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 (94.9%)Imbalance

Reproduction

Analysis started2023-12-11 08:24:50.749518
Analysis finished2023-12-11 08:24:52.195607
Duration1.45 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%
Mean1221.3305
Minimum101
Maximum2502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:24:52.312076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile102
Q1601
median1104
Q31801
95-th percentile2402
Maximum2502
Range2401
Interquartile range (IQR)1200

Descriptive statistics

Standard deviation738.76314
Coefficient of variation (CV)0.60488389
Kurtosis-1.1302261
Mean1221.3305
Median Absolute Deviation (MAD)598
Skewness0.1493472
Sum12213305
Variance545770.97
MonotonicityNot monotonic
2023-12-11T17:24:52.555751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
402 376
 
3.8%
2302 303
 
3.0%
101 283
 
2.8%
201 276
 
2.8%
2002 272
 
2.7%
802 268
 
2.7%
1801 264
 
2.6%
1602 259
 
2.6%
102 254
 
2.5%
2502 254
 
2.5%
Other values (38) 7191
71.9%
ValueCountFrequency (%)
101 283
2.8%
102 254
2.5%
103 206
2.1%
201 276
2.8%
202 220
2.2%
301 210
2.1%
401 224
2.2%
402 376
3.8%
501 233
2.3%
601 250
2.5%
ValueCountFrequency (%)
2502 254
2.5%
2501 240
2.4%
2402 226
2.3%
2401 238
2.4%
2302 303
3.0%
2301 43
 
0.4%
2202 220
2.2%
2201 57
 
0.6%
2102 19
 
0.2%
2101 18
 
0.2%

강우량계명
Categorical

HIGH CORRELATION 

Distinct48
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
상계1동
 
376
신림P
 
303
강남구청
 
283
강동구청
 
276
개봉2동
 
272
Other values (43)
8490 

Length

Max length5
Median length4
Mean length3.7339
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강남구청
2nd row서대문구청
3rd row중구청
4th row개봉2동
5th row양천구청

Common Values

ValueCountFrequency (%)
상계1동 376
 
3.8%
신림P 303
 
3.0%
강남구청 283
 
2.8%
강동구청 276
 
2.8%
개봉2동 272
 
2.7%
휘경P 268
 
2.7%
양천구청 264
 
2.6%
한남P 259
 
2.6%
세곡동 254
 
2.5%
마천2동 254
 
2.5%
Other values (38) 7191
71.9%

Length

2023-12-11T17:24:52.835078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
상계1동 376
 
3.8%
신림p 303
 
3.0%
강남구청 283
 
2.8%
강동구청 276
 
2.8%
개봉2동 272
 
2.7%
휘경p 268
 
2.7%
양천구청 264
 
2.6%
한남p 259
 
2.6%
세곡동 254
 
2.5%
마천2동 254
 
2.5%
Other values (38) 7191
71.9%

구청 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.1974
Minimum101
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T17:24:53.009691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1106
median111
Q3118
95-th percentile124
Maximum125
Range24
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.3875768
Coefficient of variation (CV)0.065844456
Kurtosis-1.1300461
Mean112.1974
Median Absolute Deviation (MAD)6
Skewness0.14937534
Sum1121974
Variance54.576291
MonotonicityNot monotonic
2023-12-11T17:24:53.214700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
101 743
 
7.4%
104 600
 
6.0%
120 522
 
5.2%
108 498
 
5.0%
102 496
 
5.0%
125 494
 
4.9%
116 490
 
4.9%
118 489
 
4.9%
107 472
 
4.7%
124 464
 
4.6%
Other values (15) 4732
47.3%
ValueCountFrequency (%)
101 743
7.4%
102 496
5.0%
103 210
 
2.1%
104 600
6.0%
105 233
 
2.3%
106 372
3.7%
107 472
4.7%
108 498
5.0%
109 458
4.6%
110 461
4.6%
ValueCountFrequency (%)
125 494
4.9%
124 464
4.6%
123 346
3.5%
122 277
2.8%
121 37
 
0.4%
120 522
5.2%
119 29
 
0.3%
118 489
4.9%
117 462
4.6%
116 490
4.9%

구청명
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
강남구
743 
노원구
 
600
구로구
 
522
동대문구
 
498
강동구
 
496
Other values (20)
7141 

Length

Max length4
Median length3
Mean length3.029
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강남구
2nd row서대문구
3rd row중구
4th row구로구
5th row양천구

Common Values

ValueCountFrequency (%)
강남구 743
 
7.4%
노원구 600
 
6.0%
구로구 522
 
5.2%
동대문구 498
 
5.0%
강동구 496
 
5.0%
송파구 494
 
4.9%
용산구 490
 
4.9%
양천구 489
 
4.9%
중랑구 472
 
4.7%
서초구 464
 
4.6%
Other values (15) 4732
47.3%

Length

2023-12-11T17:24:53.435462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강남구 743
 
7.4%
노원구 600
 
6.0%
구로구 522
 
5.2%
동대문구 498
 
5.0%
강동구 496
 
5.0%
송파구 494
 
4.9%
용산구 490
 
4.9%
양천구 489
 
4.9%
중랑구 472
 
4.7%
서초구 464
 
4.6%
Other values (15) 4732
47.3%

10분우량
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0.0
9870 
0.5
 
126
34.5
 
3
1.0
 
1

Length

Max length4
Median length3
Mean length3.0003
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 9870
98.7%
0.5 126
 
1.3%
34.5 3
 
< 0.1%
1.0 1
 
< 0.1%

Length

2023-12-11T17:24:53.625195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:24:53.765254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 9870
98.7%
0.5 126
 
1.3%
34.5 3
 
< 0.1%
1.0 1
 
< 0.1%

자료수집 시각
Date

Distinct2701
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-01-01 01:19:00
Maximum2021-01-29 23:59:00
2023-12-11T17:24:53.914864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:24:54.148598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-11T17:24:51.587022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:24:51.311349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:24:51.730540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:24:51.438556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T17:24:54.292191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계 코드강우량계명구청 코드구청명10분우량
강우량계 코드1.0001.0001.0001.0000.045
강우량계명1.0001.0001.0001.0000.068
구청 코드1.0001.0001.0001.0000.043
구청명1.0001.0001.0001.0000.065
10분우량0.0450.0680.0430.0651.000
2023-12-11T17:24:54.426470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
10분우량강우량계명구청명
10분우량1.0000.0330.035
강우량계명0.0331.0000.999
구청명0.0350.9991.000
2023-12-11T17:24:54.553272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량계 코드구청 코드강우량계명구청명10분우량
강우량계 코드1.0000.9990.9980.9970.027
구청 코드0.9991.0000.9980.9990.026
강우량계명0.9980.9981.0000.9990.033
구청명0.9970.9990.9991.0000.035
10분우량0.0270.0260.0330.0351.000

Missing values

2023-12-11T17:24:51.955906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T17:24:52.120789image/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
26745101강남구청101강남구0.02021-01-17 05:09
525481401서대문구청114서대문구0.02021-01-21 20:49
502221101중구청111중구0.02021-01-21 11:09
710452002개봉2동120구로구0.02021-01-25 01:19
949551801양천구청118양천구0.02021-01-28 22:09
33840201강동구청102강동구0.02021-01-18 10:39
76842201강동구청102강동구0.02021-01-26 00:49
64221104서소문111중구0.02021-01-13 14:09
2748402상계1동104노원구0.02021-01-11 03:29
896541302증산P113은평구0.02021-01-28 02:49
강우량계 코드강우량계명구청 코드구청명10분우량자료수집 시각
158632402반포P124서초구0.02021-01-15 07:19
108442401서초구청124서초구0.02021-01-14 09:09
831971802목동P118양천구0.02021-01-27 01:49
56647501강북구청105강북구0.02021-01-22 13:59
94634801동대문구청108동대문구0.02021-01-28 20:59
1562402상계1동104노원구0.02021-01-09 00:59
177841303갈현1동113은평구0.02021-01-15 15:19
10146201강동구청102강동구0.02021-01-14 06:19
9468101강남구청101강남구0.02021-01-14 03:09
88321101중구청111중구0.02021-01-14 00:29