Overview

Dataset statistics

Number of variables8
Number of observations22
Missing cells59
Missing cells (%)33.5%
Duplicate rows2
Duplicate rows (%)9.1%
Total size in memory1.5 KiB
Average record size in memory70.0 B

Variable types

Text4
Unsupported4

Alerts

Dataset has 2 (9.1%) duplicate rowsDuplicates
창업보육센터 운영 현황 has 2 (9.1%) missing valuesMissing
Unnamed: 1 has 8 (36.4%) missing valuesMissing
Unnamed: 2 has 9 (40.9%) missing valuesMissing
Unnamed: 3 has 9 (40.9%) missing valuesMissing
Unnamed: 4 has 9 (40.9%) missing valuesMissing
Unnamed: 5 has 8 (36.4%) missing valuesMissing
Unnamed: 6 has 7 (31.8%) missing valuesMissing
Unnamed: 7 has 7 (31.8%) missing valuesMissing
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 00:47:54.653229
Analysis finished2024-03-14 00:47:55.350544
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

창업보육센터 운영 현황
Text

MISSING 

Distinct17
Distinct (%)85.0%
Missing2
Missing (%)9.1%
Memory size308.0 B
2024-03-14T09:47:55.427170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.25
Min length1

Characters and Unicode

Total characters85
Distinct characters36
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)80.0%

Sample

1st row센터명
2nd row계
3rd row전북대BI
4th row군산대BI
5th row우석대BI
ValueCountFrequency (%)
bi 4
20.0%
전주비전대 1
 
5.0%
센터명 1
 
5.0%
여성기업종합 1
 
5.0%
포스트bi 1
 
5.0%
희망전북 1
 
5.0%
전북과학대 1
 
5.0%
전주기전대 1
 
5.0%
백제예술대 1
 
5.0%
계 1
 
5.0%
Other values (7) 7
35.0%
2024-03-14T09:47:55.683650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 12
14.1%
I 12
14.1%
대 10
 
11.8%
전 9
 
10.6%
북 4
 
4.7%
주 3
 
3.5%
원 3
 
3.5%
센 2
 
2.4%
터 2
 
2.4%
기 2
 
2.4%
Other values (26) 26
30.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61
71.8%
Uppercase Letter 24
 
28.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 10
16.4%
전 9
 
14.8%
북 4
 
6.6%
주 3
 
4.9%
원 3
 
4.9%
센 2
 
3.3%
터 2
 
3.3%
기 2
 
3.3%
합 1
 
1.6%
종 1
 
1.6%
Other values (24) 24
39.3%
Uppercase Letter
ValueCountFrequency (%)
B 12
50.0%
I 12
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61
71.8%
Latin 24
 
28.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 10
16.4%
전 9
 
14.8%
북 4
 
6.6%
주 3
 
4.9%
원 3
 
4.9%
센 2
 
3.3%
터 2
 
3.3%
기 2
 
3.3%
합 1
 
1.6%
종 1
 
1.6%
Other values (24) 24
39.3%
Latin
ValueCountFrequency (%)
B 12
50.0%
I 12
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61
71.8%
ASCII 24
 
28.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
B 12
50.0%
I 12
50.0%
Hangul
ValueCountFrequency (%)
대 10
16.4%
전 9
 
14.8%
북 4
 
6.6%
주 3
 
4.9%
원 3
 
4.9%
센 2
 
3.3%
터 2
 
3.3%
기 2
 
3.3%
합 1
 
1.6%
종 1
 
1.6%
Other values (24) 24
39.3%

Unnamed: 1
Text

MISSING 

Distinct14
Distinct (%)100.0%
Missing8
Missing (%)36.4%
Memory size308.0 B
2024-03-14T09:47:55.826981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length8
Mean length5.4285714
Min length2

Characters and Unicode

Total characters76
Distinct characters43
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)100.0%

Sample

1st row분야
2nd row기계, 식품, 메카트로닉스
3rd row해양․바이오
4th rowIT&CT
5th rowIT, BT
ValueCountFrequency (%)
메카트로닉스 2
 
11.8%
it 2
 
11.8%
분야 1
 
5.9%
기계 1
 
5.9%
식품 1
 
5.9%
해양․바이오 1
 
5.9%
it&ct 1
 
5.9%
bt 1
 
5.9%
it,bt,ct 1
 
5.9%
전자 1
 
5.9%
Other values (5) 5
29.4%
2024-03-14T09:47:56.077734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 8
 
10.5%
․ 5
 
6.6%
, 5
 
6.6%
기 4
 
5.3%
I 4
 
5.3%
3
 
3.9%
로 2
 
2.6%
C 2
 
2.6%
B 2
 
2.6%
스 2
 
2.6%
Other values (33) 39
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46
60.5%
Uppercase Letter 16
 
21.1%
Other Punctuation 11
 
14.5%
Space Separator 3
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 4
 
8.7%
로 2
 
4.3%
스 2
 
4.3%
닉 2
 
4.3%
카 2
 
4.3%
트 2
 
4.3%
메 2
 
4.3%
전 2
 
4.3%
자 2
 
4.3%
컴 1
 
2.2%
Other values (25) 25
54.3%
Uppercase Letter
ValueCountFrequency (%)
T 8
50.0%
I 4
25.0%
C 2
 
12.5%
B 2
 
12.5%
Other Punctuation
ValueCountFrequency (%)
․ 5
45.5%
, 5
45.5%
& 1
 
9.1%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46
60.5%
Latin 16
 
21.1%
Common 14
 
18.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 4
 
8.7%
로 2
 
4.3%
스 2
 
4.3%
닉 2
 
4.3%
카 2
 
4.3%
트 2
 
4.3%
메 2
 
4.3%
전 2
 
4.3%
자 2
 
4.3%
컴 1
 
2.2%
Other values (25) 25
54.3%
Latin
ValueCountFrequency (%)
T 8
50.0%
I 4
25.0%
C 2
 
12.5%
B 2
 
12.5%
Common
ValueCountFrequency (%)
․ 5
35.7%
, 5
35.7%
3
21.4%
& 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46
60.5%
ASCII 25
32.9%
Punctuation 5
 
6.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 8
32.0%
, 5
20.0%
I 4
16.0%
3
 
12.0%
C 2
 
8.0%
B 2
 
8.0%
& 1
 
4.0%
Punctuation
ValueCountFrequency (%)
․ 5
100.0%
Hangul
ValueCountFrequency (%)
기 4
 
8.7%
로 2
 
4.3%
스 2
 
4.3%
닉 2
 
4.3%
카 2
 
4.3%
트 2
 
4.3%
메 2
 
4.3%
전 2
 
4.3%
자 2
 
4.3%
컴 1
 
2.2%
Other values (25) 25
54.3%

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9
Missing (%)40.9%
Memory size308.0 B

Unnamed: 3
Text

MISSING 

Distinct12
Distinct (%)92.3%
Missing9
Missing (%)40.9%
Memory size308.0 B
2024-03-14T09:47:56.216481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters39
Distinct characters27
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

Unique11 ?
Unique (%)84.6%

Sample

1st row센터장
2nd row김철생
3rd row김영철
4th row이우금
5th row김용갑
ValueCountFrequency (%)
김철생 2
15.4%
센터장 1
7.7%
김영철 1
7.7%
이우금 1
7.7%
김용갑 1
7.7%
강인선 1
7.7%
정의붕 1
7.7%
노상돈 1
7.7%
한우용 1
7.7%
김지용 1
7.7%
Other values (2) 2
15.4%
2024-03-14T09:47:56.448509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 6
 
15.4%
용 3
 
7.7%
철 3
 
7.7%
생 2
 
5.1%
한 2
 
5.1%
우 2
 
5.1%
의 1
 
2.6%
기 1
 
2.6%
송 1
 
2.6%
수 1
 
2.6%
Other values (17) 17
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 6
 
15.4%
용 3
 
7.7%
철 3
 
7.7%
생 2
 
5.1%
한 2
 
5.1%
우 2
 
5.1%
의 1
 
2.6%
기 1
 
2.6%
송 1
 
2.6%
수 1
 
2.6%
Other values (17) 17
43.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 6
 
15.4%
용 3
 
7.7%
철 3
 
7.7%
생 2
 
5.1%
한 2
 
5.1%
우 2
 
5.1%
의 1
 
2.6%
기 1
 
2.6%
송 1
 
2.6%
수 1
 
2.6%
Other values (17) 17
43.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 6
 
15.4%
용 3
 
7.7%
철 3
 
7.7%
생 2
 
5.1%
한 2
 
5.1%
우 2
 
5.1%
의 1
 
2.6%
기 1
 
2.6%
송 1
 
2.6%
수 1
 
2.6%
Other values (17) 17
43.6%

Unnamed: 4
Text

MISSING 

Distinct13
Distinct (%)100.0%
Missing9
Missing (%)40.9%
Memory size308.0 B
2024-03-14T09:47:56.591325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.5384615
Min length4

Characters and Unicode

Total characters59
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)100.0%

Sample

1st row보육실 면적
2nd row6653㎡
3rd row778㎡
4th row799㎡
5th row3317㎡
ValueCountFrequency (%)
보육실 1
 
7.1%
면적 1
 
7.1%
6653㎡ 1
 
7.1%
778㎡ 1
 
7.1%
799㎡ 1
 
7.1%
3317㎡ 1
 
7.1%
6213㎡ 1
 
7.1%
901㎡ 1
 
7.1%
344㎡ 1
 
7.1%
2714㎡ 1
 
7.1%
Other values (4) 4
28.6%
2024-03-14T09:47:56.902736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㎡ 12
20.3%
1 7
11.9%
7 7
11.9%
3 5
8.5%
6 5
8.5%
8 4
 
6.8%
4 4
 
6.8%
9 3
 
5.1%
5 2
 
3.4%
2 2
 
3.4%
Other values (7) 8
13.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41
69.5%
Other Symbol 12
 
20.3%
Other Letter 5
 
8.5%
Space Separator 1
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7
17.1%
7 7
17.1%
3 5
12.2%
6 5
12.2%
8 4
9.8%
4 4
9.8%
9 3
7.3%
5 2
 
4.9%
2 2
 
4.9%
0 2
 
4.9%
Other Letter
ValueCountFrequency (%)
육 1
20.0%
적 1
20.0%
면 1
20.0%
실 1
20.0%
보 1
20.0%
Other Symbol
ValueCountFrequency (%)
㎡ 12
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 54
91.5%
Hangul 5
 
8.5%

Most frequent character per script

Common
ValueCountFrequency (%)
㎡ 12
22.2%
1 7
13.0%
7 7
13.0%
3 5
9.3%
6 5
9.3%
8 4
 
7.4%
4 4
 
7.4%
9 3
 
5.6%
5 2
 
3.7%
2 2
 
3.7%
Other values (2) 3
 
5.6%
Hangul
ValueCountFrequency (%)
육 1
20.0%
적 1
20.0%
면 1
20.0%
실 1
20.0%
보 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42
71.2%
CJK Compat 12
 
20.3%
Hangul 5
 
8.5%

Most frequent character per block

CJK Compat
ValueCountFrequency (%)
㎡ 12
100.0%
ASCII
ValueCountFrequency (%)
1 7
16.7%
7 7
16.7%
3 5
11.9%
6 5
11.9%
8 4
9.5%
4 4
9.5%
9 3
7.1%
5 2
 
4.8%
2 2
 
4.8%
0 2
 
4.8%
Hangul
ValueCountFrequency (%)
육 1
20.0%
적 1
20.0%
면 1
20.0%
실 1
20.0%
보 1
20.0%

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8
Missing (%)36.4%
Memory size308.0 B

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7
Missing (%)31.8%
Memory size308.0 B

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7
Missing (%)31.8%
Memory size308.0 B

Correlations

2024-03-14T09:47:57.024724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
창업보육센터 운영 현황Unnamed: 1Unnamed: 3Unnamed: 4
창업보육센터 운영 현황1.0001.0001.0001.000
Unnamed: 11.0001.0001.0001.000
Unnamed: 31.0001.0001.0001.000
Unnamed: 41.0001.0001.0001.000

Missing values

2024-03-14T09:47:54.878250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:47:54.973534image/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.
2024-03-14T09:47:55.278898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

창업보육센터 운영 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7
0<NA><NA>NaN<NA><NA>NaN(‘14. 6월말 기준)NaN
1센터명분야개소연도센터장보육실 면적보육실수공실수입주
2<NA><NA>NaN<NA><NA>NaNNaN업체수
3계<NA>NaN<NA><NA>38549270
4전북대BI기계, 식품, 메카트로닉스1999김철생6653㎡841049
5군산대BI해양․바이오2001김영철778㎡16016
6우석대BIIT&CT1999이우금799㎡30917
7원광대BIIT, BT2001김용갑3317㎡50930
8전주대BIIT,BT,CT1999강인선6213㎡66354
9호원대BI전자2000정의붕901㎡15411
창업보육센터 운영 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7
12전주비전대컴퓨터․2001한우용2714㎡42631
13BI사무기기제조NaN<NA><NA>NaNNaNNaN
14전주기전대IT1999김지용574㎡16511
15BI<NA>NaN<NA><NA>NaNNaNNaN
16전북과학대메카트로닉스2001김한수881㎡21218
17BI<NA>NaN<NA><NA>NaNNaNNaN
18희망전북광․기․전2010김철생1671㎡22016
19포스트BI<NA>NaN<NA><NA>NaNNaNNaN
20여성기업종합문화․영상2009송기순608㎡13111
21지원전북센터BI<NA>NaN<NA><NA>NaNNaNNaN

Duplicate rows

Most frequently occurring

창업보육센터 운영 현황Unnamed: 1Unnamed: 3Unnamed: 4# duplicates
0BI<NA><NA><NA>3
1<NA><NA><NA><NA>2