Overview

Dataset statistics

Number of variables3
Number of observations109
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory27.2 B

Variable types

Text1
Numeric2

Dataset

Description관할지사별 사업장수, 가입자수 현황 정보 / 단위: 개소, 명
Author국민연금공단
URLhttps://www.data.go.kr/data/15071659/fileData.do

Alerts

사업장수 is highly overall correlated with 가입자 수High correlation
가입자 수 is highly overall correlated with 사업장수High correlation
관할지사 has unique valuesUnique
사업장수 has unique valuesUnique
가입자 수 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:05:02.264278
Analysis finished2023-12-12 23:05:03.129773
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관할지사
Text

UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2023-12-13T08:05:03.362102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length3.1651376
Min length2

Characters and Unicode

Total characters345
Distinct characters104
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

Unique109 ?
Unique (%)100.0%

Sample

1st row종로중구
2nd row동대문중랑
3rd row성북강북
4th row도봉노원
5th row성동광진
ValueCountFrequency (%)
종로중구 1
 
0.9%
용인 1
 
0.9%
아산 1
 
0.9%
세종 1
 
0.9%
서산태안 1
 
0.9%
공주부여 1
 
0.9%
보령 1
 
0.9%
홍성 1
 
0.9%
천안 1
 
0.9%
증평 1
 
0.9%
Other values (99) 99
90.8%
2023-12-13T08:05:03.844663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 20
 
5.8%
부 20
 
5.8%
주 19
 
5.5%
천 16
 
4.6%
남 12
 
3.5%
동 12
 
3.5%
서 9
 
2.6%
대 9
 
2.6%
양 9
 
2.6%
구 9
 
2.6%
Other values (94) 210
60.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 345
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 20
 
5.8%
부 20
 
5.8%
주 19
 
5.5%
천 16
 
4.6%
남 12
 
3.5%
동 12
 
3.5%
서 9
 
2.6%
대 9
 
2.6%
양 9
 
2.6%
구 9
 
2.6%
Other values (94) 210
60.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 345
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 20
 
5.8%
부 20
 
5.8%
주 19
 
5.5%
천 16
 
4.6%
남 12
 
3.5%
동 12
 
3.5%
서 9
 
2.6%
대 9
 
2.6%
양 9
 
2.6%
구 9
 
2.6%
Other values (94) 210
60.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 345
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 20
 
5.8%
부 20
 
5.8%
주 19
 
5.5%
천 16
 
4.6%
남 12
 
3.5%
동 12
 
3.5%
서 9
 
2.6%
대 9
 
2.6%
양 9
 
2.6%
구 9
 
2.6%
Other values (94) 210
60.9%

사업장수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18206.688
Minimum4187
Maximum51912
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T08:05:04.019023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4187
5-th percentile5640.2
Q111502
median16010
Q323996
95-th percentile35048
Maximum51912
Range47725
Interquartile range (IQR)12494

Descriptive statistics

Standard deviation9546.1678
Coefficient of variation (CV)0.52432204
Kurtosis1.1270663
Mean18206.688
Median Absolute Deviation (MAD)5932
Skewness0.97473104
Sum1984529
Variance91129319
MonotonicityNot monotonic
2023-12-13T08:05:04.196570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49500 1
 
0.9%
6158 1
 
0.9%
12003 1
 
0.9%
11305 1
 
0.9%
8245 1
 
0.9%
6237 1
 
0.9%
7184 1
 
0.9%
12687 1
 
0.9%
23314 1
 
0.9%
12761 1
 
0.9%
Other values (99) 99
90.8%
ValueCountFrequency (%)
4187 1
0.9%
4391 1
0.9%
4802 1
0.9%
5064 1
0.9%
5238 1
0.9%
5295 1
0.9%
6158 1
0.9%
6237 1
0.9%
7015 1
0.9%
7175 1
0.9%
ValueCountFrequency (%)
51912 1
0.9%
49500 1
0.9%
40504 1
0.9%
36976 1
0.9%
36743 1
0.9%
35230 1
0.9%
34775 1
0.9%
33213 1
0.9%
32868 1
0.9%
31257 1
0.9%

가입자 수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129305.49
Minimum16420
Maximum714150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T08:05:04.379941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16420
5-th percentile29103.8
Q168108
median104427
Q3152660
95-th percentile355238.6
Maximum714150
Range697730
Interquartile range (IQR)84552

Descriptive statistics

Standard deviation105772.68
Coefficient of variation (CV)0.81800609
Kurtosis8.9931857
Mean129305.49
Median Absolute Deviation (MAD)41992
Skewness2.5170684
Sum14094298
Variance1.1187859 × 1010
MonotonicityNot monotonic
2023-12-13T08:05:04.561741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
714150 1
 
0.9%
28049 1
 
0.9%
103942 1
 
0.9%
67304 1
 
0.9%
59158 1
 
0.9%
37871 1
 
0.9%
36280 1
 
0.9%
89519 1
 
0.9%
169672 1
 
0.9%
104427 1
 
0.9%
Other values (99) 99
90.8%
ValueCountFrequency (%)
16420 1
0.9%
17383 1
0.9%
20534 1
0.9%
21122 1
0.9%
24646 1
0.9%
28049 1
0.9%
30686 1
0.9%
31822 1
0.9%
34726 1
0.9%
35980 1
0.9%
ValueCountFrequency (%)
714150 1
0.9%
449988 1
0.9%
428212 1
0.9%
400295 1
0.9%
368308 1
0.9%
360869 1
0.9%
346793 1
0.9%
314820 1
0.9%
299571 1
0.9%
260667 1
0.9%

Interactions

2023-12-13T08:05:02.515185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:02.369502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:02.592625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:02.437556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:05:04.676302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장수가입자 수
사업장수1.0000.794
가입자 수0.7941.000
2023-12-13T08:05:04.777754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장수가입자 수
사업장수1.0000.928
가입자 수0.9281.000

Missing values

2023-12-13T08:05:02.722675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:05:03.095476image/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

관할지사사업장수가입자 수
0종로중구49500714150
1동대문중랑21274113317
2성북강북1601078791
3도봉노원1592979272
4성동광진28557242811
5송파30529299571
6강동하남25075141624
7서울남부지역본부30795346793
8서초36976428212
9관악1049555055
관할지사사업장수가입자 수
99창원24696196112
100김해밀양25557155623
101통영12123106157
102진주1361190756
103마산1542389047
104거창480221122
105양산1175284266
106사천남해523834726
107제주22885116529
108서귀포839135980