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 9881 (98.8%) zerosZeros

Reproduction

Analysis started2023-12-11 08:26:16.833894
Analysis finished2023-12-11 08:26:18.789722
Duration1.96 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

강우량계 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1332.6293
Minimum101
Maximum2502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:26:18.893414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile103
Q1702
median1303
Q32001
95-th percentile2402
Maximum2502
Range2401
Interquartile range (IQR)1299

Descriptive statistics

Standard deviation729.81956
Coefficient of variation (CV)0.54765384
Kurtosis-1.1879173
Mean1332.6293
Median Absolute Deviation (MAD)602
Skewness-0.09647519
Sum13326293
Variance532636.59
MonotonicityNot monotonic
2023-12-11T17:26:19.110768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
2001 238
 
2.4%
2202 231
 
2.3%
2301 229
 
2.3%
301 227
 
2.3%
2002 227
 
2.3%
2201 227
 
2.3%
1501 226
 
2.3%
1401 224
 
2.2%
2402 219
 
2.2%
1303 219
 
2.2%
Other values (38) 7733
77.3%
ValueCountFrequency (%)
101 199
2.0%
102 192
1.9%
103 187
1.9%
201 197
2.0%
202 205
2.1%
301 227
2.3%
401 185
1.8%
402 208
2.1%
501 208
2.1%
601 195
1.9%
ValueCountFrequency (%)
2502 196
2.0%
2501 214
2.1%
2402 219
2.2%
2401 204
2.0%
2302 204
2.0%
2301 229
2.3%
2202 231
2.3%
2201 227
2.3%
2102 217
2.2%
2101 205
2.1%

강우량계명
Categorical

HIGH CORRELATION 

Distinct48
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
구로구청
 
238
가산2P
 
231
관악구청
 
229
도봉구청
 
227
개봉2동
 
227
Other values (43)
8848 

Length

Max length5
Median length4
Mean length3.7899
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row반포P
2nd row마포구청
3rd row갈현1동
4th row강서구청
5th row마포구청

Common Values

ValueCountFrequency (%)
구로구청 238
 
2.4%
가산2P 231
 
2.3%
관악구청 229
 
2.3%
도봉구청 227
 
2.3%
개봉2동 227
 
2.3%
금천구청 227
 
2.3%
마포구청 226
 
2.3%
서대문구청 224
 
2.2%
반포P 219
 
2.2%
갈현1동 219
 
2.2%
Other values (38) 7733
77.3%

Length

2023-12-11T17:26:19.314787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
구로구청 238
 
2.4%
가산2p 231
 
2.3%
관악구청 229
 
2.3%
도봉구청 227
 
2.3%
개봉2동 227
 
2.3%
금천구청 227
 
2.3%
마포구청 226
 
2.3%
서대문구청 224
 
2.2%
반포p 219
 
2.2%
갈현1동 219
 
2.2%
Other values (38) 7733
77.3%

구청 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.3107
Minimum101
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:26:19.484194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1107
median113
Q3120
95-th percentile124
Maximum125
Range24
Interquartile range (IQR)13

Descriptive statistics

Standard deviation7.2985541
Coefficient of variation (CV)0.06441187
Kurtosis-1.1877916
Mean113.3107
Median Absolute Deviation (MAD)6
Skewness-0.096415297
Sum1133107
Variance53.268892
MonotonicityNot monotonic
2023-12-11T17:26:19.652215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
113 634
 
6.3%
101 578
 
5.8%
120 465
 
4.7%
122 458
 
4.6%
115 444
 
4.4%
123 433
 
4.3%
110 423
 
4.2%
124 423
 
4.2%
121 422
 
4.2%
117 419
 
4.2%
Other values (15) 5301
53.0%
ValueCountFrequency (%)
101 578
5.8%
102 402
4.0%
103 227
 
2.3%
104 393
3.9%
105 208
 
2.1%
106 401
4.0%
107 411
4.1%
108 397
4.0%
109 409
4.1%
110 423
4.2%
ValueCountFrequency (%)
125 410
4.1%
124 423
4.2%
123 433
4.3%
122 458
4.6%
121 422
4.2%
120 465
4.7%
119 396
4.0%
118 415
4.2%
117 419
4.2%
116 402
4.0%

구청명
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
은평구
 
634
강남구
 
578
구로구
 
465
금천구
 
458
마포구
 
444
Other values (20)
7421 

Length

Max length4
Median length3
Mean length3.0621
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서초구
2nd row마포구
3rd row은평구
4th row강서구
5th row마포구

Common Values

ValueCountFrequency (%)
은평구 634
 
6.3%
강남구 578
 
5.8%
구로구 465
 
4.7%
금천구 458
 
4.6%
마포구 444
 
4.4%
관악구 433
 
4.3%
서초구 423
 
4.2%
종로구 423
 
4.2%
동작구 422
 
4.2%
강서구 419
 
4.2%
Other values (15) 5301
53.0%

Length

2023-12-11T17:26:19.845449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
은평구 634
 
6.3%
강남구 578
 
5.8%
구로구 465
 
4.7%
금천구 458
 
4.6%
마포구 444
 
4.4%
관악구 433
 
4.3%
서초구 423
 
4.2%
종로구 423
 
4.2%
동작구 422
 
4.2%
강서구 419
 
4.2%
Other values (15) 5301
53.0%

10분우량
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02385
Minimum0
Maximum8.5
Zeros9881
Zeros (%)98.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:26:20.036788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum8.5
Range8.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.29642025
Coefficient of variation (CV)12.428522
Kurtosis403.04868
Mean0.02385
Median Absolute Deviation (MAD)0
Skewness18.255185
Sum238.5
Variance0.087864964
MonotonicityNot monotonic
2023-12-11T17:26:20.190107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 9881
98.8%
0.5 31
 
0.3%
1.5 22
 
0.2%
1.0 22
 
0.2%
2.5 10
 
0.1%
3.0 7
 
0.1%
2.0 7
 
0.1%
4.0 6
 
0.1%
3.5 4
 
< 0.1%
8.0 3
 
< 0.1%
Other values (5) 7
 
0.1%
ValueCountFrequency (%)
0.0 9881
98.8%
0.5 31
 
0.3%
1.0 22
 
0.2%
1.5 22
 
0.2%
2.0 7
 
0.1%
2.5 10
 
0.1%
3.0 7
 
0.1%
3.5 4
 
< 0.1%
4.0 6
 
0.1%
4.5 1
 
< 0.1%
ValueCountFrequency (%)
8.5 1
 
< 0.1%
8.0 3
 
< 0.1%
7.5 2
 
< 0.1%
6.5 2
 
< 0.1%
5.0 1
 
< 0.1%
4.5 1
 
< 0.1%
4.0 6
0.1%
3.5 4
 
< 0.1%
3.0 7
0.1%
2.5 10
0.1%

자료수집 시각
Date

Distinct2126
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-11-01 00:09:00
Maximum2022-11-15 12:59:00
2023-12-11T17:26:20.355826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:20.586209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-11T17:26:18.132843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:17.398831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:17.761605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:18.287577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:17.519681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:17.888216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:18.425382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:17.647165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:18.015567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T17:26:20.719218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계 코드강우량계명구청 코드구청명10분우량
강우량계 코드1.0001.0001.0001.0000.011
강우량계명1.0001.0001.0001.0000.000
구청 코드1.0001.0001.0001.0000.005
구청명1.0001.0001.0001.0000.000
10분우량0.0110.0000.0050.0001.000
2023-12-11T17:26:20.842613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계명구청명
강우량계명1.0000.999
구청명0.9991.000
2023-12-11T17:26:21.309824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계 코드구청 코드10분우량강우량계명구청명
강우량계 코드1.0000.999-0.0250.9980.983
구청 코드0.9991.000-0.0250.9980.999
10분우량-0.025-0.0251.0000.0000.000
강우량계명0.9980.9980.0001.0000.999
구청명0.9830.9990.0000.9991.000

Missing values

2023-12-11T17:26:18.579751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T17:26:18.725768image/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
359012402반포P124서초구0.02022-11-06 04:49
248911501마포구청115마포구0.02022-11-04 14:29
518811303갈현1동113은평구0.02022-11-08 12:29
504711701강서구청117강서구0.02022-11-08 07:29
26131501마포구청115마포구0.02022-11-01 09:09
523562302신림P123관악구0.02022-11-08 13:59
622712501송파구청125송파구0.02022-11-10 00:29
41328902뚝섬P109성동구0.02022-11-06 23:49
137561501마포구청115마포구0.02022-11-02 23:49
41519401노원구청104노원구0.02022-11-07 00:29
강우량계 코드강우량계명구청 코드구청명10분우량자료수집 시각
59917802휘경P108동대문구0.02022-11-09 16:19
490731303갈현1동113은평구0.02022-11-08 02:39
374292401서초구청124서초구0.02022-11-06 10:09
65712801동대문구청108동대문구0.02022-11-10 12:39
288311702공항동P117강서구0.02022-11-05 04:09
41262103개포2동101강남구0.02022-11-06 23:29
938091104서소문111중구0.02022-11-14 15:19
128552102흑석P121동작구0.02022-11-02 20:39
270102002개봉2동120구로구0.02022-11-04 21:49
4192101동작구청121동작구0.02022-11-01 01:29