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 (98.5%)Imbalance

Reproduction

Analysis started2023-12-11 08:25:50.280420
Analysis finished2023-12-11 08:25:51.327318
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

강우량계 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1294.7169
Minimum101
Maximum2502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:25:51.419884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile103
Q1701
median1303
Q31902
95-th percentile2401
Maximum2502
Range2401
Interquartile range (IQR)1201

Descriptive statistics

Standard deviation734.9671
Coefficient of variation (CV)0.56766626
Kurtosis-1.1995759
Mean1294.7169
Median Absolute Deviation (MAD)601
Skewness-0.040488321
Sum12947169
Variance540176.64
MonotonicityNot monotonic
2023-12-11T17:25:51.619633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
1702 249
 
2.5%
2001 242
 
2.4%
2302 242
 
2.4%
103 241
 
2.4%
1303 241
 
2.4%
1201 239
 
2.4%
1901 239
 
2.4%
1401 238
 
2.4%
2401 238
 
2.4%
801 236
 
2.4%
Other values (36) 7595
75.9%
ValueCountFrequency (%)
101 216
2.2%
102 228
2.3%
103 241
2.4%
201 233
2.3%
202 204
2.0%
301 233
2.3%
401 203
2.0%
402 220
2.2%
501 133
1.3%
601 220
2.2%
ValueCountFrequency (%)
2502 206
2.1%
2501 226
2.3%
2402 52
 
0.5%
2401 238
2.4%
2302 242
2.4%
2301 231
2.3%
2202 229
2.3%
2201 227
2.3%
2102 216
2.2%
2101 221
2.2%

강우량계명
Categorical

HIGH CORRELATION 

Distinct46
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
공항동P
 
249
신림P
 
242
구로구청
 
242
개포2동
 
241
갈현1동
 
241
Other values (41)
8785 

Length

Max length5
Median length4
Mean length3.8282
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row뚝섬P
2nd row영등포구청
3rd row개포2동
4th row중랑구청
5th row마천2동

Common Values

ValueCountFrequency (%)
공항동P 249
 
2.5%
신림P 242
 
2.4%
구로구청 242
 
2.4%
개포2동 241
 
2.4%
갈현1동 241
 
2.4%
광진구청 239
 
2.4%
영등포구청 239
 
2.4%
서대문구청 238
 
2.4%
서초구청 238
 
2.4%
동대문구청 236
 
2.4%
Other values (36) 7595
75.9%

Length

2023-12-11T17:25:51.802617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
공항동p 249
 
2.5%
구로구청 242
 
2.4%
신림p 242
 
2.4%
개포2동 241
 
2.4%
갈현1동 241
 
2.4%
광진구청 239
 
2.4%
영등포구청 239
 
2.4%
서대문구청 238
 
2.4%
서초구청 238
 
2.4%
동대문구청 236
 
2.4%
Other values (36) 7595
75.9%

구청 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.9318
Minimum101
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:25:51.955020image/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 deviation7.3503845
Coefficient of variation (CV)0.065086933
Kurtosis-1.1994024
Mean112.9318
Median Absolute Deviation (MAD)6
Skewness-0.040462676
Sum1129318
Variance54.028152
MonotonicityNot monotonic
2023-12-11T17:25:52.145169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
101 685
 
6.9%
117 481
 
4.8%
123 473
 
4.7%
119 473
 
4.7%
113 459
 
4.6%
122 456
 
4.6%
110 443
 
4.4%
108 443
 
4.4%
102 437
 
4.4%
121 437
 
4.4%
Other values (15) 5213
52.1%
ValueCountFrequency (%)
101 685
6.9%
102 437
4.4%
103 233
 
2.3%
104 423
4.2%
105 133
 
1.3%
106 430
4.3%
107 435
4.3%
108 443
4.4%
109 431
4.3%
110 443
4.4%
ValueCountFrequency (%)
125 432
4.3%
124 290
2.9%
123 473
4.7%
122 456
4.6%
121 437
4.4%
120 242
2.4%
119 473
4.7%
118 410
4.1%
117 481
4.8%
116 415
4.2%

구청명
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
강남구
 
685
강서구
 
481
관악구
 
473
영등포구
 
473
은평구
 
459
Other values (20)
7429 

Length

Max length4
Median length3
Mean length3.0718
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row성동구
2nd row영등포구
3rd row강남구
4th row중랑구
5th row송파구

Common Values

ValueCountFrequency (%)
강남구 685
 
6.9%
강서구 481
 
4.8%
관악구 473
 
4.7%
영등포구 473
 
4.7%
은평구 459
 
4.6%
금천구 456
 
4.6%
종로구 443
 
4.4%
동대문구 443
 
4.4%
동작구 437
 
4.4%
강동구 437
 
4.4%
Other values (15) 5213
52.1%

Length

2023-12-11T17:25:52.298382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강남구 685
 
6.9%
강서구 481
 
4.8%
관악구 473
 
4.7%
영등포구 473
 
4.7%
은평구 459
 
4.6%
금천구 456
 
4.6%
종로구 443
 
4.4%
동대문구 443
 
4.4%
동작구 437
 
4.4%
강동구 437
 
4.4%
Other values (15) 5213
52.1%

10분우량
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0.0
9986 
0.5
 
14

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 9986
99.9%
0.5 14
 
0.1%

Length

2023-12-11T17:25:52.479522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:25:52.612413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 9986
99.9%
0.5 14
 
0.1%

자료수집 시각
Date

Distinct2258
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-02-03 09:59:00
Maximum2022-02-18 22:49:00
2023-12-11T17:25:52.751452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:53.219159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-11T17:25:50.890721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:50.701922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:50.989658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:50.800703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T17:25:53.349658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계 코드강우량계명구청 코드구청명10분우량
강우량계 코드1.0001.0001.0001.0000.022
강우량계명1.0001.0001.0001.0000.000
구청 코드1.0001.0001.0001.0000.015
구청명1.0001.0001.0001.0000.000
10분우량0.0220.0000.0150.0001.000
2023-12-11T17:25:53.471029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
10분우량강우량계명구청명
10분우량1.0000.0000.000
강우량계명0.0001.0000.999
구청명0.0000.9991.000
2023-12-11T17:25:53.592244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계 코드구청 코드강우량계명구청명10분우량
강우량계 코드1.0000.9990.9980.9850.017
구청 코드0.9991.0000.9980.9990.011
강우량계명0.9980.9981.0000.9990.000
구청명0.9850.9990.9991.0000.000
10분우량0.0170.0110.0000.0001.000

Missing values

2023-12-11T17:25:51.139665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T17:25:51.275272image/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
73654902뚝섬P109성동구0.02022-02-14 21:09
114951901영등포구청119영등포구0.02022-02-05 04:49
8989103개포2동101강남구0.02022-02-04 19:39
24016701중랑구청107중랑구0.02022-02-07 03:19
201912502마천2동125송파구0.02022-02-06 12:59
57655101강남구청101강남구0.02022-02-12 08:39
20348902뚝섬P109성동구0.02022-02-06 13:39
722822301관악구청123관악구0.02022-02-14 15:59
66403701중랑구청107중랑구0.02022-02-13 17:49
512942202가산2P122금천구0.02022-02-11 08:39
강우량계 코드강우량계명구청 코드구청명10분우량자료수집 시각
757482502마천2동125송파구0.02022-02-15 04:59
176251801양천구청118양천구0.02022-02-06 03:29
259741303갈현1동113은평구0.02022-02-07 10:29
954351901영등포구청119영등포구0.02022-02-18 05:49
35078702면목P107중랑구0.02022-02-08 20:29
302302401서초구청124서초구0.02022-02-08 02:19
180071701강서구청117강서구0.02022-02-06 04:59
27169802휘경P108동대문구0.02022-02-07 14:59
906482201금천구청122금천구0.02022-02-17 12:09
35069201강동구청102강동구0.02022-02-08 20:29