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 (99.3%)Imbalance

Reproduction

Analysis started2023-12-11 08:25:54.689567
Analysis finished2023-12-11 08:25:56.031629
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

강우량계 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1240.4411
Minimum101
Maximum2502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:25:56.137625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile102
Q1602
median1201
Q31802
95-th percentile2501
Maximum2502
Range2401
Interquartile range (IQR)1200

Descriptive statistics

Standard deviation756.03447
Coefficient of variation (CV)0.60948841
Kurtosis-1.1793258
Mean1240.4411
Median Absolute Deviation (MAD)600
Skewness0.16872251
Sum12404411
Variance571588.13
MonotonicityNot monotonic
2023-12-11T17:25:56.355499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1802 495
 
5.0%
2501 488
 
4.9%
701 481
 
4.8%
2101 473
 
4.7%
2102 466
 
4.7%
201 462
 
4.6%
101 461
 
4.6%
2502 452
 
4.5%
602 452
 
4.5%
1602 452
 
4.5%
Other values (27) 5318
53.2%
ValueCountFrequency (%)
101 461
4.6%
102 157
 
1.6%
201 462
4.6%
202 178
 
1.8%
301 185
1.8%
401 164
 
1.6%
402 200
2.0%
501 174
 
1.7%
601 450
4.5%
602 452
4.5%
ValueCountFrequency (%)
2502 452
4.5%
2501 488
4.9%
2401 188
 
1.9%
2301 177
 
1.8%
2102 466
4.7%
2101 473
4.7%
2001 88
 
0.9%
1802 495
5.0%
1701 163
 
1.6%
1602 452
4.5%

강우량계명
Categorical

HIGH CORRELATION 

Distinct37
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
목동P
 
495
송파구청
 
488
중랑구청
 
481
동작구청
 
473
흑석P
 
466
Other values (32)
7597 

Length

Max length5
Median length4
Mean length3.7603
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row송파구청
2nd row목동P
3rd row성북구청
4th row세곡동
5th row한남P

Common Values

ValueCountFrequency (%)
목동P 495
 
5.0%
송파구청 488
 
4.9%
중랑구청 481
 
4.8%
동작구청 473
 
4.7%
흑석P 466
 
4.7%
강동구청 462
 
4.6%
강남구청 461
 
4.6%
마천2동 452
 
4.5%
상월곡동 452
 
4.5%
한남P 452
 
4.5%
Other values (27) 5318
53.2%

Length

2023-12-11T17:25:56.568193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
목동p 495
 
5.0%
송파구청 488
 
4.9%
중랑구청 481
 
4.8%
동작구청 473
 
4.7%
흑석p 466
 
4.7%
강동구청 462
 
4.6%
강남구청 461
 
4.6%
상월곡동 452
 
4.5%
한남p 452
 
4.5%
마천2동 452
 
4.5%
Other values (27) 5318
53.2%

구청 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.3898
Minimum101
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:25:56.754021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1106
median112
Q3118
95-th percentile125
Maximum125
Range24
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.5599187
Coefficient of variation (CV)0.067265168
Kurtosis-1.1792375
Mean112.3898
Median Absolute Deviation (MAD)6
Skewness0.16909957
Sum1123898
Variance57.152371
MonotonicityNot monotonic
2023-12-11T17:25:56.936337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
125 940
 
9.4%
121 939
 
9.4%
106 902
 
9.0%
116 891
 
8.9%
107 643
 
6.4%
102 640
 
6.4%
101 618
 
6.2%
118 495
 
5.0%
112 426
 
4.3%
108 387
 
3.9%
Other values (13) 3119
31.2%
ValueCountFrequency (%)
101 618
6.2%
102 640
6.4%
103 185
 
1.8%
104 364
3.6%
105 174
 
1.7%
106 902
9.0%
107 643
6.4%
108 387
3.9%
109 167
 
1.7%
110 367
3.7%
ValueCountFrequency (%)
125 940
9.4%
124 188
 
1.9%
123 177
 
1.8%
121 939
9.4%
120 88
 
0.9%
118 495
5.0%
117 163
 
1.6%
116 891
8.9%
115 343
 
3.4%
114 170
 
1.7%

구청명
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
송파구
940 
동작구
939 
성북구
902 
용산구
891 
중랑구
643 
Other values (18)
5685 

Length

Max length4
Median length3
Mean length3.0193
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row송파구
2nd row양천구
3rd row성북구
4th row강남구
5th row용산구

Common Values

ValueCountFrequency (%)
송파구 940
 
9.4%
동작구 939
 
9.4%
성북구 902
 
9.0%
용산구 891
 
8.9%
중랑구 643
 
6.4%
강동구 640
 
6.4%
강남구 618
 
6.2%
양천구 495
 
5.0%
광진구 426
 
4.3%
동대문구 387
 
3.9%
Other values (13) 3119
31.2%

Length

2023-12-11T17:25:57.152287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
송파구 940
 
9.4%
동작구 939
 
9.4%
성북구 902
 
9.0%
용산구 891
 
8.9%
중랑구 643
 
6.4%
강동구 640
 
6.4%
강남구 618
 
6.2%
양천구 495
 
5.0%
광진구 426
 
4.3%
동대문구 387
 
3.9%
Other values (13) 3119
31.2%

10분우량
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0.0
9994 
0.5
 
6

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 9994
99.9%
0.5 6
 
0.1%

Length

2023-12-11T17:25:57.338727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:25:57.478397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 9994
99.9%
0.5 6
 
0.1%

자료수집 시각
Date

Distinct3616
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-01-01 00:04:00
Maximum2022-01-31 13:59:00
2023-12-11T17:25:57.613832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:57.819327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-11T17:25:55.496565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:55.210684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:55.631810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:25:55.358660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T17:25:57.947606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계 코드강우량계명구청 코드구청명10분우량
강우량계 코드1.0001.0001.0000.9970.027
강우량계명1.0001.0001.0001.0000.022
구청 코드1.0001.0001.0001.0000.036
구청명0.9971.0001.0001.0000.036
10분우량0.0270.0220.0360.0361.000
2023-12-11T17:25:58.064086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
10분우량강우량계명구청명
10분우량1.0000.0180.031
강우량계명0.0181.0000.999
구청명0.0310.9991.000
2023-12-11T17:25:58.210500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계 코드구청 코드강우량계명구청명10분우량
강우량계 코드1.0000.9990.9990.9870.020
구청 코드0.9991.0000.9990.9990.027
강우량계명0.9990.9991.0000.9990.018
구청명0.9870.9990.9991.0000.031
10분우량0.0200.0270.0180.0311.000

Missing values

2023-12-11T17:25:55.826592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T17:25:55.965614image/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
183352501송파구청125송파구0.02022-01-12 07:29
132631802목동P118양천구0.02022-01-09 13:59
69940601성북구청106성북구0.02022-01-27 15:49
79122102세곡동101강남구0.02022-01-29 11:19
31491602한남P116용산구0.02022-01-04 04:19
710991303갈현1동113은평구0.02022-01-27 22:09
32359402상계1동104노원구0.02022-01-19 18:19
656571501마포구청115마포구0.02022-01-26 18:49
667092102흑석P121동작구0.02022-01-26 23:59
39466202고덕2동102강동구0.02022-01-21 13:59
강우량계 코드강우량계명구청 코드구청명10분우량자료수집 시각
823241401서대문구청114서대문구0.02022-01-30 02:09
85344601성북구청106성북구0.02022-01-30 16:19
59576701중랑구청107중랑구0.02022-01-25 14:39
26450601성북구청106성북구0.02022-01-16 15:39
299702101동작구청121동작구0.02022-01-18 12:39
65199801동대문구청108동대문구0.02022-01-26 16:39
650071104서소문111중구0.02022-01-26 15:49
76503702면목P107중랑구0.02022-01-28 23:09
35092301도봉구청103도봉구0.02022-01-20 17:09
75099902뚝섬P109성동구0.02022-01-28 16:39