Overview

Dataset statistics

Number of variables5
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory45.3 B

Variable types

Categorical1
Text3
DateTime1

Dataset

Description경상북도에서 운영하고 있는 푸드뱅크 현황입니다. 구분목록과 사업주체, 소재지, 설치일 등에 관한 내용이 포함되어 있습니다.
Author경상북도
URLhttps://www.data.go.kr/data/15063077/fileData.do

Alerts

구 분 is highly imbalanced (51.8%)Imbalance

Reproduction

Analysis started2023-12-12 16:44:04.232253
Analysis finished2023-12-12 16:44:04.644437
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구 분
Categorical

IMBALANCE 

Distinct3
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
기초
21 
마켓
3 
광역
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)4.0%

Sample

1st row광역
2nd row기초
3rd row기초
4th row기초
5th row기초

Common Values

ValueCountFrequency (%)
기초 21
84.0%
마켓 3
 
12.0%
광역 1
 
4.0%

Length

2023-12-13T01:44:04.703658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:44:04.800752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기초 21
84.0%
마켓 3
 
12.0%
광역 1
 
4.0%

시군명
Text

Distinct17
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-13T01:44:04.927462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2
Min length1

Characters and Unicode

Total characters50
Distinct characters24
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

Unique13 ?
Unique (%)52.0%

Sample

1st row도
2nd row포항
3rd row포항
4th row포항
5th row포항
ValueCountFrequency (%)
포항 5
20.0%
구미 3
12.0%
경산 2
 
8.0%
김천 2
 
8.0%
영덕 1
 
4.0%
도 1
 
4.0%
칠곡 1
 
4.0%
성주 1
 
4.0%
청도 1
 
4.0%
의성 1
 
4.0%
Other values (7) 7
28.0%
2023-12-13T01:44:05.192013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
포 5
 
10.0%
항 5
 
10.0%
주 4
 
8.0%
경 4
 
8.0%
천 3
 
6.0%
영 3
 
6.0%
미 3
 
6.0%
구 3
 
6.0%
김 2
 
4.0%
도 2
 
4.0%
Other values (14) 16
32.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49
98.0%
Space Separator 1
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
포 5
 
10.2%
항 5
 
10.2%
주 4
 
8.2%
경 4
 
8.2%
천 3
 
6.1%
영 3
 
6.1%
미 3
 
6.1%
구 3
 
6.1%
김 2
 
4.1%
도 2
 
4.1%
Other values (13) 15
30.6%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49
98.0%
Common 1
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
포 5
 
10.2%
항 5
 
10.2%
주 4
 
8.2%
경 4
 
8.2%
천 3
 
6.1%
영 3
 
6.1%
미 3
 
6.1%
구 3
 
6.1%
김 2
 
4.1%
도 2
 
4.1%
Other values (13) 15
30.6%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49
98.0%
ASCII 1
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
포 5
 
10.2%
항 5
 
10.2%
주 4
 
8.2%
경 4
 
8.2%
천 3
 
6.1%
영 3
 
6.1%
미 3
 
6.1%
구 3
 
6.1%
김 2
 
4.1%
도 2
 
4.1%
Other values (13) 15
30.6%
ASCII
ValueCountFrequency (%)
1
100.0%

사 업 주 체
Text

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-13T01:44:05.385725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length8
Min length2

Characters and Unicode

Total characters200
Distinct characters78
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)84.0%

Sample

1st row경상북도사회복지협의회
2nd row한기장내일을여는집
3rd row개인(경동교회)
4th row흥해제일교회
5th row선한 이웃
ValueCountFrequency (%)
경산시노인종합복지관 2
 
7.7%
금오종합사회복지관 2
 
7.7%
경상북도사회복지협의회 1
 
3.8%
로뎀복지재단 1
 
3.8%
영신해밀홈 1
 
3.8%
칠곡군교육문화복지회관 1
 
3.8%
실로암육아원 1
 
3.8%
효사랑실버센터 1
 
3.8%
영덕군지역사회보장협의체 1
 
3.8%
의성자혜원 1
 
3.8%
Other values (14) 14
53.8%
2023-12-13T01:44:05.725929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 13
 
6.5%
복 12
 
6.0%
회 12
 
6.0%
사 9
 
4.5%
관 8
 
4.0%
인 7
 
3.5%
종 7
 
3.5%
합 7
 
3.5%
경 6
 
3.0%
시 6
 
3.0%
Other values (68) 113
56.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 193
96.5%
Open Punctuation 3
 
1.5%
Close Punctuation 3
 
1.5%
Space Separator 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 13
 
6.7%
복 12
 
6.2%
회 12
 
6.2%
사 9
 
4.7%
관 8
 
4.1%
인 7
 
3.6%
종 7
 
3.6%
합 7
 
3.6%
경 6
 
3.1%
시 6
 
3.1%
Other values (65) 106
54.9%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 193
96.5%
Common 7
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 13
 
6.7%
복 12
 
6.2%
회 12
 
6.2%
사 9
 
4.7%
관 8
 
4.1%
인 7
 
3.6%
종 7
 
3.6%
합 7
 
3.6%
경 6
 
3.1%
시 6
 
3.1%
Other values (65) 106
54.9%
Common
ValueCountFrequency (%)
( 3
42.9%
) 3
42.9%
1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 193
96.5%
ASCII 7
 
3.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 13
 
6.7%
복 12
 
6.2%
회 12
 
6.2%
사 9
 
4.7%
관 8
 
4.1%
인 7
 
3.6%
종 7
 
3.6%
합 7
 
3.6%
경 6
 
3.1%
시 6
 
3.1%
Other values (65) 106
54.9%
ASCII
ValueCountFrequency (%)
( 3
42.9%
) 3
42.9%
1
 
14.3%

소 재 지
Text

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-13T01:44:06.016685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length14.4
Min length9

Characters and Unicode

Total characters360
Distinct characters81
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)92.0%

Sample

1st row안동시 광명로 166 7층
2nd row포항시 북구 삼흥로74번길 7-7
3rd row포항시 남구 오천읍 해병로347번길 34
4th row포항시 북구 흥해읍 한동로43
5th row포항시 북구 중앙로298번길 3-1
ValueCountFrequency (%)
포항시 5
 
5.6%
구미시 3
 
3.4%
북구 3
 
3.4%
문장로 2
 
2.2%
김천시 2
 
2.2%
34 2
 
2.2%
남구 2
 
2.2%
경산시 2
 
2.2%
110 2
 
2.2%
안동시 2
 
2.2%
Other values (64) 64
71.9%
2023-12-13T01:44:06.569108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
64
 
17.8%
1 24
 
6.7%
시 20
 
5.6%
로 17
 
4.7%
길 15
 
4.2%
3 13
 
3.6%
- 10
 
2.8%
2 10
 
2.8%
구 8
 
2.2%
6 8
 
2.2%
Other values (71) 171
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 201
55.8%
Decimal Number 85
23.6%
Space Separator 64
 
17.8%
Dash Punctuation 10
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 20
 
10.0%
로 17
 
8.5%
길 15
 
7.5%
구 8
 
4.0%
포 7
 
3.5%
읍 6
 
3.0%
주 6
 
3.0%
경 6
 
3.0%
군 6
 
3.0%
청 5
 
2.5%
Other values (59) 105
52.2%
Decimal Number
ValueCountFrequency (%)
1 24
28.2%
3 13
15.3%
2 10
11.8%
6 8
 
9.4%
7 8
 
9.4%
4 7
 
8.2%
9 7
 
8.2%
5 4
 
4.7%
0 3
 
3.5%
8 1
 
1.2%
Space Separator
ValueCountFrequency (%)
64
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 201
55.8%
Common 159
44.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 20
 
10.0%
로 17
 
8.5%
길 15
 
7.5%
구 8
 
4.0%
포 7
 
3.5%
읍 6
 
3.0%
주 6
 
3.0%
경 6
 
3.0%
군 6
 
3.0%
청 5
 
2.5%
Other values (59) 105
52.2%
Common
ValueCountFrequency (%)
64
40.3%
1 24
 
15.1%
3 13
 
8.2%
- 10
 
6.3%
2 10
 
6.3%
6 8
 
5.0%
7 8
 
5.0%
4 7
 
4.4%
9 7
 
4.4%
5 4
 
2.5%
Other values (2) 4
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 201
55.8%
ASCII 159
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
64
40.3%
1 24
 
15.1%
3 13
 
8.2%
- 10
 
6.3%
2 10
 
6.3%
6 8
 
5.0%
7 8
 
5.0%
4 7
 
4.4%
9 7
 
4.4%
5 4
 
2.5%
Other values (2) 4
 
2.5%
Hangul
ValueCountFrequency (%)
시 20
 
10.0%
로 17
 
8.5%
길 15
 
7.5%
구 8
 
4.0%
포 7
 
3.5%
읍 6
 
3.0%
주 6
 
3.0%
경 6
 
3.0%
군 6
 
3.0%
청 5
 
2.5%
Other values (59) 105
52.2%

설치일
Date

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
Minimum1998-01-01 00:00:00
Maximum2019-08-08 00:00:00
2023-12-13T01:44:06.751718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:44:06.949553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

Correlations

2023-12-13T01:44:07.091765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구 분시군명사 업 주 체소 재 지설치일
구 분1.0000.0000.0000.0001.000
시군명0.0001.0001.0001.0000.000
사 업 주 체0.0001.0001.0001.0000.950
소 재 지0.0001.0001.0001.0000.959
설치일1.0000.0000.9500.9591.000

Missing values

2023-12-13T01:44:04.500008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:44:04.607885image/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

구 분시군명사 업 주 체소 재 지설치일
0광역도경상북도사회복지협의회안동시 광명로 166 7층2000-05-29
1기초포항한기장내일을여는집포항시 북구 삼흥로74번길 7-72005-03-11
2기초포항개인(경동교회)포항시 남구 오천읍 해병로347번길 342005-05-31
3기초포항흥해제일교회포항시 북구 흥해읍 한동로432005-09-30
4기초포항선한 이웃포항시 북구 중앙로298번길 3-12005-11-14
5기초경주경주시종합사회복지관경주시 승삼1길 342000-07-01
6기초김천개인(반석노인복지센터)김천시 모암길 32008-03-19
7기초김천개인김천시 지좌길 13-32018-01-05
8기초안동안동복지원안동시 복주5길 23-171998-02-01
9기초구미금오종합사회복지관구미시 문장로 1102004-10-01
구 분시군명사 업 주 체소 재 지설치일
15기초경산경산시노인종합복지관경산시 경청로222길 792001-06-27
16기초의성의성자혜원의성군 의성읍 북원3길 51-61998-01-01
17기초영덕영덕군지역사회보장협의체영덕군 영덕읍 화개길 9-62019-08-08
18기초청도효사랑실버센터청도군 화양읍 청화로 79-112000-01-01
19기초성주실로암육아원성주군 수륜면 성주가야산로 6162002-01-01
20기초칠곡칠곡군교육문화복지회관칠곡군 왜관읍 관문로1길 322003-03-03
21기초울진영신해밀홈울진군 후포면 후포삼율로 49-12002-01-01
22마켓포항포항모자원포항시 남구 송도로 512009-06-26
23마켓구미금오종합사회복지관구미시 문장로 1102009-07-08
24마켓경산경산시노인종합복지관경산시 경청로219길 3-22009-06-25