Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory576.2 KiB
Average record size in memory59.0 B

Variable types

Numeric3
Categorical2
DateTime1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-1168/S/1/datasetView.do

Alerts

강우량계명 is highly overall correlated with 강우량계 코드 and 2 other fieldsHigh correlation
구청명 is highly overall correlated with 강우량계 코드 and 2 other fieldsHigh correlation
강우량계 코드 is highly overall correlated with 구청 코드 and 2 other fieldsHigh correlation
구청 코드 is highly overall correlated with 강우량계 코드 and 2 other fieldsHigh correlation
10분우량 has 9783 (97.8%) zerosZeros

Reproduction

Analysis started2023-12-11 08:25:05.812154
Analysis finished2023-12-11 08:25:08.402500
Duration2.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

강우량계 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1297.4544
Minimum101
Maximum2502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:25:08.511276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile103
Q1701
median1302
Q31902
95-th percentile2402
Maximum2502
Range2401
Interquartile range (IQR)1201

Descriptive statistics

Standard deviation742.06764
Coefficient of variation (CV)0.57194121
Kurtosis-1.2122243
Mean1297.4544
Median Absolute Deviation (MAD)600
Skewness-0.014634887
Sum12974544
Variance550664.38
MonotonicityNot monotonic
2023-12-11T17:25:08.735570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
202 246
 
2.5%
1001 245
 
2.5%
2502 240
 
2.4%
1002 236
 
2.4%
1902 236
 
2.4%
401 234
 
2.3%
301 229
 
2.3%
1702 229
 
2.3%
201 229
 
2.3%
1104 227
 
2.3%
Other values (37) 7649
76.5%
ValueCountFrequency (%)
101 210
2.1%
102 202
2.0%
103 223
2.2%
201 229
2.3%
202 246
2.5%
301 229
2.3%
401 234
2.3%
402 207
2.1%
501 223
2.2%
601 179
1.8%
ValueCountFrequency (%)
2502 240
2.4%
2501 211
2.1%
2402 222
2.2%
2401 215
2.1%
2302 225
2.2%
2301 226
2.3%
2202 185
1.8%
2201 210
2.1%
2102 217
2.2%
2101 220
2.2%

강우량계명
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
고덕2동
 
246
종로구청
 
245
마천2동
 
240
부암동
 
236
도림2동P
 
236
Other values (42)
8797 

Length

Max length5
Median length4
Mean length3.7853
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서대문구청
2nd row갈현1동
3rd row부암동
4th row서소문
5th row강남구청

Common Values

ValueCountFrequency (%)
고덕2동 246
 
2.5%
종로구청 245
 
2.5%
마천2동 240
 
2.4%
부암동 236
 
2.4%
도림2동P 236
 
2.4%
노원구청 234
 
2.3%
도봉구청 229
 
2.3%
강동구청 229
 
2.3%
공항동P 229
 
2.3%
서소문 227
 
2.3%
Other values (37) 7649
76.5%

Length

2023-12-11T17:25:08.978459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고덕2동 246
 
2.5%
종로구청 245
 
2.5%
마천2동 240
 
2.4%
부암동 236
 
2.4%
도림2동p 236
 
2.4%
노원구청 234
 
2.3%
도봉구청 229
 
2.3%
강동구청 229
 
2.3%
공항동p 229
 
2.3%
서소문 227
 
2.3%
Other values (37) 7649
76.5%

구청 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.9589
Minimum101
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:25:09.215266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1107
median113
Q3119
95-th percentile124
Maximum125
Range24
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.4211399
Coefficient of variation (CV)0.0656977
Kurtosis-1.2121236
Mean112.9589
Median Absolute Deviation (MAD)6
Skewness-0.01457905
Sum1129589
Variance55.073318
MonotonicityNot monotonic
2023-12-11T17:25:09.380515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
101 635
 
6.3%
113 589
 
5.9%
110 481
 
4.8%
102 475
 
4.8%
125 451
 
4.5%
123 451
 
4.5%
104 441
 
4.4%
121 437
 
4.4%
124 437
 
4.4%
117 435
 
4.3%
Other values (15) 5168
51.7%
ValueCountFrequency (%)
101 635
6.3%
102 475
4.8%
103 229
 
2.3%
104 441
4.4%
105 223
 
2.2%
106 390
3.9%
107 418
4.2%
108 408
4.1%
109 411
4.1%
110 481
4.8%
ValueCountFrequency (%)
125 451
4.5%
124 437
4.4%
123 451
4.5%
122 395
4.0%
121 437
4.4%
120 220
2.2%
119 430
4.3%
118 400
4.0%
117 435
4.3%
116 421
4.2%

구청명
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
강남구
 
635
은평구
 
589
종로구
 
481
강동구
 
475
송파구
 
451
Other values (20)
7369 

Length

Max length4
Median length3
Mean length3.0592
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서대문구
2nd row은평구
3rd row종로구
4th row중구
5th row강남구

Common Values

ValueCountFrequency (%)
강남구 635
 
6.3%
은평구 589
 
5.9%
종로구 481
 
4.8%
강동구 475
 
4.8%
송파구 451
 
4.5%
관악구 451
 
4.5%
노원구 441
 
4.4%
서초구 437
 
4.4%
동작구 437
 
4.4%
강서구 435
 
4.3%
Other values (15) 5168
51.7%

Length

2023-12-11T17:25:09.585065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강남구 635
 
6.3%
은평구 589
 
5.9%
종로구 481
 
4.8%
강동구 475
 
4.8%
송파구 451
 
4.5%
관악구 451
 
4.5%
노원구 441
 
4.4%
서초구 437
 
4.4%
동작구 437
 
4.4%
강서구 435
 
4.3%
Other values (15) 5168
51.7%

10분우량
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01635
Minimum0
Maximum3
Zeros9783
Zeros (%)97.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:25:09.744914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum3
Range3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.12393229
Coefficient of variation (CV)7.5799568
Kurtosis123.76251
Mean0.01635
Median Absolute Deviation (MAD)0
Skewness9.8294841
Sum163.5
Variance0.015359213
MonotonicityNot monotonic
2023-12-11T17:25:09.888443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.0 9783
97.8%
0.5 134
 
1.3%
1.0 64
 
0.6%
1.5 14
 
0.1%
2.0 3
 
< 0.1%
3.0 1
 
< 0.1%
2.5 1
 
< 0.1%
ValueCountFrequency (%)
0.0 9783
97.8%
0.5 134
 
1.3%
1.0 64
 
0.6%
1.5 14
 
0.1%
2.0 3
 
< 0.1%
2.5 1
 
< 0.1%
3.0 1
 
< 0.1%
ValueCountFrequency (%)
3.0 1
 
< 0.1%
2.5 1
 
< 0.1%
2.0 3
 
< 0.1%
1.5 14
 
0.1%
1.0 64
 
0.6%
0.5 134
 
1.3%
0.0 9783
97.8%

자료수집 시각
Date

Distinct2161
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-11-01 13:39:00
Maximum2021-11-22 19:09:00
2023-12-11T17:25:10.090261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:10.314203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-11T17:25:07.712333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:06.844706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:07.307540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:07.870283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:06.992444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:07.429606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:07.991477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:07.147897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:07.567220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T17:25:10.488314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계 코드강우량계명구청 코드구청명10분우량
강우량계 코드1.0001.0001.0001.0000.000
강우량계명1.0001.0001.0001.0000.000
구청 코드1.0001.0001.0001.0000.000
구청명1.0001.0001.0001.0000.014
10분우량0.0000.0000.0000.0141.000
2023-12-11T17:25:10.624911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계명구청명
강우량계명1.0000.999
구청명0.9991.000
2023-12-11T17:25:10.763849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계 코드구청 코드10분우량강우량계명구청명
강우량계 코드1.0000.9990.0110.9980.984
구청 코드0.9991.0000.0110.9980.999
10분우량0.0110.0111.0000.0000.006
강우량계명0.9980.9980.0001.0000.999
구청명0.9840.9990.0060.9991.000

Missing values

2023-12-11T17:25:08.177926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T17:25:08.331709image/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

강우량계 코드강우량계명구청 코드구청명10분우량자료수집 시각
706111401서대문구청114서대문구0.02021-11-18 09:58
625581303갈현1동113은평구0.02021-11-17 03:29
435161002부암동110종로구0.02021-11-08 00:49
517971104서소문111중구0.02021-11-09 06:09
39455101강남구청101강남구0.02021-11-07 10:29
850571401서대문구청114서대문구0.02021-11-20 13:29
825042501송파구청125송파구0.02021-11-20 04:29
162981201광진구청112광진구0.02021-11-03 23:49
817111602한남P116용산구0.02021-11-20 01:39
28141801동대문구청108동대문구0.02021-11-05 18:09
강우량계 코드강우량계명구청 코드구청명10분우량자료수집 시각
65888103개포2동101강남구0.02021-11-17 16:09
619122202가산2P122금천구0.02021-11-17 00:59
652192101동작구청121동작구0.02021-11-17 13:39
659481701강서구청117강서구0.02021-11-17 16:19
291011001종로구청110종로구0.02021-11-05 21:29
857222302신림P123관악구0.02021-11-20 15:49
24012501송파구청125송파구0.02021-11-01 22:29
364852102흑석P121동작구0.02021-11-06 23:49
228511502봉원P115마포구0.02021-11-04 23:19
121171502봉원P115마포구0.02021-11-03 08:59