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

Numeric2
Categorical3
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 is highly imbalanced (90.6%)Imbalance

Reproduction

Analysis started2023-12-11 08:25:18.487013
Analysis finished2023-12-11 08:25:19.647985
Duration1.16 second
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%
Mean1292.6012
Minimum101
Maximum2502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:25:19.746323image/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 deviation735.14981
Coefficient of variation (CV)0.56873675
Kurtosis-1.1928013
Mean1292.6012
Median Absolute Deviation (MAD)600
Skewness-0.02364273
Sum12926012
Variance540445.24
MonotonicityNot monotonic
2023-12-11T17:25:19.944393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
202 238
 
2.4%
301 237
 
2.4%
1902 235
 
2.4%
1702 230
 
2.3%
1502 227
 
2.3%
101 226
 
2.3%
1501 226
 
2.3%
2001 226
 
2.3%
103 225
 
2.2%
1602 225
 
2.2%
Other values (37) 7705
77.0%
ValueCountFrequency (%)
101 226
2.3%
102 202
2.0%
103 225
2.2%
201 213
2.1%
202 238
2.4%
301 237
2.4%
401 212
2.1%
402 206
2.1%
501 206
2.1%
601 223
2.2%
ValueCountFrequency (%)
2502 216
2.2%
2501 208
2.1%
2402 198
2.0%
2401 192
1.9%
2302 207
2.1%
2301 216
2.2%
2202 217
2.2%
2201 222
2.2%
2102 212
2.1%
2101 182
1.8%

강우량계명
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
고덕2동
 
238
도봉구청
 
237
도림2동P
 
235
공항동P
 
230
봉원P
 
227
Other values (42)
8833 

Length

Max length5
Median length4
Mean length3.7932
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row양천구청
2nd row성동구청
3rd row용산구청
4th row영등포구청
5th row강서구청

Common Values

ValueCountFrequency (%)
고덕2동 238
 
2.4%
도봉구청 237
 
2.4%
도림2동P 235
 
2.4%
공항동P 230
 
2.3%
봉원P 227
 
2.3%
강남구청 226
 
2.3%
마포구청 226
 
2.3%
구로구청 226
 
2.3%
한남P 225
 
2.2%
개포2동 225
 
2.2%
Other values (37) 7705
77.0%

Length

2023-12-11T17:25:20.106936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고덕2동 238
 
2.4%
도봉구청 237
 
2.4%
도림2동p 235
 
2.4%
공항동p 230
 
2.3%
봉원p 227
 
2.3%
강남구청 226
 
2.3%
마포구청 226
 
2.3%
구로구청 226
 
2.3%
한남p 225
 
2.2%
개포2동 225
 
2.2%
Other values (37) 7705
77.0%

구청 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.9105
Minimum101
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:25:20.262136image/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 deviation7.3519314
Coefficient of variation (CV)0.065112911
Kurtosis-1.1926624
Mean112.9105
Median Absolute Deviation (MAD)6
Skewness-0.023625803
Sum1129105
Variance54.050895
MonotonicityNot monotonic
2023-12-11T17:25:20.409155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
101 653
 
6.5%
113 591
 
5.9%
115 453
 
4.5%
102 451
 
4.5%
119 450
 
4.5%
117 447
 
4.5%
122 439
 
4.4%
108 437
 
4.4%
116 428
 
4.3%
111 426
 
4.3%
Other values (15) 5225
52.2%
ValueCountFrequency (%)
101 653
6.5%
102 451
4.5%
103 237
 
2.4%
104 418
4.2%
105 206
 
2.1%
106 421
4.2%
107 421
4.2%
108 437
4.4%
109 420
4.2%
110 403
4.0%
ValueCountFrequency (%)
125 424
4.2%
124 390
3.9%
123 423
4.2%
122 439
4.4%
121 394
3.9%
120 226
2.3%
119 450
4.5%
118 424
4.2%
117 447
4.5%
116 428
4.3%

구청명
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
강남구
 
653
은평구
 
591
마포구
 
453
강동구
 
451
영등포구
 
450
Other values (20)
7402 

Length

Max length4
Median length3
Mean length3.0665
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row양천구
2nd row성동구
3rd row용산구
4th row영등포구
5th row강서구

Common Values

ValueCountFrequency (%)
강남구 653
 
6.5%
은평구 591
 
5.9%
마포구 453
 
4.5%
강동구 451
 
4.5%
영등포구 450
 
4.5%
강서구 447
 
4.5%
금천구 439
 
4.4%
동대문구 437
 
4.4%
용산구 428
 
4.3%
중구 426
 
4.3%
Other values (15) 5225
52.2%

Length

2023-12-11T17:25:20.550259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강남구 653
 
6.5%
은평구 591
 
5.9%
마포구 453
 
4.5%
강동구 451
 
4.5%
영등포구 450
 
4.5%
강서구 447
 
4.5%
금천구 439
 
4.4%
동대문구 437
 
4.4%
용산구 428
 
4.3%
중구 426
 
4.3%
Other values (15) 5225
52.2%

10분우량
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0.0
9710 
0.5
 
225
1.0
 
50
1.5
 
10
2.0
 
5

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 9710
97.1%
0.5 225
 
2.2%
1.0 50
 
0.5%
1.5 10
 
0.1%
2.0 5
 
0.1%

Length

2023-12-11T17:25:20.707061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:25:20.851308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 9710
97.1%
0.5 225
 
2.2%
1.0 50
 
0.5%
1.5 10
 
0.1%
2.0 5
 
< 0.1%

자료수집 시각
Date

Distinct2141
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-09-01 00:09:00
Maximum2021-09-15 19:49:00
2023-12-11T17:25:21.070673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:21.265973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-11T17:25:19.169068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:18.920212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:19.282086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:19.050026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T17:25:21.431906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계 코드강우량계명구청 코드구청명10분우량
강우량계 코드1.0001.0001.0001.0000.019
강우량계명1.0001.0001.0001.0000.065
구청 코드1.0001.0001.0001.0000.018
구청명1.0001.0001.0001.0000.043
10분우량0.0190.0650.0180.0431.000
2023-12-11T17:25:21.557578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
10분우량강우량계명구청명
10분우량1.0000.0300.018
강우량계명0.0301.0000.999
구청명0.0180.9991.000
2023-12-11T17:25:21.669678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계 코드구청 코드강우량계명구청명10분우량
강우량계 코드1.0000.9990.9980.9830.008
구청 코드0.9991.0000.9980.9990.008
강우량계명0.9980.9981.0000.9990.030
구청명0.9830.9990.9991.0000.018
10분우량0.0080.0080.0300.0181.000

Missing values

2023-12-11T17:25:19.420650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T17:25:19.591939image/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
159821801양천구청118양천구0.02021-09-03 08:49
32723901성동구청109성동구0.02021-09-05 20:09
660551601용산구청116용산구0.02021-09-10 18:29
298201901영등포구청119영등포구0.02021-09-05 09:49
266511701강서구청117강서구0.02021-09-04 22:39
16779102세곡동101강남구0.02021-09-03 11:39
342771802목동P118양천구0.02021-09-06 01:39
470112202가산2P122금천구0.02021-09-07 22:49
428211702공항동P117강서구0.02021-09-07 07:59
394991302증산P113은평구0.52021-09-06 20:09
강우량계 코드강우량계명구청 코드구청명10분우량자료수집 시각
816492001구로구청120구로구0.02021-09-13 01:49
8912501송파구청125송파구0.02021-09-01 03:09
31103402상계1동104노원구0.02021-09-05 14:19
570921801양천구청118양천구0.02021-09-09 10:39
553851701강서구청117강서구0.02021-09-09 04:29
5830103개포2동101강남구0.02021-09-01 20:49
838402201금천구청122금천구0.02021-09-13 09:39
3907602상월곡동106성북구0.02021-09-01 13:59
571111601용산구청116용산구0.02021-09-09 10:39
250231302증산P113은평구0.02021-09-04 16:49