Overview

Dataset statistics

Number of variables2
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory540.0 B
Average record size in memory22.5 B

Variable types

Text1
Numeric1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15361/S/1/datasetView.do

Alerts

구청명 has unique valuesUnique
구청코드 has unique valuesUnique

Reproduction

Analysis started2024-04-16 11:31:15.337969
Analysis finished2024-04-16 11:31:15.558155
Duration0.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구청명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-04-16T20:31:15.661335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0833333
Min length2

Characters and Unicode

Total characters74
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row강동구
2nd row강북구
3rd row강서구
4th row관악구
5th row광진구
ValueCountFrequency (%)
강동구 1
 
4.2%
강북구 1
 
4.2%
중랑구 1
 
4.2%
중구 1
 
4.2%
종로구 1
 
4.2%
은평구 1
 
4.2%
용산구 1
 
4.2%
영등포구 1
 
4.2%
양천구 1
 
4.2%
송파구 1
 
4.2%
Other values (14) 14
58.3%
2024-04-16T20:31:15.962200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 25
33.8%
강 4
 
5.4%
서 3
 
4.1%
동 3
 
4.1%
로 2
 
2.7%
포 2
 
2.7%
문 2
 
2.7%
대 2
 
2.7%
천 2
 
2.7%
중 2
 
2.7%
Other values (26) 27
36.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 25
33.8%
강 4
 
5.4%
서 3
 
4.1%
동 3
 
4.1%
로 2
 
2.7%
포 2
 
2.7%
문 2
 
2.7%
대 2
 
2.7%
천 2
 
2.7%
중 2
 
2.7%
Other values (26) 27
36.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 25
33.8%
강 4
 
5.4%
서 3
 
4.1%
동 3
 
4.1%
로 2
 
2.7%
포 2
 
2.7%
문 2
 
2.7%
대 2
 
2.7%
천 2
 
2.7%
중 2
 
2.7%
Other values (26) 27
36.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 25
33.8%
강 4
 
5.4%
서 3
 
4.1%
동 3
 
4.1%
로 2
 
2.7%
포 2
 
2.7%
문 2
 
2.7%
대 2
 
2.7%
천 2
 
2.7%
중 2
 
2.7%
Other values (26) 27
36.5%

구청코드
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.916667
Minimum2
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-16T20:31:16.062138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3.15
Q17.75
median13.5
Q320.25
95-th percentile24.85
Maximum26
Range24
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.5060362
Coefficient of variation (CV)0.5393559
Kurtosis-1.2745593
Mean13.916667
Median Absolute Deviation (MAD)6.5
Skewness0.03543869
Sum334
Variance56.34058
MonotonicityStrictly increasing
2024-04-16T20:31:16.154351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
2 1
 
4.2%
15 1
 
4.2%
26 1
 
4.2%
25 1
 
4.2%
24 1
 
4.2%
23 1
 
4.2%
22 1
 
4.2%
21 1
 
4.2%
20 1
 
4.2%
19 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
2 1
4.2%
3 1
4.2%
4 1
4.2%
5 1
4.2%
6 1
4.2%
7 1
4.2%
8 1
4.2%
9 1
4.2%
10 1
4.2%
11 1
4.2%
ValueCountFrequency (%)
26 1
4.2%
25 1
4.2%
24 1
4.2%
23 1
4.2%
22 1
4.2%
21 1
4.2%
20 1
4.2%
19 1
4.2%
18 1
4.2%
17 1
4.2%

Interactions

2024-04-16T20:31:15.405938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-16T20:31:16.224160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구청명구청코드
구청명1.0001.000
구청코드1.0001.000

Missing values

2024-04-16T20:31:15.491384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-16T20:31:15.538842image/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

구청명구청코드
0강동구2
1강북구3
2강서구4
3관악구5
4광진구6
5구로구7
6금천구8
7노원구9
8도봉구10
9동대문구11
구청명구청코드
14성북구17
15송파구18
16양천구19
17영등포구20
18용산구21
19은평구22
20종로구23
21중구24
22중랑구25
23강남구26