Overview

Dataset statistics

Number of variables4
Number of observations119
Missing cells119
Missing cells (%)25.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory36.1 B

Variable types

Numeric2
Text1
Unsupported1

Dataset

Description공간id,펌프이름,기타,생성일자
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21179/S/1/datasetView.do

Alerts

생성일자 has 119 (100.0%) missing valuesMissing
공간id has unique valuesUnique
펌프이름 has unique valuesUnique
기타 has unique valuesUnique
생성일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-03 21:21:28.273670
Analysis finished2024-05-03 21:21:30.229651
Duration1.96 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공간id
Real number (ℝ)

UNIQUE 

Distinct119
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12534.504
Minimum12271
Maximum12597
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-03T21:21:30.462004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12271
5-th percentile12484.9
Q112508.5
median12538
Q312567.5
95-th percentile12591.1
Maximum12597
Range326
Interquartile range (IQR)59

Descriptive statistics

Standard deviation48.20206
Coefficient of variation (CV)0.0038455498
Kurtosis13.207859
Mean12534.504
Median Absolute Deviation (MAD)30
Skewness-2.6609515
Sum1491606
Variance2323.4385
MonotonicityNot monotonic
2024-05-03T21:21:30.958430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12560 1
 
0.8%
12561 1
 
0.8%
12529 1
 
0.8%
12528 1
 
0.8%
12527 1
 
0.8%
12526 1
 
0.8%
12525 1
 
0.8%
12524 1
 
0.8%
12523 1
 
0.8%
12522 1
 
0.8%
Other values (109) 109
91.6%
ValueCountFrequency (%)
12271 1
0.8%
12272 1
0.8%
12481 1
0.8%
12482 1
0.8%
12483 1
0.8%
12484 1
0.8%
12485 1
0.8%
12486 1
0.8%
12487 1
0.8%
12488 1
0.8%
ValueCountFrequency (%)
12597 1
0.8%
12596 1
0.8%
12595 1
0.8%
12594 1
0.8%
12593 1
0.8%
12592 1
0.8%
12591 1
0.8%
12590 1
0.8%
12589 1
0.8%
12588 1
0.8%

펌프이름
Text

UNIQUE 

Distinct119
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-03T21:21:32.066064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.4453782
Min length2

Characters and Unicode

Total characters291
Distinct characters122
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)100.0%

Sample

1st row용답
2nd row봉원
3rd row중화2
4th row방화
5th row당인
ValueCountFrequency (%)
용답 1
 
0.8%
공릉2 1
 
0.8%
장안 1
 
0.8%
조원동 1
 
0.8%
신설2-1 1
 
0.8%
마곡2 1
 
0.8%
율현 1
 
0.8%
휘경 1
 
0.8%
장안2 1
 
0.8%
자양4 1
 
0.8%
Other values (109) 109
91.6%
2024-05-03T21:21:33.328293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 16
 
5.5%
1 13
 
4.5%
신 11
 
3.8%
림 7
 
2.4%
원 7
 
2.4%
양 7
 
2.4%
동 7
 
2.4%
로 6
 
2.1%
구 6
 
2.1%
장 6
 
2.1%
Other values (112) 205
70.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 252
86.6%
Decimal Number 38
 
13.1%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
신 11
 
4.4%
림 7
 
2.8%
원 7
 
2.8%
양 7
 
2.8%
동 7
 
2.8%
로 6
 
2.4%
구 6
 
2.4%
장 6
 
2.4%
산 6
 
2.4%
대 5
 
2.0%
Other values (106) 184
73.0%
Decimal Number
ValueCountFrequency (%)
2 16
42.1%
1 13
34.2%
4 5
 
13.2%
3 3
 
7.9%
5 1
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 252
86.6%
Common 39
 
13.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
신 11
 
4.4%
림 7
 
2.8%
원 7
 
2.8%
양 7
 
2.8%
동 7
 
2.8%
로 6
 
2.4%
구 6
 
2.4%
장 6
 
2.4%
산 6
 
2.4%
대 5
 
2.0%
Other values (106) 184
73.0%
Common
ValueCountFrequency (%)
2 16
41.0%
1 13
33.3%
4 5
 
12.8%
3 3
 
7.7%
- 1
 
2.6%
5 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 252
86.6%
ASCII 39
 
13.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 16
41.0%
1 13
33.3%
4 5
 
12.8%
3 3
 
7.7%
- 1
 
2.6%
5 1
 
2.6%
Hangul
ValueCountFrequency (%)
신 11
 
4.4%
림 7
 
2.8%
원 7
 
2.8%
양 7
 
2.8%
동 7
 
2.8%
로 6
 
2.4%
구 6
 
2.4%
장 6
 
2.4%
산 6
 
2.4%
대 5
 
2.0%
Other values (106) 184
73.0%

기타
Real number (ℝ)

UNIQUE 

Distinct119
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1475.2857
Minimum101
Maximum2506
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-03T21:21:33.846993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile202.9
Q1816.5
median1604
Q32004.5
95-th percentile2417.3
Maximum2506
Range2405
Interquartile range (IQR)1188

Descriptive statistics

Standard deviation670.6726
Coefficient of variation (CV)0.45460523
Kurtosis-0.94199934
Mean1475.2857
Median Absolute Deviation (MAD)598
Skewness-0.29836665
Sum175559
Variance449801.73
MonotonicityNot monotonic
2024-05-03T21:21:34.396563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
902 1
 
0.8%
1509 1
 
0.8%
2303 1
 
0.8%
805 1
 
0.8%
2011 1
 
0.8%
811 1
 
0.8%
1707 1
 
0.8%
105 1
 
0.8%
803 1
 
0.8%
806 1
 
0.8%
Other values (109) 109
91.6%
ValueCountFrequency (%)
101 1
0.8%
102 1
0.8%
105 1
0.8%
106 1
0.8%
201 1
0.8%
202 1
0.8%
203 1
0.8%
401 1
0.8%
402 1
0.8%
501 1
0.8%
ValueCountFrequency (%)
2506 1
0.8%
2505 1
0.8%
2504 1
0.8%
2503 1
0.8%
2502 1
0.8%
2501 1
0.8%
2408 1
0.8%
2407 1
0.8%
2405 1
0.8%
2404 1
0.8%

생성일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing119
Missing (%)100.0%
Memory size1.2 KiB

Interactions

2024-05-03T21:21:29.134871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:21:28.584023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:21:29.399203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:21:28.880384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T21:21:34.817252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간id기타
공간id1.0000.608
기타0.6081.000
2024-05-03T21:21:35.063215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간id기타
공간id1.0000.189
기타0.1891.000

Missing values

2024-05-03T21:21:29.723424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T21:21:30.110807image/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

공간id펌프이름기타생성일자
012560용답902<NA>
112561봉원1509<NA>
212562중화2704<NA>
312563방화1706<NA>
412564당인1510<NA>
512565중곡1203<NA>
612566구로42008<NA>
712567양화1804<NA>
812568박미2206<NA>
912569신길1907<NA>
공간id펌프이름기타생성일자
10912550가산22204<NA>
11012551가산12203<NA>
11112552독산2201<NA>
11212553대림2동1906<NA>
11312554시흥2202<NA>
11412555면목701<NA>
11512556중화702<NA>
11612557행당909<NA>
11712558구로32003<NA>
11812559사근906<NA>