Overview

Dataset statistics

Number of variables5
Number of observations9974
Missing cells2
Missing cells (%)< 0.1%
Duplicate rows9
Duplicate rows (%)0.1%
Total size in memory419.0 KiB
Average record size in memory43.0 B

Variable types

Numeric3
DateTime1
Text1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-22189/F/1/datasetView.do

Alerts

Dataset has 9 (0.1%) duplicate rowsDuplicates
경도 is highly overall correlated with 위도High correlation
위도 is highly overall correlated with 경도High correlation

Reproduction

Analysis started2024-03-23 01:34:09.327083
Analysis finished2024-03-23 01:34:15.570838
Duration6.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

민원접수일
Real number (ℝ)

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20211003
Minimum20210929
Maximum20211021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.8 KiB
2024-03-23T10:34:15.707467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210929
5-th percentile20210930
Q120211004
median20211009
Q320211015
95-th percentile20211020
Maximum20211021
Range92
Interquartile range (IQR)11

Descriptive statistics

Standard deviation24.637176
Coefficient of variation (CV)1.2189982 × 10-6
Kurtosis4.6606221
Mean20211003
Median Absolute Deviation (MAD)6
Skewness-2.4731479
Sum2.0158454 × 1011
Variance606.99042
MonotonicityIncreasing
2024-03-23T10:34:15.977360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
20211019 545
 
5.5%
20211015 532
 
5.3%
20211008 498
 
5.0%
20211007 493
 
4.9%
20210930 486
 
4.9%
20211020 484
 
4.9%
20210929 474
 
4.8%
20211016 464
 
4.7%
20211001 461
 
4.6%
20211005 459
 
4.6%
Other values (13) 5078
50.9%
ValueCountFrequency (%)
20210929 474
4.8%
20210930 486
4.9%
20211001 461
4.6%
20211002 452
4.5%
20211003 431
4.3%
20211004 397
4.0%
20211005 459
4.6%
20211006 413
4.1%
20211007 493
4.9%
20211008 498
5.0%
ValueCountFrequency (%)
20211021 166
 
1.7%
20211020 484
4.9%
20211019 545
5.5%
20211018 426
4.3%
20211017 346
3.5%
20211016 464
4.7%
20211015 532
5.3%
20211014 453
4.5%
20211013 453
4.5%
20211012 370
3.7%

민원접수시간
Date

Distinct1250
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
Minimum2024-03-23 00:00:00
Maximum2024-03-23 23:59:00
2024-03-23T10:34:16.409202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T10:34:16.744078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

주소
Text

Distinct6328
Distinct (%)63.5%
Missing2
Missing (%)< 0.1%
Memory size78.1 KiB
2024-03-23T10:34:17.363205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length111
Median length101
Mean length21.032992
Min length5

Characters and Unicode

Total characters209741
Distinct characters652
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5003 ?
Unique (%)50.2%

Sample

1st row서울 강서구 화곡로66길 130
2nd row중구 다산로48길 33 단우물어린이집앞
3rd row서울특별시 중구 마장로 19
4th row서울특별시 강서구 까치산로15길 21
5th row서울특별시 중구 다산로 293
ValueCountFrequency (%)
서울특별시 5736
 
13.1%
강서구 3583
 
8.2%
중구 1668
 
3.8%
성북구 1403
 
3.2%
서울 1036
 
2.4%
동작구 934
 
2.1%
앞 919
 
2.1%
강북구 854
 
2.0%
화곡동 334
 
0.8%
성북동 300
 
0.7%
Other values (6657) 26930
61.6%
2024-03-23T10:34:18.752884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35251
 
16.8%
서 11691
 
5.6%
로 9346
 
4.5%
구 9158
 
4.4%
1 8728
 
4.2%
울 6924
 
3.3%
길 6748
 
3.2%
2 6348
 
3.0%
시 5891
 
2.8%
특 5741
 
2.7%
Other values (642) 103915
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125447
59.8%
Decimal Number 42379
 
20.2%
Space Separator 35251
 
16.8%
Dash Punctuation 3301
 
1.6%
Close Punctuation 1201
 
0.6%
Open Punctuation 1192
 
0.6%
Other Punctuation 488
 
0.2%
Uppercase Letter 222
 
0.1%
Math Symbol 131
 
0.1%
Lowercase Letter 129
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 11691
 
9.3%
로 9346
 
7.5%
구 9158
 
7.3%
울 6924
 
5.5%
길 6748
 
5.4%
시 5891
 
4.7%
특 5741
 
4.6%
별 5739
 
4.6%
강 5416
 
4.3%
동 4547
 
3.6%
Other values (573) 54246
43.2%
Uppercase Letter
ValueCountFrequency (%)
S 36
16.2%
C 27
12.2%
K 23
10.4%
G 19
8.6%
O 18
8.1%
M 18
8.1%
U 15
6.8%
D 12
 
5.4%
P 11
 
5.0%
A 7
 
3.2%
Other values (12) 36
16.2%
Lowercase Letter
ValueCountFrequency (%)
t 27
20.9%
g 21
16.3%
b 17
13.2%
a 10
 
7.8%
m 9
 
7.0%
p 9
 
7.0%
s 8
 
6.2%
o 5
 
3.9%
x 4
 
3.1%
l 3
 
2.3%
Other values (9) 16
12.4%
Decimal Number
ValueCountFrequency (%)
1 8728
20.6%
2 6348
15.0%
3 5086
12.0%
4 4382
10.3%
5 3838
9.1%
6 3164
 
7.5%
7 3121
 
7.4%
8 2924
 
6.9%
0 2585
 
6.1%
9 2203
 
5.2%
Other Punctuation
ValueCountFrequency (%)
. 165
33.8%
, 158
32.4%
/ 58
 
11.9%
: 37
 
7.6%
; 30
 
6.1%
& 29
 
5.9%
? 9
 
1.8%
* 2
 
0.4%
Math Symbol
ValueCountFrequency (%)
~ 124
94.7%
= 4
 
3.1%
| 2
 
1.5%
→ 1
 
0.8%
Close Punctuation
ValueCountFrequency (%)
) 1167
97.2%
] 34
 
2.8%
Open Punctuation
ValueCountFrequency (%)
( 1162
97.5%
[ 30
 
2.5%
Space Separator
ValueCountFrequency (%)
35251
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3301
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 125443
59.8%
Common 83943
40.0%
Latin 351
 
0.2%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 11691
 
9.3%
로 9346
 
7.5%
구 9158
 
7.3%
울 6924
 
5.5%
길 6748
 
5.4%
시 5891
 
4.7%
특 5741
 
4.6%
별 5739
 
4.6%
강 5416
 
4.3%
동 4547
 
3.6%
Other values (572) 54242
43.2%
Latin
ValueCountFrequency (%)
S 36
 
10.3%
t 27
 
7.7%
C 27
 
7.7%
K 23
 
6.6%
g 21
 
6.0%
G 19
 
5.4%
O 18
 
5.1%
M 18
 
5.1%
b 17
 
4.8%
U 15
 
4.3%
Other values (31) 130
37.0%
Common
ValueCountFrequency (%)
35251
42.0%
1 8728
 
10.4%
2 6348
 
7.6%
3 5086
 
6.1%
4 4382
 
5.2%
5 3838
 
4.6%
- 3301
 
3.9%
6 3164
 
3.8%
7 3121
 
3.7%
8 2924
 
3.5%
Other values (18) 7800
 
9.3%
Han
ValueCountFrequency (%)
上 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 125437
59.8%
ASCII 84293
40.2%
Compat Jamo 6
 
< 0.1%
CJK 4
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35251
41.8%
1 8728
 
10.4%
2 6348
 
7.5%
3 5086
 
6.0%
4 4382
 
5.2%
5 3838
 
4.6%
- 3301
 
3.9%
6 3164
 
3.8%
7 3121
 
3.7%
8 2924
 
3.5%
Other values (58) 8150
 
9.7%
Hangul
ValueCountFrequency (%)
서 11691
 
9.3%
로 9346
 
7.5%
구 9158
 
7.3%
울 6924
 
5.5%
길 6748
 
5.4%
시 5891
 
4.7%
특 5741
 
4.6%
별 5739
 
4.6%
강 5416
 
4.3%
동 4547
 
3.6%
Other values (570) 54236
43.2%
Compat Jamo
ValueCountFrequency (%)
ㅡ 5
83.3%
ㄱ 1
 
16.7%
CJK
ValueCountFrequency (%)
上 4
100.0%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct8045
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.94037
Minimum126.79909
Maximum128.48033
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.8 KiB
2024-03-23T10:34:19.022356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.79909
5-th percentile126.81418
Q1126.84802
median126.97742
Q3127.01554
95-th percentile127.04186
Maximum128.48033
Range1.6812438
Interquartile range (IQR)0.16752783

Descriptive statistics

Standard deviation0.093348836
Coefficient of variation (CV)0.00073537549
Kurtosis29.522188
Mean126.94037
Median Absolute Deviation (MAD)0.0549215
Skewness2.1257395
Sum1266103.2
Variance0.0087140052
MonotonicityNot monotonic
2024-03-23T10:34:19.370373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.002093204685 44
 
0.4%
127.002075428037 39
 
0.4%
127.015544787336 37
 
0.4%
127.00217791133 32
 
0.3%
126.912110841797 31
 
0.3%
127.019770338332 26
 
0.3%
127.002139867598 26
 
0.3%
127.015437291859 25
 
0.3%
126.835447100924 25
 
0.3%
127.018619966466 24
 
0.2%
Other values (8035) 9665
96.9%
ValueCountFrequency (%)
126.799086225825 1
< 0.1%
126.7992237 1
< 0.1%
126.7993374 1
< 0.1%
126.79950332577329 1
< 0.1%
126.800375 1
< 0.1%
126.800678 1
< 0.1%
126.80085415201728 1
< 0.1%
126.80111505891692 2
< 0.1%
126.801408 1
< 0.1%
126.8015722 1
< 0.1%
ValueCountFrequency (%)
128.48033 1
 
< 0.1%
128.47765997222223 1
 
< 0.1%
128.28835997222222 1
 
< 0.1%
128.21931997222222 1
 
< 0.1%
128.1323399722222 1
 
< 0.1%
128.10056997222222 1
 
< 0.1%
127.89349997222222 2
 
< 0.1%
127.566288213262 7
0.1%
127.5213999722222 1
 
< 0.1%
127.437168786329 1
 
< 0.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct8030
Distinct (%)80.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.564956
Minimum36.314171
Maximum39.20717
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.8 KiB
2024-03-23T10:34:19.663388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.314171
5-th percentile37.496099
Q137.54227
median37.561397
Q337.593757
95-th percentile37.636951
Maximum39.20717
Range2.8929987
Interquartile range (IQR)0.051486515

Descriptive statistics

Standard deviation0.054304325
Coefficient of variation (CV)0.0014456113
Kurtosis269.68899
Mean37.564956
Median Absolute Deviation (MAD)0.023847166
Skewness8.3841408
Sum374672.87
Variance0.0029489597
MonotonicityNot monotonic
2024-03-23T10:34:20.100350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5941125317105 44
 
0.4%
37.5941398320738 39
 
0.4%
37.5956209578746 37
 
0.4%
37.5944279673737 32
 
0.3%
37.4897581484644 31
 
0.3%
37.5945097781136 26
 
0.3%
37.5703293503309 26
 
0.3%
37.5521648737652 25
 
0.3%
37.5959936220515 25
 
0.3%
37.5691169776983 24
 
0.2%
Other values (8020) 9665
96.9%
ValueCountFrequency (%)
36.3141712846463 1
 
< 0.1%
37.2993621542091 7
0.1%
37.4117590016607 4
< 0.1%
37.4579646525751 1
 
< 0.1%
37.466406 1
 
< 0.1%
37.4673322 1
 
< 0.1%
37.4688334692528 1
 
< 0.1%
37.469317389327 1
 
< 0.1%
37.46951654259525 1
 
< 0.1%
37.470394111318825 1
 
< 0.1%
ValueCountFrequency (%)
39.20716997222222 1
< 0.1%
38.97096 1
< 0.1%
38.95916 2
< 0.1%
38.53417 1
< 0.1%
38.44767997222223 1
< 0.1%
38.375099972222216 1
< 0.1%
38.26838997222222 1
< 0.1%
38.171459972222216 1
< 0.1%
38.02416997222223 1
< 0.1%
37.798499972222224 1
< 0.1%

Interactions

2024-03-23T10:34:13.926008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T10:34:12.460083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T10:34:13.113487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T10:34:14.097361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T10:34:12.633926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T10:34:13.333509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T10:34:14.718530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T10:34:12.867070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T10:34:13.634247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T10:34:20.517456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
민원접수일경도위도
민원접수일1.0000.0140.000
경도0.0141.0000.927
위도0.0000.9271.000
2024-03-23T10:34:20.861344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
민원접수일경도위도
민원접수일1.0000.0120.033
경도0.0121.0000.580
위도0.0330.5801.000

Missing values

2024-03-23T10:34:15.188402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T10:34:15.422540image/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.

Sample

민원접수일민원접수시간주소경도위도
02021092900:05:00서울 강서구 화곡로66길 130126.85991137.555537
12021092900:38:00중구 다산로48길 33 단우물어린이집앞127.01801337.567483
22021092900:38:00서울특별시 중구 마장로 19127.01279337.569183
32021092900:50:00서울특별시 강서구 까치산로15길 21126.84712537.54704
42021092901:15:00서울특별시 중구 다산로 293127.01570337.569085
52021092901:16:00서울특별시 중구 마장로 19127.01182337.568211
62021092901:27:00서울특별시 중구 동호로11마길 31127.0059837.550744
72021092901:27:00서울특별시 중구 동호로11마길 37127.00581637.550737
82021092901:28:00서울특별시 중구 동호로11마길 16127.00631137.551363
92021092901:28:00서울특별시 중구 동호로11마길 5-2127.00650837.551723
민원접수일민원접수시간주소경도위도
99642021102111:16:00노원구 월계로42길 97 꿈의숲 SK뷰 아파트와 우이천 사이 도로상127.05317437.622005
99652021102111:18:00강서구 양천로17길 27-2(방화동 453-30) 2동옆126.81280937.575014
99662021102111:22:00서울특별시 동작구 사당로 2차길54-7126.96733737.486759
99672021102111:24:00서울 성북구 정릉동 160-17 (도로명)서울 성북구 정릉로 261127.01276237.604126
99682021102111:25:00서울 중구 봉래동1가 13-1126.97408237.559359
99692021102111:27:00성북구 아리랑 로31-1 앞도로127.01554537.595621
99702021102111:28:00성북구 아리랑 로34 앞도로127.01595337.595736
99712021102111:31:00서울특별시 중구 장충단로13길 34127.00697337.568322
99722021102111:38:00중구 수표로4길 7(충무로3가 58-5)126.9908937.562574
99732021102111:39:00수유로2~수유로30까지127.01812937.631107

Duplicate rows

Most frequently occurring

민원접수일민원접수시간주소경도위도# duplicates
02021093007:41:00서울특별시 강서구 양천로47길 24126.83783837.5715352
12021100119:55:00서울 성북구 장위로 173( 장위동 89-3)명품 공인중개사부분 일대 보도 및 차도127.05511937.615612
22021100308:39:00서울특별시 강북구 한천로139가길 10127.02582937.6400112
32021100813:02:00서울특별시 강서구 화곡로31길 27126.84175737.5442352
42021100823:11:00강서구 초원로2길 일방통행길 진출입구간과 공원입구126.805737.567672
52021101110:23:00성북구 성북동 154-2 앞127.00209337.5941132
62021101218:42:00서울특별시 강서구 강서로18라길 22-13126.84859137.5358172
72021101417:35:00서울특별시 동작구 동작대로7길 21126.98137137.4796242
82021101420:25:00성북동154-2127.00209337.5941132