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 8837 (88.4%) zerosZeros

Reproduction

Analysis started2023-12-11 08:26:04.770484
Analysis finished2023-12-11 08:26:06.737275
Duration1.97 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%
Mean1313.6653
Minimum101
Maximum2502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:26:06.848255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile103
Q1702
median1302
Q32001
95-th percentile2402
Maximum2502
Range2401
Interquartile range (IQR)1299

Descriptive statistics

Standard deviation733.54094
Coefficient of variation (CV)0.55839257
Kurtosis-1.2013418
Mean1313.6653
Median Absolute Deviation (MAD)600
Skewness-0.052770169
Sum13136653
Variance538082.31
MonotonicityNot monotonic
2023-12-11T17:26:07.048233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
2001 241
 
2.4%
702 236
 
2.4%
401 234
 
2.3%
2501 229
 
2.3%
801 228
 
2.3%
901 228
 
2.3%
902 228
 
2.3%
202 227
 
2.3%
1801 226
 
2.3%
1701 223
 
2.2%
Other values (38) 7700
77.0%
ValueCountFrequency (%)
101 211
2.1%
102 204
2.0%
103 185
1.8%
201 211
2.1%
202 227
2.3%
301 197
2.0%
401 234
2.3%
402 203
2.0%
501 195
1.9%
601 209
2.1%
ValueCountFrequency (%)
2502 203
2.0%
2501 229
2.3%
2402 204
2.0%
2401 216
2.2%
2302 218
2.2%
2301 206
2.1%
2202 200
2.0%
2201 205
2.1%
2102 179
1.8%
2101 194
1.9%

강우량계명
Categorical

HIGH CORRELATION 

Distinct48
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
구로구청
 
241
면목P
 
236
노원구청
 
234
송파구청
 
229
동대문구청
 
228
Other values (43)
8832 

Length

Max length5
Median length4
Mean length3.7921
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row도림2동P
2nd row반포P
3rd row구로구청
4th row동대문구청
5th row동작구청

Common Values

ValueCountFrequency (%)
구로구청 241
 
2.4%
면목P 236
 
2.4%
노원구청 234
 
2.3%
송파구청 229
 
2.3%
동대문구청 228
 
2.3%
성동구청 228
 
2.3%
뚝섬P 228
 
2.3%
고덕2동 227
 
2.3%
양천구청 226
 
2.3%
강서구청 223
 
2.2%
Other values (38) 7700
77.0%

Length

2023-12-11T17:26:07.277424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
구로구청 241
 
2.4%
면목p 236
 
2.4%
노원구청 234
 
2.3%
송파구청 229
 
2.3%
동대문구청 228
 
2.3%
성동구청 228
 
2.3%
뚝섬p 228
 
2.3%
고덕2동 227
 
2.3%
양천구청 226
 
2.3%
강서구청 223
 
2.2%
Other values (38) 7700
77.0%

구청 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.1211
Minimum101
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:26:07.489784image/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 deviation7.3357765
Coefficient of variation (CV)0.064848878
Kurtosis-1.2012105
Mean113.1211
Median Absolute Deviation (MAD)6
Skewness-0.052698355
Sum1131211
Variance53.813616
MonotonicityNot monotonic
2023-12-11T17:26:07.678071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
113 611
 
6.1%
101 600
 
6.0%
109 456
 
4.6%
120 452
 
4.5%
107 447
 
4.5%
102 438
 
4.4%
104 437
 
4.4%
125 432
 
4.3%
118 429
 
4.3%
117 428
 
4.3%
Other values (15) 5270
52.7%
ValueCountFrequency (%)
101 600
6.0%
102 438
4.4%
103 197
 
2.0%
104 437
4.4%
105 195
 
1.9%
106 406
4.1%
107 447
4.5%
108 419
4.2%
109 456
4.6%
110 407
4.1%
ValueCountFrequency (%)
125 432
4.3%
124 420
4.2%
123 424
4.2%
122 405
4.0%
121 373
3.7%
120 452
4.5%
119 409
4.1%
118 429
4.3%
117 428
4.3%
116 409
4.1%

구청명
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
은평구
 
611
강남구
 
600
성동구
 
456
구로구
 
452
중랑구
 
447
Other values (20)
7434 

Length

Max length4
Median length3
Mean length3.0629
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영등포구
2nd row서초구
3rd row구로구
4th row동대문구
5th row동작구

Common Values

ValueCountFrequency (%)
은평구 611
 
6.1%
강남구 600
 
6.0%
성동구 456
 
4.6%
구로구 452
 
4.5%
중랑구 447
 
4.5%
강동구 438
 
4.4%
노원구 437
 
4.4%
송파구 432
 
4.3%
양천구 429
 
4.3%
강서구 428
 
4.3%
Other values (15) 5270
52.7%

Length

2023-12-11T17:26:07.876628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
은평구 611
 
6.1%
강남구 600
 
6.0%
성동구 456
 
4.6%
구로구 452
 
4.5%
중랑구 447
 
4.5%
강동구 438
 
4.4%
노원구 437
 
4.4%
송파구 432
 
4.3%
양천구 429
 
4.3%
강서구 428
 
4.3%
Other values (15) 5270
52.7%

10분우량
Real number (ℝ)

ZEROS 

Distinct40
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.22185
Minimum0
Maximum26.5
Zeros8837
Zeros (%)88.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:26:08.049680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum26.5
Range26.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.1850941
Coefficient of variation (CV)5.3418711
Kurtosis157.30383
Mean0.22185
Median Absolute Deviation (MAD)0
Skewness10.864184
Sum2218.5
Variance1.404448
MonotonicityNot monotonic
2023-12-11T17:26:08.234040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0.0 8837
88.4%
0.5 557
 
5.6%
1.0 189
 
1.9%
1.5 115
 
1.1%
2.0 54
 
0.5%
2.5 48
 
0.5%
3.0 32
 
0.3%
3.5 27
 
0.3%
4.0 18
 
0.2%
5.0 16
 
0.2%
Other values (30) 107
 
1.1%
ValueCountFrequency (%)
0.0 8837
88.4%
0.5 557
 
5.6%
1.0 189
 
1.9%
1.5 115
 
1.1%
2.0 54
 
0.5%
2.5 48
 
0.5%
3.0 32
 
0.3%
3.5 27
 
0.3%
4.0 18
 
0.2%
4.5 14
 
0.1%
ValueCountFrequency (%)
26.5 1
 
< 0.1%
25.5 1
 
< 0.1%
25.0 1
 
< 0.1%
23.5 1
 
< 0.1%
21.5 1
 
< 0.1%
19.0 2
< 0.1%
18.5 1
 
< 0.1%
17.5 1
 
< 0.1%
16.0 1
 
< 0.1%
15.5 4
< 0.1%

자료수집 시각
Date

Distinct2119
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-08-01 00:09:00
Maximum2022-08-15 16:19:00
2023-12-11T17:26:08.431223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:08.610688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-11T17:26:06.040700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:05.290778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:05.651066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:06.163392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:05.405510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:05.765860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:06.313890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:05.529540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:05.902035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T17:26:08.746292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계 코드강우량계명구청 코드구청명10분우량
강우량계 코드1.0001.0001.0001.0000.060
강우량계명1.0001.0001.0001.0000.052
구청 코드1.0001.0001.0001.0000.056
구청명1.0001.0001.0001.0000.039
10분우량0.0600.0520.0560.0391.000
2023-12-11T17:26:08.881217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계명구청명
강우량계명1.0000.999
구청명0.9991.000
2023-12-11T17:26:09.003776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계 코드구청 코드10분우량강우량계명구청명
강우량계 코드1.0000.9990.0040.9980.983
구청 코드0.9991.0000.0050.9980.999
10분우량0.0040.0051.0000.0180.014
강우량계명0.9980.9980.0181.0000.999
구청명0.9830.9990.0140.9991.000

Missing values

2023-12-11T17:26:06.507557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T17:26:06.661013image/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
37311902도림2동P119영등포구0.02022-08-01 12:59
903612402반포P124서초구0.02022-08-14 06:49
767182001구로구청120구로구0.02022-08-12 06:49
61256801동대문구청108동대문구3.02022-08-10 00:09
268942101동작구청121동작구0.02022-08-04 22:59
450841104서소문111중구0.02022-08-07 14:59
79033202고덕2동102강동구0.02022-08-12 14:49
159582001구로구청120구로구1.02022-08-03 07:44
262712102흑석P121동작구0.02022-08-04 20:49
396592101동작구청121동작구0.02022-08-06 19:59
강우량계 코드강우량계명구청 코드구청명10분우량자료수집 시각
122752402반포P124서초구0.02022-08-02 18:59
89408602상월곡동106성북구0.02022-08-14 03:29
492472502마천2동125송파구0.02022-08-08 05:29
130511301은평구청113은평구0.02022-08-02 21:49
30601101강남구청101강남구0.02022-08-05 11:59
944521302증산P113은평구0.02022-08-14 21:09
45398901성동구청109성동구0.02022-08-07 16:09
111312401서초구청124서초구0.02022-08-02 14:39
20699602상월곡동106성북구0.02022-08-04 00:39
60793701중랑구청107중랑구0.02022-08-09 22:29