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 9652 (96.5%) zerosZeros

Reproduction

Analysis started2023-12-11 08:25:59.546034
Analysis finished2023-12-11 08:26:01.272694
Duration1.73 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%
Mean1318.7294
Minimum101
Maximum2502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:26:01.372711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile103
Q1701
median1303
Q31902
95-th percentile2402
Maximum2502
Range2401
Interquartile range (IQR)1201

Descriptive statistics

Standard deviation731.08685
Coefficient of variation (CV)0.55438732
Kurtosis-1.1931448
Mean1318.7294
Median Absolute Deviation (MAD)602
Skewness-0.072781214
Sum13187294
Variance534487.99
MonotonicityNot monotonic
2023-12-11T17:26:01.541337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
102 236
 
2.4%
1303 235
 
2.4%
901 234
 
2.3%
1502 233
 
2.3%
2301 231
 
2.3%
2102 229
 
2.3%
1302 229
 
2.3%
1902 227
 
2.3%
301 226
 
2.3%
2302 226
 
2.3%
Other values (38) 7694
76.9%
ValueCountFrequency (%)
101 169
1.7%
102 236
2.4%
103 206
2.1%
201 201
2.0%
202 189
1.9%
301 226
2.3%
401 215
2.1%
402 213
2.1%
501 216
2.2%
601 221
2.2%
ValueCountFrequency (%)
2502 215
2.1%
2501 172
1.7%
2402 210
2.1%
2401 214
2.1%
2302 226
2.3%
2301 231
2.3%
2202 221
2.2%
2201 218
2.2%
2102 229
2.3%
2101 196
2.0%

강우량계명
Categorical

HIGH CORRELATION 

Distinct48
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
세곡동
 
236
갈현1동
 
235
성동구청
 
234
봉원P
 
233
관악구청
 
231
Other values (43)
8831 

Length

Max length5
Median length4
Mean length3.787
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강서구청
2nd row반포P
3rd row동작구청
4th row동대문구청
5th row금천구청

Common Values

ValueCountFrequency (%)
세곡동 236
 
2.4%
갈현1동 235
 
2.4%
성동구청 234
 
2.3%
봉원P 233
 
2.3%
관악구청 231
 
2.3%
흑석P 229
 
2.3%
증산P 229
 
2.3%
도림2동P 227
 
2.3%
도봉구청 226
 
2.3%
신림P 226
 
2.3%
Other values (38) 7694
76.9%

Length

2023-12-11T17:26:01.716306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
세곡동 236
 
2.4%
갈현1동 235
 
2.4%
성동구청 234
 
2.3%
봉원p 233
 
2.3%
관악구청 231
 
2.3%
흑석p 229
 
2.3%
증산p 229
 
2.3%
도림2동p 227
 
2.3%
도봉구청 226
 
2.3%
신림p 226
 
2.3%
Other values (38) 7694
76.9%

구청 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.1716
Minimum101
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:26:01.853537image/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 deviation7.3112447
Coefficient of variation (CV)0.064603175
Kurtosis-1.1929862
Mean113.1716
Median Absolute Deviation (MAD)6
Skewness-0.072744198
Sum1131716
Variance53.454299
MonotonicityNot monotonic
2023-12-11T17:26:02.007432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
113 678
 
6.8%
101 611
 
6.1%
123 457
 
4.6%
115 448
 
4.5%
119 442
 
4.4%
122 439
 
4.4%
106 433
 
4.3%
104 428
 
4.3%
117 427
 
4.3%
109 425
 
4.2%
Other values (15) 5212
52.1%
ValueCountFrequency (%)
101 611
6.1%
102 390
3.9%
103 226
 
2.3%
104 428
4.3%
105 216
 
2.2%
106 433
4.3%
107 403
4.0%
108 366
3.7%
109 425
4.2%
110 401
4.0%
ValueCountFrequency (%)
125 387
3.9%
124 424
4.2%
123 457
4.6%
122 439
4.4%
121 425
4.2%
120 356
3.6%
119 442
4.4%
118 398
4.0%
117 427
4.3%
116 417
4.2%

구청명
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
은평구
 
678
강남구
 
611
관악구
 
457
마포구
 
448
영등포구
 
442
Other values (20)
7364 

Length

Max length4
Median length3
Mean length3.0571
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강서구
2nd row서초구
3rd row동작구
4th row동대문구
5th row금천구

Common Values

ValueCountFrequency (%)
은평구 678
 
6.8%
강남구 611
 
6.1%
관악구 457
 
4.6%
마포구 448
 
4.5%
영등포구 442
 
4.4%
금천구 439
 
4.4%
성북구 433
 
4.3%
노원구 428
 
4.3%
강서구 427
 
4.3%
성동구 425
 
4.2%
Other values (15) 5212
52.1%

Length

2023-12-11T17:26:02.153198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
은평구 678
 
6.8%
강남구 611
 
6.1%
관악구 457
 
4.6%
마포구 448
 
4.5%
영등포구 442
 
4.4%
금천구 439
 
4.4%
성북구 433
 
4.3%
노원구 428
 
4.3%
강서구 427
 
4.3%
성동구 425
 
4.2%
Other values (15) 5212
52.1%

10분우량
Real number (ℝ)

ZEROS 

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.06755
Minimum0
Maximum17.5
Zeros9652
Zeros (%)96.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:26:02.279952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum17.5
Range17.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.55699463
Coefficient of variation (CV)8.2456644
Kurtosis240.08281
Mean0.06755
Median Absolute Deviation (MAD)0
Skewness13.428161
Sum675.5
Variance0.31024302
MonotonicityNot monotonic
2023-12-11T17:26:02.724948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0.0 9652
96.5%
0.5 144
 
1.4%
1.0 71
 
0.7%
1.5 22
 
0.2%
2.0 20
 
0.2%
3.0 14
 
0.1%
2.5 14
 
0.1%
4.0 12
 
0.1%
5.0 9
 
0.1%
5.5 7
 
0.1%
Other values (13) 35
 
0.4%
ValueCountFrequency (%)
0.0 9652
96.5%
0.5 144
 
1.4%
1.0 71
 
0.7%
1.5 22
 
0.2%
2.0 20
 
0.2%
2.5 14
 
0.1%
3.0 14
 
0.1%
3.5 4
 
< 0.1%
4.0 12
 
0.1%
4.5 4
 
< 0.1%
ValueCountFrequency (%)
17.5 1
 
< 0.1%
13.5 1
 
< 0.1%
10.5 1
 
< 0.1%
9.5 2
 
< 0.1%
9.0 2
 
< 0.1%
8.5 2
 
< 0.1%
8.0 2
 
< 0.1%
7.5 2
 
< 0.1%
7.0 5
0.1%
6.5 7
0.1%

자료수집 시각
Date

Distinct2112
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-07-01 00:09:00
Maximum2022-07-15 23:49:00
2023-12-11T17:26:02.895999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:03.071937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-11T17:26:00.699685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:00.085761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:00.384561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:00.788938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:00.184755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:00.491683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:00.885756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:00.281983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:26:00.593999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T17:26:03.173946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계 코드강우량계명구청 코드구청명10분우량
강우량계 코드1.0001.0001.0001.0000.015
강우량계명1.0001.0001.0001.0000.058
구청 코드1.0001.0001.0001.0000.000
구청명1.0001.0001.0001.0000.039
10분우량0.0150.0580.0000.0391.000
2023-12-11T17:26:03.283954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계명구청명
강우량계명1.0000.999
구청명0.9991.000
2023-12-11T17:26:03.378488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계 코드구청 코드10분우량강우량계명구청명
강우량계 코드1.0000.999-0.0020.9980.982
구청 코드0.9991.000-0.0020.9980.999
10분우량-0.002-0.0021.0000.0260.018
강우량계명0.9980.9980.0261.0000.999
구청명0.9820.9990.0180.9991.000

Missing values

2023-12-11T17:26:01.062343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T17:26:01.202007image/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
596691701강서구청117강서구0.02022-07-10 00:39
71552402반포P124서초구0.02022-07-02 01:29
655002101동작구청121동작구0.02022-07-10 20:59
88921801동대문구청108동대문구0.02022-07-14 07:39
385292201금천구청122금천구0.02022-07-06 18:39
41801602한남P116용산구0.02022-07-01 14:59
80692302신림P123관악구0.02022-07-02 04:49
53656501강북구청105강북구0.02022-07-08 23:19
22911902도림2동P119영등포구0.02022-07-01 08:09
833761303갈현1동113은평구0.02022-07-13 12:29
강우량계 코드강우량계명구청 코드구청명10분우량자료수집 시각
332831104서소문111중구0.02022-07-06 00:29
52455102세곡동101강남구0.02022-07-08 19:09
183571602한남P116용산구0.02022-07-03 18:29
117091702공항동P117강서구0.02022-07-02 17:39
55311301은평구청113은평구0.02022-07-01 19:49
11476501강북구청105강북구0.02022-07-02 16:49
91587801동대문구청108동대문구0.02022-07-14 16:59
73159402상계1동104노원구0.02022-07-12 00:09
46747301도봉구청103도봉구0.02022-07-07 23:19
551882501송파구청125송파구0.02022-07-09 04:29