Overview

Dataset statistics

Number of variables3
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory756.0 B
Average record size in memory31.5 B

Variable types

Text1
Numeric2

Dataset

Description대구광역시 달서구_행정동별 기초생활수급자_20230424
Author대구광역시 달서구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15113503&dataSetDetailId=151135031d0d34ce7de9f&provdMethod=FILE

Alerts

기초생활수급자 세대수 is highly overall correlated with 기초생활수급자 인원수High correlation
기초생활수급자 인원수 is highly overall correlated with 기초생활수급자 세대수High correlation
행정동 has unique valuesUnique
기초생활수급자 세대수 has unique valuesUnique
기초생활수급자 인원수 has unique valuesUnique

Reproduction

Analysis started2024-04-19 05:35:26.639625
Analysis finished2024-04-19 05:35:27.245937
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-04-19T14:35:27.368182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.5416667
Min length2

Characters and Unicode

Total characters85
Distinct characters34
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row성당동
2nd row두류1.2동
3rd row두류3동
4th row감삼동
5th row죽전동
ValueCountFrequency (%)
성당동 1
 
4.2%
두류1.2동 1
 
4.2%
본동 1
 
4.2%
송현2동 1
 
4.2%
송현1동 1
 
4.2%
도원동 1
 
4.2%
상인3동 1
 
4.2%
상인2동 1
 
4.2%
상인1동 1
 
4.2%
유천동 1
 
4.2%
Other values (14) 14
58.3%
2024-04-19T14:35:27.693189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 23
27.1%
1 6
 
7.1%
2 6
 
7.1%
성 3
 
3.5%
인 3
 
3.5%
상 3
 
3.5%
용 2
 
2.4%
현 2
 
2.4%
송 2
 
2.4%
천 2
 
2.4%
Other values (24) 33
38.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70
82.4%
Decimal Number 14
 
16.5%
Other Punctuation 1
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 23
32.9%
성 3
 
4.3%
인 3
 
4.3%
상 3
 
4.3%
용 2
 
2.9%
현 2
 
2.9%
송 2
 
2.9%
천 2
 
2.9%
월 2
 
2.9%
본 2
 
2.9%
Other values (20) 26
37.1%
Decimal Number
ValueCountFrequency (%)
1 6
42.9%
2 6
42.9%
3 2
 
14.3%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70
82.4%
Common 15
 
17.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 23
32.9%
성 3
 
4.3%
인 3
 
4.3%
상 3
 
4.3%
용 2
 
2.9%
현 2
 
2.9%
송 2
 
2.9%
천 2
 
2.9%
월 2
 
2.9%
본 2
 
2.9%
Other values (20) 26
37.1%
Common
ValueCountFrequency (%)
1 6
40.0%
2 6
40.0%
3 2
 
13.3%
. 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70
82.4%
ASCII 15
 
17.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 23
32.9%
성 3
 
4.3%
인 3
 
4.3%
상 3
 
4.3%
용 2
 
2.9%
현 2
 
2.9%
송 2
 
2.9%
천 2
 
2.9%
월 2
 
2.9%
본 2
 
2.9%
Other values (20) 26
37.1%
ASCII
ValueCountFrequency (%)
1 6
40.0%
2 6
40.0%
3 2
 
13.3%
. 1
 
6.7%

기초생활수급자 세대수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1005.25
Minimum105
Maximum3150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-19T14:35:27.816332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum105
5-th percentile215.15
Q1431.5
median666
Q31239.25
95-th percentile2654.35
Maximum3150
Range3045
Interquartile range (IQR)807.75

Descriptive statistics

Standard deviation836.20136
Coefficient of variation (CV)0.83183423
Kurtosis0.91210192
Mean1005.25
Median Absolute Deviation (MAD)287.5
Skewness1.3509775
Sum24126
Variance699232.72
MonotonicityNot monotonic
2024-04-19T14:35:27.920963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1236 1
 
4.2%
3150 1
 
4.2%
364 1
 
4.2%
830 1
 
4.2%
2050 1
 
4.2%
1816 1
 
4.2%
702 1
 
4.2%
2492 1
 
4.2%
848 1
 
4.2%
393 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
105 1
4.2%
194 1
4.2%
335 1
4.2%
364 1
4.2%
393 1
4.2%
406 1
4.2%
440 1
4.2%
474 1
4.2%
519 1
4.2%
625 1
4.2%
ValueCountFrequency (%)
3150 1
4.2%
2683 1
4.2%
2492 1
4.2%
2050 1
4.2%
1816 1
4.2%
1249 1
4.2%
1236 1
4.2%
1228 1
4.2%
848 1
4.2%
830 1
4.2%

기초생활수급자 인원수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1428.9583
Minimum229
Maximum3921
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-19T14:35:28.028026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum229
5-th percentile332.75
Q1648.5
median1028
Q31837
95-th percentile3516.5
Maximum3921
Range3692
Interquartile range (IQR)1188.5

Descriptive statistics

Standard deviation1068.1577
Coefficient of variation (CV)0.74750792
Kurtosis0.16645517
Mean1428.9583
Median Absolute Deviation (MAD)454.5
Skewness1.1126751
Sum34295
Variance1140960.8
MonotonicityNot monotonic
2024-04-19T14:35:28.151922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1772 1
 
4.2%
3921 1
 
4.2%
439 1
 
4.2%
1197 1
 
4.2%
2768 1
 
4.2%
2756 1
 
4.2%
1095 1
 
4.2%
3202 1
 
4.2%
1355 1
 
4.2%
650 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
229 1
4.2%
314 1
4.2%
439 1
4.2%
528 1
4.2%
619 1
4.2%
644 1
4.2%
650 1
4.2%
694 1
4.2%
787 1
4.2%
981 1
4.2%
ValueCountFrequency (%)
3921 1
4.2%
3572 1
4.2%
3202 1
4.2%
2768 1
4.2%
2756 1
4.2%
2032 1
4.2%
1772 1
4.2%
1692 1
4.2%
1355 1
4.2%
1197 1
4.2%

Interactions

2024-04-19T14:35:26.932817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:35:26.733207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:35:27.016728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:35:26.836725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T14:35:28.289794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동기초생활수급자 세대수기초생활수급자 인원수
행정동1.0001.0001.000
기초생활수급자 세대수1.0001.0000.886
기초생활수급자 인원수1.0000.8861.000
2024-04-19T14:35:28.392944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기초생활수급자 세대수기초생활수급자 인원수
기초생활수급자 세대수1.0000.994
기초생활수급자 인원수0.9941.000

Missing values

2024-04-19T14:35:27.136189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T14:35:27.215177image/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

행정동기초생활수급자 세대수기초생활수급자 인원수
0성당동12361772
1두류1.2동12281692
2두류3동474644
3감삼동6711050
4죽전동661992
5장기동625981
6용산1동6551006
7용산2동519787
8이곡1동440694
9이곡2동335528
행정동기초생활수급자 세대수기초생활수급자 인원수
14진천동12492032
15유천동105229
16상인1동393650
17상인2동8481355
18상인3동24923202
19도원동7021095
20송현1동18162756
21송현2동20502768
22본동8301197
23시설364439