Overview

Dataset statistics

Number of variables7
Number of observations21
Missing cells10
Missing cells (%)6.8%
Duplicate rows1
Duplicate rows (%)4.8%
Total size in memory1.3 KiB
Average record size in memory62.3 B

Variable types

Text1
Unsupported6

Dataset

Description중소기업은행 거래 고객 대상으로 명절을 앞두고 자금난에 어려움을 겪는 중소기업 대상으로 자금지원한 현황(2015년)을 지역별 및 xlsx파일 형식으로 제공
URLhttps://www.data.go.kr/data/15045505/fileData.do

Alerts

Dataset has 1 (4.8%) duplicate rowsDuplicates
명절특별지원자금 시도별 지원현황 has 2 (9.5%) missing valuesMissing
Unnamed: 1 has 1 (4.8%) missing valuesMissing
Unnamed: 2 has 2 (9.5%) missing valuesMissing
Unnamed: 3 has 1 (4.8%) missing valuesMissing
Unnamed: 4 has 2 (9.5%) missing valuesMissing
Unnamed: 6 has 2 (9.5%) missing valuesMissing
Unnamed: 1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 4 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

Reproduction

Analysis started2023-12-12 18:19:21.018168
Analysis finished2023-12-12 18:19:21.422152
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

명절특별지원자금 시도별 지원현황
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing2
Missing (%)9.5%
Memory size300.0 B
2023-12-13T03:19:21.544540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.2631579
Min length3

Characters and Unicode

Total characters81
Distinct characters35
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

Unique19 ?
Unique (%)100.0%

Sample

1st row시도명
2nd row경기도
3rd row서울특별시
4th row부산광역시
5th row인천광역시
ValueCountFrequency (%)
시도명 1
 
5.0%
경기도 1
 
5.0%
총 1
 
5.0%
세종특별자치시 1
 
5.0%
제주도 1
 
5.0%
강원도 1
 
5.0%
전라남도 1
 
5.0%
대전광역시 1
 
5.0%
울산광역시 1
 
5.0%
전라북도 1
 
5.0%
Other values (10) 10
50.0%
2023-12-13T03:19:21.879403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 10
 
12.3%
시 9
 
11.1%
광 7
 
8.6%
역 6
 
7.4%
경 3
 
3.7%
전 3
 
3.7%
북 3
 
3.7%
남 3
 
3.7%
상 2
 
2.5%
라 2
 
2.5%
Other values (25) 33
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80
98.8%
Space Separator 1
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 10
 
12.5%
시 9
 
11.2%
광 7
 
8.8%
역 6
 
7.5%
경 3
 
3.8%
전 3
 
3.8%
북 3
 
3.8%
남 3
 
3.8%
상 2
 
2.5%
라 2
 
2.5%
Other values (24) 32
40.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80
98.8%
Common 1
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 10
 
12.5%
시 9
 
11.2%
광 7
 
8.8%
역 6
 
7.5%
경 3
 
3.8%
전 3
 
3.8%
북 3
 
3.8%
남 3
 
3.8%
상 2
 
2.5%
라 2
 
2.5%
Other values (24) 32
40.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80
98.8%
ASCII 1
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 10
 
12.5%
시 9
 
11.2%
광 7
 
8.8%
역 6
 
7.5%
경 3
 
3.8%
전 3
 
3.8%
북 3
 
3.8%
남 3
 
3.8%
상 2
 
2.5%
라 2
 
2.5%
Other values (24) 32
40.0%
ASCII
ValueCountFrequency (%)
1
100.0%

Unnamed: 1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)4.8%
Memory size300.0 B

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.5%
Memory size300.0 B

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)4.8%
Memory size300.0 B

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.5%
Memory size300.0 B

Unnamed: 5
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size300.0 B

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.5%
Memory size300.0 B

Missing values

2023-12-13T03:19:21.105605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:19:21.214953image/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.
2023-12-13T03:19:21.343854image/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

명절특별지원자금 시도별 지원현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
0<NA>NaNNaNNaNNaN(단위 : 건, 억원)NaN
1시도명2015년설날NaN2015년추석NaN합계NaN
2<NA>지원건수지원금액지원건수지원금액지원건수지원금액
3경기도2159295842208198144367319398
4서울특별시1359560021426666132786112615
5부산광역시5813263360212768118345401
6인천광역시5992225658622362118544618
7경상남도367620873779219174554278
8대구광역시286311962859113257222328
9경상북도19381123179096637282089
명절특별지원자금 시도별 지원현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
11충청북도1283670135366126361331
12광주광역시1203766120581824081584
13전라북도8434107904461633856
14울산광역시8144637404161554879
15대전광역시6302906443531274643
16전라남도366207377208743415
17강원도359162354129713291
18제주도256131298160554291
19세종특별자치시6136524611382
20총 계6295128942642132992312716458865

Duplicate rows

Most frequently occurring

명절특별지원자금 시도별 지원현황# duplicates
0<NA>2