Overview

Dataset statistics

Number of variables1
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory156.2 KiB
Average record size in memory16.0 B

Variable types

Categorical1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15249/A/1/datasetView.do

Alerts

Dataset has 1 (< 0.1%) duplicate rowsDuplicates
PK is highly imbalanced (99.3%)Imbalance

Reproduction

Analysis started2024-05-18 01:15:26.956662
Analysis finished2024-05-18 01:15:27.510160
Duration0.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

PK
Categorical

IMBALANCE 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Yƣ+D[D)
9980 
US С6ǀP 2^#_qfwBkkW%y_"fiJq=`lpkcHƀ~w\yUrRZ
 
1
!x+JUY~
 
1
U"K0}#٘n 
 
1
ƕ ovH%&7?ye^ Vh nXX@UHrU H"Zԫ++|w
 
1
Other values (16)
 
16

Length

Max length66
Median length13
Mean length13.0309
Min length1

Unique

Unique20 ?
Unique (%)0.2%

Sample

1st rowYƣ+D[D)
2nd rowYƣ+D[D)
3rd rowYƣ+D[D)
4th rowYƣ+D[D)
5th rowYƣ+D[D)

Common Values

ValueCountFrequency (%)
Yƣ+D[D) 9980
99.8%
US С6ǀP 2^#_qfwBkkW%y_"fiJq=`lpkcHƀ~w\yUrRZ 1
 
< 0.1%
!x+JUY~ 1
 
< 0.1%
U"K0}#٘n  1
 
< 0.1%
ƕ ovH%&7?ye^ Vh nXX@UHrU H"Zԫ++|w 1
 
< 0.1%
¡1ZZ'&4HI)ipD_?(Bb 1
 
< 0.1%
s\MAPGd+5{_ WE`ʻY=ΫcCPt‰裏a}!>c 1
 
< 0.1%
1 1
 
< 0.1%
:>ǻ)F&z/kH xGxg`?r^ͤR36/4`Ft)"x - 1
 
< 0.1%
%Rh")5iʦ$j@aZT eS|ysuR1 bW[^ss꽿?Y㟯O?+k?zu?4ɵg^+r|_׮O>?§z 1
 
< 0.1%
Other values (11) 11
 
0.1%

Length

2024-05-18T10:15:27.947927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
yƣ+d[d) 9980
99.4%
rh")5iʦ$j@azt 1
 
< 0.1%
bw[^ss꽿?y㟯o?+k?z 1
 
< 0.1%
u?4ɵg^+r|_׮o>?§z 1
 
< 0.1%
i'<ekb 1
 
< 0.1%
sp$3qukl 1
 
< 0.1%
ԕck6bܫd;nnnmo'|di~:~fpumck|bt8~j4 1
 
< 0.1%
ay3 1
 
< 0.1%
on 1
 
< 0.1%
7ssz 1
 
< 0.1%
Other values (47) 47
 
0.5%

Missing values

2024-05-18T10:15:27.135172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T10:15:27.436493image/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

PK
8999Yƣ+D[D)
3536Yƣ+D[D)
27807Yƣ+D[D)
24836Yƣ+D[D)
15289Yƣ+D[D)
20857Yƣ+D[D)
3054Yƣ+D[D)
8131Yƣ+D[D)
26255Yƣ+D[D)
5605Yƣ+D[D)
PK
4923Yƣ+D[D)
7905Yƣ+D[D)
5527Yƣ+D[D)
26386Yƣ+D[D)
28124Yƣ+D[D)
6855Yƣ+D[D)
13354Yƣ+D[D)
26137Yƣ+D[D)
28875Yƣ+D[D)
21299Yƣ+D[D)

Duplicate rows

Most frequently occurring

PK# duplicates
0Yƣ+D[D)9980