Overview

Dataset statistics

Number of variables14
Number of observations667
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory80.2 KiB
Average record size in memory123.2 B

Variable types

Categorical5
Text1
Numeric8

Dataset

Description부산광역시_기초생활보장수급자읍면동현황_20231231
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15127068

Alerts

시도 has constant value ""Constant
기타 수급권자수 is highly overall correlated with 기타 가구수High correlation
기타 가구수 is highly overall correlated with 기타 수급권자수High correlation
일반수급자 가구수 is highly overall correlated with 일반수급자 수급권자수 and 4 other fieldsHigh correlation
일반수급자 수급권자수 is highly overall correlated with 일반수급자 가구수 and 4 other fieldsHigh correlation
조건부수급자 가구수 is highly overall correlated with 일반수급자 가구수 and 4 other fieldsHigh correlation
조건부수급자 수급권자수 is highly overall correlated with 일반수급자 가구수 and 4 other fieldsHigh correlation
특례수급자 가구수 is highly overall correlated with 일반수급자 가구수 and 4 other fieldsHigh correlation
특례수급자 수급권자수 is highly overall correlated with 일반수급자 가구수 and 4 other fieldsHigh correlation
시설수급자 가구수 is highly overall correlated with 시설수급자 수급권자수High correlation
시설수급자 수급권자수 is highly overall correlated with 시설수급자 가구수High correlation
기타 가구수 is highly imbalanced (93.5%)Imbalance
기타 수급권자수 is highly imbalanced (94.7%)Imbalance
일반수급자 가구수 has 10 (1.5%) zerosZeros
일반수급자 수급권자수 has 15 (2.2%) zerosZeros
조건부수급자 가구수 has 45 (6.7%) zerosZeros
조건부수급자 수급권자수 has 49 (7.3%) zerosZeros
특례수급자 가구수 has 66 (9.9%) zerosZeros
특례수급자 수급권자수 has 66 (9.9%) zerosZeros
시설수급자 가구수 has 281 (42.1%) zerosZeros
시설수급자 수급권자수 has 281 (42.1%) zerosZeros

Reproduction

Analysis started2024-03-23 07:04:48.562168
Analysis finished2024-03-23 07:05:16.389349
Duration27.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2021
223 
2022
222 
2023
222 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 223
33.4%
2022 222
33.3%
2023 222
33.3%

Length

2024-03-23T07:05:16.593482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:05:16.919915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 223
33.4%
2022 222
33.3%
2023 222
33.3%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
부산광역시
667 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시
2nd row부산광역시
3rd row부산광역시
4th row부산광역시
5th row부산광역시

Common Values

ValueCountFrequency (%)
부산광역시 667
100.0%

Length

2024-03-23T07:05:17.317271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:05:17.612188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 667
100.0%

시군구
Categorical

Distinct16
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
부산진구
63 
해운대구
57 
남구
54 
금정구
53 
사하구
51 
Other values (11)
389 

Length

Max length4
Median length3
Mean length2.8695652
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중구
2nd row중구
3rd row중구
4th row중구
5th row중구

Common Values

ValueCountFrequency (%)
부산진구 63
 
9.4%
해운대구 57
 
8.5%
남구 54
 
8.1%
금정구 53
 
7.9%
사하구 51
 
7.6%
서구 42
 
6.3%
동래구 42
 
6.3%
북구 42
 
6.3%
동구 39
 
5.8%
연제구 39
 
5.8%
Other values (6) 185
27.7%

Length

2024-03-23T07:05:17.956561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부산진구 63
 
9.4%
해운대구 57
 
8.5%
남구 54
 
8.1%
금정구 53
 
7.9%
사하구 51
 
7.6%
서구 42
 
6.3%
동래구 42
 
6.3%
북구 42
 
6.3%
동구 39
 
5.8%
연제구 39
 
5.8%
Other values (6) 185
27.7%

읍면동
Text

Distinct224
Distinct (%)33.6%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-03-23T07:05:18.813052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.7076462
Min length2

Characters and Unicode

Total characters2473
Distinct characters114
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

Unique2 ?
Unique (%)0.3%

Sample

1st row중구
2nd row중앙동
3rd row동광동
4th row대청동
5th row보수동
ValueCountFrequency (%)
중구 3
 
0.4%
감천2동 3
 
0.4%
서1동 3
 
0.4%
하단1동 3
 
0.4%
하단2동 3
 
0.4%
신평1동 3
 
0.4%
신평2동 3
 
0.4%
장림1동 3
 
0.4%
장림2동 3
 
0.4%
다대1동 3
 
0.4%
Other values (214) 637
95.5%
2024-03-23T07:05:19.924923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 635
25.7%
1 171
 
6.9%
2 159
 
6.4%
3 79
 
3.2%
구 66
 
2.7%
대 51
 
2.1%
연 45
 
1.8%
천 39
 
1.6%
부 39
 
1.6%
4 39
 
1.6%
Other values (104) 1150
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1998
80.8%
Decimal Number 475
 
19.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 635
31.8%
구 66
 
3.3%
대 51
 
2.6%
연 45
 
2.3%
천 39
 
2.0%
부 39
 
2.0%
정 39
 
2.0%
산 36
 
1.8%
장 34
 
1.7%
서 30
 
1.5%
Other values (96) 984
49.2%
Decimal Number
ValueCountFrequency (%)
1 171
36.0%
2 159
33.5%
3 79
16.6%
4 39
 
8.2%
5 12
 
2.5%
6 9
 
1.9%
8 3
 
0.6%
9 3
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1998
80.8%
Common 475
 
19.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 635
31.8%
구 66
 
3.3%
대 51
 
2.6%
연 45
 
2.3%
천 39
 
2.0%
부 39
 
2.0%
정 39
 
2.0%
산 36
 
1.8%
장 34
 
1.7%
서 30
 
1.5%
Other values (96) 984
49.2%
Common
ValueCountFrequency (%)
1 171
36.0%
2 159
33.5%
3 79
16.6%
4 39
 
8.2%
5 12
 
2.5%
6 9
 
1.9%
8 3
 
0.6%
9 3
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1998
80.8%
ASCII 475
 
19.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 635
31.8%
구 66
 
3.3%
대 51
 
2.6%
연 45
 
2.3%
천 39
 
2.0%
부 39
 
2.0%
정 39
 
2.0%
산 36
 
1.8%
장 34
 
1.7%
서 30
 
1.5%
Other values (96) 984
49.2%
ASCII
ValueCountFrequency (%)
1 171
36.0%
2 159
33.5%
3 79
16.6%
4 39
 
8.2%
5 12
 
2.5%
6 9
 
1.9%
8 3
 
0.6%
9 3
 
0.6%

일반수급자 가구수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct469
Distinct (%)70.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean634.4033
Minimum0
Maximum4680
Zeros10
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size6.0 KiB
2024-03-23T07:05:20.353005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q1344.5
median509
Q3779
95-th percentile1517.8
Maximum4680
Range4680
Interquartile range (IQR)434.5

Descriptive statistics

Standard deviation592.87192
Coefficient of variation (CV)0.93453474
Kurtosis13.204381
Mean634.4033
Median Absolute Deviation (MAD)205
Skewness3.0485726
Sum423147
Variance351497.11
MonotonicityNot monotonic
2024-03-23T07:05:20.807382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 11
 
1.6%
0 10
 
1.5%
2 8
 
1.2%
4 7
 
1.0%
3 6
 
0.9%
491 5
 
0.7%
337 4
 
0.6%
359 4
 
0.6%
276 4
 
0.6%
403 4
 
0.6%
Other values (459) 604
90.6%
ValueCountFrequency (%)
0 10
1.5%
1 11
1.6%
2 8
1.2%
3 6
0.9%
4 7
1.0%
5 1
 
0.1%
6 4
 
0.6%
7 1
 
0.1%
12 1
 
0.1%
17 2
 
0.3%
ValueCountFrequency (%)
4680 1
0.1%
4580 1
0.1%
4539 1
0.1%
3407 1
0.1%
3307 1
0.1%
3290 1
0.1%
3254 1
0.1%
3249 1
0.1%
3224 1
0.1%
2860 1
0.1%

일반수급자 수급권자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct501
Distinct (%)75.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean822.29535
Minimum0
Maximum5609
Zeros15
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size6.0 KiB
2024-03-23T07:05:21.234149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q1429
median660
Q3993
95-th percentile1916.8
Maximum5609
Range5609
Interquartile range (IQR)564

Descriptive statistics

Standard deviation754.5613
Coefficient of variation (CV)0.91762807
Kurtosis11.430168
Mean822.29535
Median Absolute Deviation (MAD)268
Skewness2.8646293
Sum548471
Variance569362.75
MonotonicityNot monotonic
2024-03-23T07:05:21.632280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 15
 
2.2%
2 10
 
1.5%
1 7
 
1.0%
3 6
 
0.9%
5 5
 
0.7%
692 4
 
0.6%
564 4
 
0.6%
502 3
 
0.4%
779 3
 
0.4%
1167 3
 
0.4%
Other values (491) 607
91.0%
ValueCountFrequency (%)
0 15
2.2%
1 7
1.0%
2 10
1.5%
3 6
 
0.9%
4 3
 
0.4%
5 5
 
0.7%
6 2
 
0.3%
11 1
 
0.1%
17 2
 
0.3%
18 1
 
0.1%
ValueCountFrequency (%)
5609 1
0.1%
5520 1
0.1%
5507 1
0.1%
4486 1
0.1%
4454 1
0.1%
4213 1
0.1%
4010 1
0.1%
3895 1
0.1%
3891 1
0.1%
3875 1
0.1%

조건부수급자 가구수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct229
Distinct (%)34.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.529235
Minimum0
Maximum596
Zeros45
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size6.0 KiB
2024-03-23T07:05:22.116225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q134
median62
Q3124
95-th percentile249.4
Maximum596
Range596
Interquartile range (IQR)90

Descriptive statistics

Standard deviation86.497793
Coefficient of variation (CV)0.96614019
Kurtosis6.9390851
Mean89.529235
Median Absolute Deviation (MAD)38
Skewness2.1594305
Sum59716
Variance7481.8681
MonotonicityNot monotonic
2024-03-23T07:05:22.748778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 45
 
6.7%
43 10
 
1.5%
47 10
 
1.5%
54 9
 
1.3%
63 9
 
1.3%
18 8
 
1.2%
40 8
 
1.2%
53 8
 
1.2%
25 8
 
1.2%
58 8
 
1.2%
Other values (219) 544
81.6%
ValueCountFrequency (%)
0 45
6.7%
1 5
 
0.7%
2 5
 
0.7%
3 1
 
0.1%
4 3
 
0.4%
6 1
 
0.1%
7 2
 
0.3%
8 2
 
0.3%
9 2
 
0.3%
10 3
 
0.4%
ValueCountFrequency (%)
596 1
0.1%
571 1
0.1%
557 1
0.1%
523 1
0.1%
519 1
0.1%
488 1
0.1%
428 1
0.1%
395 1
0.1%
377 1
0.1%
370 1
0.1%

조건부수급자 수급권자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct303
Distinct (%)45.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean156.003
Minimum0
Maximum1071
Zeros49
Zeros (%)7.3%
Negative0
Negative (%)0.0%
Memory size6.0 KiB
2024-03-23T07:05:23.201583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q158
median107
Q3218
95-th percentile442.6
Maximum1071
Range1071
Interquartile range (IQR)160

Descriptive statistics

Standard deviation155.63178
Coefficient of variation (CV)0.99762047
Kurtosis7.5129486
Mean156.003
Median Absolute Deviation (MAD)64
Skewness2.2892827
Sum104054
Variance24221.252
MonotonicityNot monotonic
2024-03-23T07:05:23.687669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 49
 
7.3%
84 9
 
1.3%
68 8
 
1.2%
112 7
 
1.0%
99 7
 
1.0%
48 7
 
1.0%
106 7
 
1.0%
77 6
 
0.9%
158 6
 
0.9%
93 6
 
0.9%
Other values (293) 555
83.2%
ValueCountFrequency (%)
0 49
7.3%
1 3
 
0.4%
2 1
 
0.1%
4 1
 
0.1%
5 1
 
0.1%
6 3
 
0.4%
7 1
 
0.1%
8 1
 
0.1%
10 1
 
0.1%
12 2
 
0.3%
ValueCountFrequency (%)
1071 1
0.1%
996 1
0.1%
994 1
0.1%
956 1
0.1%
952 1
0.1%
893 1
0.1%
807 1
0.1%
766 1
0.1%
713 1
0.1%
657 2
0.3%

특례수급자 가구수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct67
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.535232
Minimum0
Maximum151
Zeros66
Zeros (%)9.9%
Negative0
Negative (%)0.0%
Memory size6.0 KiB
2024-03-23T07:05:24.091522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median11
Q318
95-th percentile45
Maximum151
Range151
Interquartile range (IQR)14

Descriptive statistics

Standard deviation16.410643
Coefficient of variation (CV)1.1290251
Kurtosis16.145882
Mean14.535232
Median Absolute Deviation (MAD)7
Skewness3.1912582
Sum9695
Variance269.30919
MonotonicityNot monotonic
2024-03-23T07:05:24.596246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 66
 
9.9%
7 34
 
5.1%
4 30
 
4.5%
10 29
 
4.3%
2 27
 
4.0%
11 26
 
3.9%
3 26
 
3.9%
9 25
 
3.7%
13 25
 
3.7%
12 24
 
3.6%
Other values (57) 355
53.2%
ValueCountFrequency (%)
0 66
9.9%
1 24
 
3.6%
2 27
4.0%
3 26
 
3.9%
4 30
4.5%
5 22
 
3.3%
6 24
 
3.6%
7 34
5.1%
8 23
 
3.4%
9 25
 
3.7%
ValueCountFrequency (%)
151 1
0.1%
131 1
0.1%
125 1
0.1%
91 1
0.1%
83 1
0.1%
82 1
0.1%
81 1
0.1%
77 1
0.1%
75 1
0.1%
74 1
0.1%

특례수급자 수급권자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct85
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.853073
Minimum0
Maximum198
Zeros66
Zeros (%)9.9%
Negative0
Negative (%)0.0%
Memory size6.0 KiB
2024-03-23T07:05:25.088037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median14
Q324
95-th percentile55
Maximum198
Range198
Interquartile range (IQR)19

Descriptive statistics

Standard deviation21.241907
Coefficient of variation (CV)1.1267079
Kurtosis15.592298
Mean18.853073
Median Absolute Deviation (MAD)9
Skewness3.1028514
Sum12575
Variance451.21862
MonotonicityNot monotonic
2024-03-23T07:05:25.570642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 66
 
9.9%
4 30
 
4.5%
2 28
 
4.2%
21 25
 
3.7%
11 23
 
3.4%
15 22
 
3.3%
14 22
 
3.3%
13 22
 
3.3%
23 21
 
3.1%
12 21
 
3.1%
Other values (75) 387
58.0%
ValueCountFrequency (%)
0 66
9.9%
1 17
 
2.5%
2 28
4.2%
3 15
 
2.2%
4 30
4.5%
5 20
 
3.0%
6 17
 
2.5%
7 15
 
2.2%
8 18
 
2.7%
9 15
 
2.2%
ValueCountFrequency (%)
198 1
0.1%
166 1
0.1%
157 1
0.1%
113 1
0.1%
112 1
0.1%
104 1
0.1%
103 1
0.1%
96 1
0.1%
95 1
0.1%
92 1
0.1%

기타 가구수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
0
659 
1
 
6
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 659
98.8%
1 6
 
0.9%
4 2
 
0.3%

Length

2024-03-23T07:05:26.192799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:05:26.480045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 659
98.8%
1 6
 
0.9%
4 2
 
0.3%

기타 수급권자수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
0
658 
1
 
6
5
 
1
6
 
1
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique3 ?
Unique (%)0.4%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 658
98.7%
1 6
 
0.9%
5 1
 
0.1%
6 1
 
0.1%
2 1
 
0.1%

Length

2024-03-23T07:05:26.788773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:05:27.228099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 658
98.7%
1 6
 
0.9%
5 1
 
0.1%
6 1
 
0.1%
2 1
 
0.1%

시설수급자 가구수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct92
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.898051
Minimum0
Maximum522
Zeros281
Zeros (%)42.1%
Negative0
Negative (%)0.0%
Memory size6.0 KiB
2024-03-23T07:05:27.735204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q37
95-th percentile105
Maximum522
Range522
Interquartile range (IQR)7

Descriptive statistics

Standard deviation69.982506
Coefficient of variation (CV)3.3487576
Kurtosis26.532801
Mean20.898051
Median Absolute Deviation (MAD)1
Skewness4.99237
Sum13939
Variance4897.5512
MonotonicityNot monotonic
2024-03-23T07:05:28.322350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 281
42.1%
1 91
 
13.6%
3 35
 
5.2%
2 33
 
4.9%
4 23
 
3.4%
5 17
 
2.5%
6 15
 
2.2%
9 12
 
1.8%
12 12
 
1.8%
7 11
 
1.6%
Other values (82) 137
20.5%
ValueCountFrequency (%)
0 281
42.1%
1 91
 
13.6%
2 33
 
4.9%
3 35
 
5.2%
4 23
 
3.4%
5 17
 
2.5%
6 15
 
2.2%
7 11
 
1.6%
8 4
 
0.6%
9 12
 
1.8%
ValueCountFrequency (%)
522 1
0.1%
502 1
0.1%
492 1
0.1%
487 1
0.1%
473 1
0.1%
446 1
0.1%
440 1
0.1%
436 1
0.1%
431 1
0.1%
422 1
0.1%

시설수급자 수급권자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct92
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.898051
Minimum0
Maximum522
Zeros281
Zeros (%)42.1%
Negative0
Negative (%)0.0%
Memory size6.0 KiB
2024-03-23T07:05:29.145687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q37
95-th percentile105
Maximum522
Range522
Interquartile range (IQR)7

Descriptive statistics

Standard deviation69.982506
Coefficient of variation (CV)3.3487576
Kurtosis26.532801
Mean20.898051
Median Absolute Deviation (MAD)1
Skewness4.99237
Sum13939
Variance4897.5512
MonotonicityNot monotonic
2024-03-23T07:05:29.890018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 281
42.1%
1 91
 
13.6%
3 35
 
5.2%
2 33
 
4.9%
4 23
 
3.4%
5 17
 
2.5%
6 15
 
2.2%
9 12
 
1.8%
12 12
 
1.8%
7 11
 
1.6%
Other values (82) 137
20.5%
ValueCountFrequency (%)
0 281
42.1%
1 91
 
13.6%
2 33
 
4.9%
3 35
 
5.2%
4 23
 
3.4%
5 17
 
2.5%
6 15
 
2.2%
7 11
 
1.6%
8 4
 
0.6%
9 12
 
1.8%
ValueCountFrequency (%)
522 1
0.1%
502 1
0.1%
492 1
0.1%
487 1
0.1%
473 1
0.1%
446 1
0.1%
440 1
0.1%
436 1
0.1%
431 1
0.1%
422 1
0.1%

Interactions

2024-03-23T07:05:12.559117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:50.649398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:53.505920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:56.643203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:00.628897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:03.483092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:06.563342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:09.257062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:12.876064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:51.000709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:53.875041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:57.130579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:00.880214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:03.780185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:06.896822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:09.626410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:13.338116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:51.382520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:54.181426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:57.850907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:01.180964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:04.195968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:07.201860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:09.899273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:13.819421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:51.922120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:54.504157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:58.543505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:01.535629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:04.544717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:07.533751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:10.274764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:14.269509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:52.206445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:54.819814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:58.985288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:01.962220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:04.989052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:07.886061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:10.579255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:14.571205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:52.515102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:55.222085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:59.476688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:02.461357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:05.450985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:08.243552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:11.332692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:14.881610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:52.883615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:55.627507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:59.875944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:02.861575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:05.898419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:08.572916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:11.727744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:15.157542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:53.236498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:04:56.133463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:00.273476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:03.197908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:06.180903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:08.939070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:05:12.071946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T07:05:30.402345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도시군구일반수급자 가구수일반수급자 수급권자수조건부수급자 가구수조건부수급자 수급권자수특례수급자 가구수특례수급자 수급권자수기타 가구수기타 수급권자수시설수급자 가구수시설수급자 수급권자수
연도1.0000.0000.0000.0000.2010.1130.0000.0000.0930.0000.0000.000
시군구0.0001.0000.5620.5370.4940.5210.4700.4820.1010.0000.3420.342
일반수급자 가구수0.0000.5621.0000.9890.7770.7990.9170.8930.3010.2770.0000.000
일반수급자 수급권자수0.0000.5370.9891.0000.7900.7950.9130.9340.1200.2360.0000.000
조건부수급자 가구수0.2010.4940.7770.7901.0000.9880.6770.7180.0560.2360.0000.000
조건부수급자 수급권자수0.1130.5210.7990.7950.9881.0000.6880.7210.0940.2500.0000.000
특례수급자 가구수0.0000.4700.9170.9130.6770.6881.0000.9840.0000.0580.0000.000
특례수급자 수급권자수0.0000.4820.8930.9340.7180.7210.9841.0000.0000.0000.0000.000
기타 가구수0.0930.1010.3010.1200.0560.0940.0000.0001.0000.9140.0000.000
기타 수급권자수0.0000.0000.2770.2360.2360.2500.0580.0000.9141.0000.0000.000
시설수급자 가구수0.0000.3420.0000.0000.0000.0000.0000.0000.0000.0001.0001.000
시설수급자 수급권자수0.0000.3420.0000.0000.0000.0000.0000.0000.0000.0001.0001.000
2024-03-23T07:05:31.120711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기타 수급권자수시군구기타 가구수연도
기타 수급권자수1.0000.0000.9630.000
시군구0.0001.0000.0530.000
기타 가구수0.9630.0531.0000.027
연도0.0000.0000.0271.000
2024-03-23T07:05:31.762242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일반수급자 가구수일반수급자 수급권자수조건부수급자 가구수조건부수급자 수급권자수특례수급자 가구수특례수급자 수급권자수시설수급자 가구수시설수급자 수급권자수연도시군구기타 가구수기타 수급권자수
일반수급자 가구수1.0000.9950.8400.8280.7430.7320.0930.0930.0000.2700.1380.163
일반수급자 수급권자수0.9951.0000.8350.8310.7380.7310.1020.1020.0000.2530.0520.138
조건부수급자 가구수0.8400.8351.0000.9890.6020.5980.0740.0740.1210.2170.0330.099
조건부수급자 수급권자수0.8280.8310.9891.0000.6000.6010.0940.0940.0670.2320.0560.106
특례수급자 가구수0.7430.7380.6020.6001.0000.9880.0160.0160.0000.2130.0000.033
특례수급자 수급권자수0.7320.7310.5980.6010.9881.0000.0130.0130.0000.2200.0000.000
시설수급자 가구수0.0930.1020.0740.0940.0160.0131.0001.0000.0000.1400.0000.000
시설수급자 수급권자수0.0930.1020.0740.0940.0160.0131.0001.0000.0000.1400.0000.000
연도0.0000.0000.1210.0670.0000.0000.0000.0001.0000.0000.0270.000
시군구0.2700.2530.2170.2320.2130.2200.1400.1400.0001.0000.0530.000
기타 가구수0.1380.0520.0330.0560.0000.0000.0000.0000.0270.0531.0000.963
기타 수급권자수0.1630.1380.0990.1060.0330.0000.0000.0000.0000.0000.9631.000

Missing values

2024-03-23T07:05:15.553792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T07:05:16.147044image/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

연도시도시군구읍면동일반수급자 가구수일반수급자 수급권자수조건부수급자 가구수조건부수급자 수급권자수특례수급자 가구수특례수급자 수급권자수기타 가구수기타 수급권자수시설수급자 가구수시설수급자 수급권자수
02021부산광역시중구중구0000000044
12021부산광역시중구중앙동12115418241111001212
22021부산광역시중구동광동3163623044330000
32021부산광역시중구대청동4325375410315190000
42021부산광역시중구보수동7108499415822280000
52021부산광역시중구부평동32436653798110000
62021부산광역시중구광복동587222110000
72021부산광역시중구남포동88921717000000
82021부산광역시중구영주1동3463944876330011
92021부산광역시중구영주2동499603548720260000
연도시도시군구읍면동일반수급자 가구수일반수급자 수급권자수조건부수급자 가구수조건부수급자 수급권자수특례수급자 가구수특례수급자 수급권자수기타 가구수기타 수급권자수시설수급자 가구수시설수급자 수급권자수
6572023부산광역시사상구주례3동3374595512716230033
6582023부산광역시사상구학장동123315091452723037003030
6592023부산광역시사상구엄궁동442607611442837001414
6602023부산광역시기장군기장군66000000169169
6612023부산광역시기장군기장읍274036774287662934001111
6622023부산광역시기장군장안읍456552467922003636
6632023부산광역시기장군정관읍2733445437780766103004343
6642023부산광역시기장군일광읍5407288515122003838
6652023부산광역시기장군일광면2200000000
6662023부산광역시기장군철마면54874574137120033