-12T22:10:19.951073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.5555556
Min length5

Characters and Unicode

Total characters50
Distinct characters27
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

Unique4 ?
Unique (%)44.4%

Sample

1st row농업기술센터
2nd row행정안전국
3rd row농업기술센터
4th row환경녹지국
5th row시민행복기획실
ValueCountFrequency (%)
농업기술센터 3
33.3%
환경녹지국 2
22.2%
행정안전국 1
 
11.1%
시민행복기획실 1
 
11.1%
건설교통국 1
 
11.1%
도시개발국 1
 
11.1%
2023-12-12T22:10:20.273895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
 
10.0%
4
 
8.0%
3
 
6.0%
3
 
6.0%
3
 
6.0%
3
 
6.0%
3
 
6.0%
2
 
4.0%
2
 
4.0%
2
 
4.0%
Other values (17) 20
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
 
10.0%
4
 
8.0%
3
 
6.0%
3
 
6.0%
3
 
6.0%
3
 
6.0%
3
 
6.0%
2
 
4.0%
2
 
4.0%
2
 
4.0%
Other values (17) 20
40.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
 
10.0%
4
 
8.0%
3
 
6.0%
3
 
6.0%
3
 
6.0%
3
 
6.0%
3
 
6.0%
2
 
4.0%
2
 
4.0%
2
 
4.0%
Other values (17) 20
40.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5
 
10.0%
4
 
8.0%
3
 
6.0%
3
 
6.0%
3
 
6.0%
3
 
6.0%
3
 
6.0%
2
 
4.0%
2
 
4.0%
2
 
4.0%
Other values (17) 20
40.0%

협조팀명
Text

MISSING 

Distinct14
Distinct (%)77.8%
Missing9982
Missing (%)99.8%
Memory size156.2 KiB
2023-12-12T22:10:20.478688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0555556
Min length4

Characters and Unicode

Total characters91
Distinct characters42
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

Unique10 ?
Unique (%)55.6%

Sample

1st row환경지도팀
2nd row해양수산팀
3rd row교통시설팀
4th row농촌관리
5th row대기관리팀
ValueCountFrequency (%)
환경지도팀 2
11.1%
교통시설팀 2
11.1%
축산유통팀 2
11.1%
도로관리팀 2
11.1%
해양수산팀 1
 
5.6%
농촌관리 1
 
5.6%
대기관리팀 1
 
5.6%
정보기획팀 1
 
5.6%
실개천생태팀 1
 
5.6%
민원콜센터팀 1
 
5.6%
Other values (4) 4
22.2%
2023-12-12T22:10:20.827219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17
18.7%
5
 
5.5%
4
 
4.4%
4
 
4.4%
4
 
4.4%
3
 
3.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
Other values (32) 42
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
17
18.7%
5
 
5.5%
4
 
4.4%
4
 
4.4%
4
 
4.4%
3
 
3.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
Other values (32) 42
46.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
17
18.7%
5
 
5.5%
4
 
4.4%
4
 
4.4%
4
 
4.4%
3
 
3.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
Other values (32) 42
46.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
17
18.7%
5
 
5.5%
4
 
4.4%
4
 
4.4%
4
 
4.4%
3
 
3.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
3
 
3.3%
Other values (32) 42
46.2%
Distinct3
Distinct (%)75.0%
Missing9996
Missing (%)> 99.9%
Memory size156.2 KiB
Minimum2020-04-30 00:00:00
Maximum2021-03-19 00:00:00
2023-12-12T22:10:20.950930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:10:21.060534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
Distinct3
Distinct (%)75.0%
Missing9996
Missing (%)> 99.9%
Memory size156.2 KiB
2023-12-12T22:10:21.212649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25.5
Mean length15.75
Min length6

Characters and Unicode

Total characters63
Distinct characters34
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st row민원처리지연
2nd row2020년 처리(2019년 예산 미확보)
3rd row민원처리지연
4th row추경예산확보 후 처리예정(배방읍 박병훈 3월2일요청)
ValueCountFrequency (%)
민원처리지연 2
18.2%
2020년 1
9.1%
처리(2019년 1
9.1%
예산 1
9.1%
미확보 1
9.1%
추경예산확보 1
9.1%
1
9.1%
처리예정(배방읍 1
9.1%
박병훈 1
9.1%
3월2일요청 1
9.1%
2023-12-12T22:10:21.534731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
 
11.1%
4
 
6.3%
4
 
6.3%
2 4
 
6.3%
3
 
4.8%
0 3
 
4.8%
2
 
3.2%
) 2
 
3.2%
2
 
3.2%
2
 
3.2%
Other values (24) 30
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42
66.7%
Decimal Number 10
 
15.9%
Space Separator 7
 
11.1%
Close Punctuation 2
 
3.2%
Open Punctuation 2
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4
 
9.5%
4
 
9.5%
3
 
7.1%
2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
Other values (16) 17
40.5%
Decimal Number
ValueCountFrequency (%)
2 4
40.0%
0 3
30.0%
9 1
 
10.0%
3 1
 
10.0%
1 1
 
10.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42
66.7%
Common 21
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4
 
9.5%
4
 
9.5%
3
 
7.1%
2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
Other values (16) 17
40.5%
Common
ValueCountFrequency (%)
7
33.3%
2 4
19.0%
0 3
14.3%
) 2
 
9.5%
( 2
 
9.5%
9 1
 
4.8%
3 1
 
4.8%
1 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42
66.7%
ASCII 21
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
33.3%
2 4
19.0%
0 3
14.3%
) 2
 
9.5%
( 2
 
9.5%
9 1
 
4.8%
3 1
 
4.8%
1 1
 
4.8%
Hangul
ValueCountFrequency (%)
4
 
9.5%
4
 
9.5%
3
 
7.1%
2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
Other values (16) 17
40.5%

Interactions

2023-12-12T22:10:10.080222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:10:21.647081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
생활민원번호출동처리여부배정자부서명이관처리부서명이관부서명협조요청일시협조부서명협조상위부서명협조팀명중장기연장처리예정일중장기연장처리사유
생활민원번호1.0000.2570.2990.2630.5831.0000.7820.6710.9681.0001.000
출동처리여부0.2571.0000.2870.5850.3171.0000.7961.0001.0001.0001.000
배정자부서명0.2990.2871.0000.8560.9950.0000.000NaN0.000NaNNaN
이관처리부서명0.2630.5850.8561.0000.9771.0000.8731.0001.000NaNNaN
이관부서명0.5830.3170.9950.9771.0001.0000.7671.0001.0000.0000.000
협조요청일시1.0001.0000.0001.0001.0001.0001.0001.0001.000NaNNaN
협조부서명0.7820.7960.0000.8730.7671.0001.0001.0001.000NaNNaN
협조상위부서명0.6711.000NaN1.0001.0001.0001.0001.0001.000NaNNaN
협조팀명0.9681.0000.0001.0001.0001.0001.0001.0001.000NaNNaN
중장기연장처리예정일1.0001.000NaNNaN0.000NaNNaNNaNNaN1.0001.000
중장기연장처리사유1.0001.000NaNNaN0.000NaNNaNNaNNaN1.0001.000
2023-12-12T22:10:21.784349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
생활민원번호출동처리여부
생활민원번호1.0000.171
출동처리여부0.1711.000

Missing values

2023-12-12T22:10:10.251833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:10:10.531015image/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.
2023-12-12T22:10:10.825658image/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

생활민원번호발송요청일시발송일시출동처리여부출동예정일시처리완료일시이관요청일시알림예약일시배정자부서명배정자팀명이관처리부서명이관처리팀명이관시의견이관부서명협조요청일시협조부서명협조상위부서명협조팀명중장기연장처리예정일중장기연장처리사유
15080201809270172018-09-27 13:102.02E+13N2018-09-27 11:302018-09-28 17:40<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
85524202101190222021-01-24 19:1120200000000000.0Y2021-01-24 19:102021-01-19 10:54<NA>민원봉사과민원콜센터팀경로장애인과경로복지팀담당자 변경민원봉사과<NA><NA><NA><NA><NA><NA>
85585202101190592021-01-27 09:0020200000000000.0Y2021-01-27 17:212021-01-19 16:46<NA><NA><NA>기후변화대책과미세먼지대책팀<NA><NA><NA><NA><NA><NA><NA><NA>
80941202011270432020-11-27 17:5420200000000000.0Y2020-11-30 09:082020-11-27 17:54<NA><NA><NA>대중교통과운수지도팀<NA><NA><NA><NA><NA><NA><NA><NA>
23422201901180172019-01-21 09:332.02E+13Y2019-01-21 11:44<NA><NA><NA><NA><NA><NA>담당자 재지정민원봉사과<NA><NA><NA><NA><NA><NA>
22109201812260032019-01-03 11:272.02E+13N2018-12-28 10:002019-01-03 11:27<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
57445202004040082020-04-04 14:3020200000000000.0N2020-04-06 15:002020-04-07 10:002020-04-04 14:30<NA><NA><NA>기후변화대책과생활환경팀<NA><NA><NA><NA><NA><NA><NA><NA>
49324201911180062019-11-18 09:1220200000000000.0N2019-11-18 14:302019-11-18 16:07<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
78853202011020392020-11-02 14:4220200000000000.0N2020-11-03 10:002020-11-03 11:412020-11-02 14:42<NA><NA><NA>배방읍산업개발팀<NA><NA><NA><NA><NA><NA><NA><NA>
74497202009140622020-09-14 16:3020200000000000.0N2020-09-14 17:002020-09-15 09:102020-09-14 16:30<NA><NA><NA>교통행정과교통시설팀<NA><NA><NA><NA><NA><NA><NA><NA>
생활민원번호발송요청일시발송일시출동처리여부출동예정일시처리완료일시이관요청일시알림예약일시배정자부서명배정자팀명이관처리부서명이관처리팀명이관시의견이관부서명협조요청일시협조부서명협조상위부서명협조팀명중장기연장처리예정일중장기연장처리사유
56502202003190512020-03-20 09:0020200000000000.0Y2020-03-23 14:492020-03-19 20:222020-03-20 09:00징수과징수팀공원녹지과공원관리팀<NA><NA><NA><NA><NA><NA><NA><NA>
24913201902190202019-02-19 13:532.02E+13N2019-02-21 11:302019-02-22 09:01<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38392201907190102019-08-01 09:0020200000000000.0Y2019-08-22 19:24<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28317201904050242019-04-05 13:572.02E+13N2019-04-08 10:302019-04-08 16:16<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
66662202007240652020-07-24 17:4320200000000000.0Y2020-08-01 16:252020-07-24 17:43<NA><NA><NA>도로과도로관리팀<NA><NA><NA><NA><NA><NA><NA><NA>
7061201807100022018-07-10 09:052.02E+13Y2018-07-12 14:39<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
89068202102260302021-03-09 09:0020200000000000.0Y2021-03-05 13:002021-03-09 17:472021-02-26 14:53<NA><NA><NA>둔포면산업개발팀<NA><NA><NA><NA><NA><NA><NA><NA>
87207202102050182021-02-05 10:1020200000000000.0Y2021-02-09 16:022021-02-05 10:10<NA><NA><NA>기후변화대책과미세먼지대책팀<NA><NA><NA><NA><NA><NA><NA><NA>
55637202003030202020-03-03 14:4920200000000000.0Y2020-03-10 14:542020-03-03 14:49<NA><NA><NA>감사위원회조사팀<NA><NA><NA><NA><NA><NA><NA><NA>
51143201912140042019-12-18 11:0620200000000000.0Y2019-12-18 11:06<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

생활민원번호발송요청일시출동처리여부출동예정일시처리완료일시이관요청일시알림예약일시배정자부서명배정자팀명이관처리부서명이관처리팀명이관시의견이관부서명협조요청일시협조부서명협조상위부서명협조팀명중장기연장처리예정일중장기연장처리사유# duplicates
0201805160052018-05-16 08:37N2018-05-16 10:002018-05-17 08:28<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
1201805200032018-05-20 10:40Y2018-05-21 13:23<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
2201806270542018-06-28 09:00N2018-07-02 10:002018-07-02 10:47<NA><NA><NA><NA><NA><NA>담당자 변경배방읍<NA><NA><NA><NA><NA><NA>2
3201807180212018-07-18 12:45Y2018-07-18 13:49<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
4201808110182018-08-11 15:39Y2018-08-13 14:40<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
5201809110282018-09-11 12:55N2018-09-11 16:002018-09-17 09:06<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
6201809160162018-09-27 09:00Y2018-09-27 21:37<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
7201810110292018-10-11 18:20Y2018-10-17 09:45<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
8201810120272018-10-12 14:17N2018-10-12 14:002018-10-16 16:52<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
9201810140102018-10-15 09:00Y2018-10-15 10:30<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2