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 is highly skewed (γ1 = 94.0015559)Skewed
10분우량 has 9721 (97.2%) zerosZeros

Reproduction

Analysis started2023-12-11 08:24:39.565336
Analysis finished2023-12-11 08:24:41.901959
Duration2.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

강우량계 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1448.6394
Minimum201
Maximum2502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:24:42.008055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201
5-th percentile401
Q1901
median1502
Q32002
95-th percentile2501
Maximum2502
Range2301
Interquartile range (IQR)1101

Descriptive statistics

Standard deviation670.17354
Coefficient of variation (CV)0.46262275
Kurtosis-1.1301167
Mean1448.6394
Median Absolute Deviation (MAD)600
Skewness-0.18110738
Sum14486394
Variance449132.57
MonotonicityNot monotonic
2023-12-11T17:24:42.246284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
2102 292
 
2.9%
1501 285
 
2.9%
402 284
 
2.8%
2302 281
 
2.8%
1601 277
 
2.8%
2201 274
 
2.7%
1701 272
 
2.7%
1702 268
 
2.7%
2002 266
 
2.7%
2202 265
 
2.6%
Other values (35) 7236
72.4%
ValueCountFrequency (%)
201 128
1.3%
202 132
1.3%
301 213
2.1%
401 258
2.6%
402 284
2.8%
501 179
1.8%
601 239
2.4%
602 247
2.5%
701 136
1.4%
702 135
1.4%
ValueCountFrequency (%)
2502 250
2.5%
2501 253
2.5%
2402 149
1.5%
2401 159
1.6%
2302 281
2.8%
2301 254
2.5%
2202 265
2.6%
2201 274
2.7%
2102 292
2.9%
2101 244
2.4%

강우량계명
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
흑석P
 
292
마포구청
 
285
상계1동
 
284
신림P
 
281
용산구청
 
277
Other values (40)
8581 

Length

Max length5
Median length4
Mean length3.8037
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광진구청
2nd row고덕2동
3rd row개봉2동
4th row한남P
5th row서소문

Common Values

ValueCountFrequency (%)
흑석P 292
 
2.9%
마포구청 285
 
2.9%
상계1동 284
 
2.8%
신림P 281
 
2.8%
용산구청 277
 
2.8%
금천구청 274
 
2.7%
강서구청 272
 
2.7%
공항동P 268
 
2.7%
개봉2동 266
 
2.7%
가산2P 265
 
2.6%
Other values (35) 7236
72.4%

Length

2023-12-11T17:24:42.494670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
흑석p 292
 
2.9%
마포구청 285
 
2.9%
상계1동 284
 
2.8%
신림p 281
 
2.8%
용산구청 277
 
2.8%
금천구청 274
 
2.7%
강서구청 272
 
2.7%
공항동p 268
 
2.7%
개봉2동 266
 
2.7%
가산2p 265
 
2.6%
Other values (35) 7236
72.4%

구청 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean114.4712
Minimum102
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:24:42.786562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile104
Q1109
median115
Q3120
95-th percentile125
Maximum125
Range23
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.7016164
Coefficient of variation (CV)0.058544126
Kurtosis-1.1304166
Mean114.4712
Median Absolute Deviation (MAD)6
Skewness-0.18088177
Sum1144712
Variance44.911662
MonotonicityNot monotonic
2023-12-11T17:24:42.964847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
113 766
 
7.7%
104 542
 
5.4%
117 540
 
5.4%
122 539
 
5.4%
121 536
 
5.4%
123 535
 
5.3%
116 527
 
5.3%
115 525
 
5.2%
120 524
 
5.2%
108 507
 
5.1%
Other values (14) 4459
44.6%
ValueCountFrequency (%)
102 260
2.6%
103 213
 
2.1%
104 542
5.4%
105 179
 
1.8%
106 486
4.9%
107 271
2.7%
108 507
5.1%
109 469
4.7%
110 194
 
1.9%
111 288
2.9%
ValueCountFrequency (%)
125 503
5.0%
124 308
3.1%
123 535
5.3%
122 539
5.4%
121 536
5.4%
120 524
5.2%
119 327
3.3%
118 454
4.5%
117 540
5.4%
116 527
5.3%

구청명
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
은평구
766 
노원구
 
542
강서구
 
540
금천구
 
539
동작구
 
536
Other values (19)
7077 

Length

Max length4
Median length3
Mean length3.0802
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광진구
2nd row강동구
3rd row구로구
4th row용산구
5th row중구

Common Values

ValueCountFrequency (%)
은평구 766
 
7.7%
노원구 542
 
5.4%
강서구 540
 
5.4%
금천구 539
 
5.4%
동작구 536
 
5.4%
관악구 535
 
5.3%
용산구 527
 
5.3%
마포구 525
 
5.2%
구로구 524
 
5.2%
동대문구 507
 
5.1%
Other values (14) 4459
44.6%

Length

2023-12-11T17:24:43.169879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
은평구 766
 
7.7%
노원구 542
 
5.4%
강서구 540
 
5.4%
금천구 539
 
5.4%
동작구 536
 
5.4%
관악구 535
 
5.3%
용산구 527
 
5.3%
마포구 525
 
5.2%
구로구 524
 
5.2%
동대문구 507
 
5.1%
Other values (14) 4459
44.6%

10분우량
Real number (ℝ)

SKEWED  ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0272
Minimum0
Maximum65
Zeros9721
Zeros (%)97.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:24:43.331766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum65
Range65
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.66347885
Coefficient of variation (CV)24.392605
Kurtosis9199.9704
Mean0.0272
Median Absolute Deviation (MAD)0
Skewness94.001556
Sum272
Variance0.44020418
MonotonicityNot monotonic
2023-12-11T17:24:43.461380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0.0 9721
97.2%
0.5 161
 
1.6%
1.0 101
 
1.0%
1.5 15
 
0.1%
3.0 1
 
< 0.1%
65.0 1
 
< 0.1%
ValueCountFrequency (%)
0.0 9721
97.2%
0.5 161
 
1.6%
1.0 101
 
1.0%
1.5 15
 
0.1%
3.0 1
 
< 0.1%
65.0 1
 
< 0.1%
ValueCountFrequency (%)
65.0 1
 
< 0.1%
3.0 1
 
< 0.1%
1.5 15
 
0.1%
1.0 101
 
1.0%
0.5 161
 
1.6%
0.0 9721
97.2%

자료수집 시각
Date

Distinct2570
Distinct (%)25.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-03-01 00:09:00
Maximum2021-03-19 03:29:00
2023-12-11T17:24:43.631393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:24:43.831388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-11T17:24:41.103227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:24:40.206927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:24:40.653121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:24:41.276510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:24:40.337159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:24:40.805124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:24:41.432929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:24:40.502945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:24:40.963297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T17:24:43.988003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계 코드강우량계명구청 코드구청명10분우량
강우량계 코드1.0001.0001.0001.0000.000
강우량계명1.0001.0001.0001.0000.057
구청 코드1.0001.0001.0001.0000.000
구청명1.0001.0001.0001.0000.037
10분우량0.0000.0570.0000.0371.000
2023-12-11T17:24:44.128256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계명구청명
강우량계명1.0000.999
구청명0.9991.000
2023-12-11T17:24:44.260459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계 코드구청 코드10분우량강우량계명구청명
강우량계 코드1.0000.999-0.0140.9980.999
구청 코드0.9991.000-0.0140.9980.999
10분우량-0.014-0.0141.0000.0470.029
강우량계명0.9980.9980.0471.0000.999
구청명0.9990.9990.0290.9991.000

Missing values

2023-12-11T17:24:41.633787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T17:24:41.809305image/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
529311201광진구청112광진구0.02021-03-10 12:19
24259202고덕2동102강동구0.02021-03-05 13:47
456572002개봉2동120구로구0.02021-03-09 06:59
511602한남P116용산구0.02021-03-01 00:19
623081104서소문111중구0.02021-03-12 02:09
27488601성북구청106성북구0.02021-03-06 03:09
952551801양천구청118양천구0.02021-03-18 07:59
19921901영등포구청119영등포구1.02021-03-01 10:09
474922001구로구청120구로구0.02021-03-09 14:09
904931601용산구청116용산구0.02021-03-17 11:39
강우량계 코드강우량계명구청 코드구청명10분우량자료수집 시각
549381901영등포구청119영등포구0.02021-03-10 20:29
407332101동작구청121동작구0.02021-03-08 11:39
688381401서대문구청114서대문구0.02021-03-13 05:49
371142002개봉2동120구로구0.02021-03-07 20:09
393491501마포구청115마포구0.02021-03-08 05:39
76208602상월곡동106성북구0.02021-03-14 14:59
612981902도림2동P119영등포구0.02021-03-11 22:09
88761801양천구청118양천구0.02021-03-02 18:19
505731801양천구청118양천구0.02021-03-10 02:39
738591401서대문구청114서대문구0.02021-03-14 04:09