Overview

Dataset statistics

Number of variables13
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory122.0 B

Variable types

Text1
Numeric10
Categorical2

Dataset

Description2023년 기준 경상북도 기초생활수급자 수 현황(22개 시군별 수급가구 및 수급자 수, 행정구역 개편으로 당초 23개 시군에서 22개 시군으로 변경)
Author경상북도
URLhttps://www.data.go.kr/data/15063365/fileData.do

Alerts

가구수(계) is highly overall correlated with 수급권자수(계) and 10 other fieldsHigh correlation
수급권자수(계) is highly overall correlated with 가구수(계) and 10 other fieldsHigh correlation
일반수급 가구수 is highly overall correlated with 가구수(계) and 10 other fieldsHigh correlation
일반 수급권자수 is highly overall correlated with 가구수(계) and 10 other fieldsHigh correlation
조건부 수급자 가구수 is highly overall correlated with 가구수(계) and 10 other fieldsHigh correlation
조건부 수급권자수 is highly overall correlated with 가구수(계) and 10 other fieldsHigh correlation
특례수급 가구수 is highly overall correlated with 가구수(계) and 8 other fieldsHigh correlation
특례 수급권자수 is highly overall correlated with 가구수(계) and 8 other fieldsHigh correlation
시설수급자 가구수 is highly overall correlated with 가구수(계) and 10 other fieldsHigh correlation
시설 수급권자수 is highly overall correlated with 가구수(계) and 10 other fieldsHigh correlation
기타 수급 가구수 is highly overall correlated with 가구수(계) and 7 other fieldsHigh correlation
기타 수급권자수 is highly overall correlated with 가구수(계) and 7 other fieldsHigh correlation
기타 수급 가구수 is highly imbalanced (73.3%)Imbalance
기타 수급권자수 is highly imbalanced (73.3%)Imbalance
시군명 has unique valuesUnique
가구수(계) has unique valuesUnique
수급권자수(계) has unique valuesUnique
일반수급 가구수 has unique valuesUnique
일반 수급권자수 has unique valuesUnique
특례수급 가구수 has unique valuesUnique
시설수급자 가구수 has unique valuesUnique
시설 수급권자수 has unique valuesUnique

Reproduction

Analysis started2023-12-16 15:28:07.858321
Analysis finished2023-12-16 15:29:02.751238
Duration54.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-16T15:29:03.235458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters66
Distinct characters33
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

Unique22 ?
Unique (%)100.0%

Sample

1st row포항시
2nd row경주시
3rd row김천시
4th row안동시
5th row구미시
ValueCountFrequency (%)
포항시 1
 
4.5%
경주시 1
 
4.5%
울진군 1
 
4.5%
봉화군 1
 
4.5%
예천군 1
 
4.5%
칠곡군 1
 
4.5%
성주군 1
 
4.5%
고령군 1
 
4.5%
청도군 1
 
4.5%
영덕군 1
 
4.5%
Other values (12) 12
54.5%
2023-12-16T15:29:04.937172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 12
18.2%
시 10
15.2%
주 4
 
6.1%
영 4
 
6.1%
경 3
 
4.5%
천 3
 
4.5%
성 2
 
3.0%
청 2
 
3.0%
울 2
 
3.0%
칠 1
 
1.5%
Other values (23) 23
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 12
18.2%
시 10
15.2%
주 4
 
6.1%
영 4
 
6.1%
경 3
 
4.5%
천 3
 
4.5%
성 2
 
3.0%
청 2
 
3.0%
울 2
 
3.0%
칠 1
 
1.5%
Other values (23) 23
34.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 12
18.2%
시 10
15.2%
주 4
 
6.1%
영 4
 
6.1%
경 3
 
4.5%
천 3
 
4.5%
성 2
 
3.0%
청 2
 
3.0%
울 2
 
3.0%
칠 1
 
1.5%
Other values (23) 23
34.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 12
18.2%
시 10
15.2%
주 4
 
6.1%
영 4
 
6.1%
경 3
 
4.5%
천 3
 
4.5%
성 2
 
3.0%
청 2
 
3.0%
울 2
 
3.0%
칠 1
 
1.5%
Other values (23) 23
34.8%

가구수(계)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5222.4545
Minimum274
Maximum23161
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-16T15:29:05.642348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum274
5-th percentile958.95
Q11997
median2946
Q36435
95-th percentile10672.55
Maximum23161
Range22887
Interquartile range (IQR)4438

Descriptive statistics

Standard deviation5168.3091
Coefficient of variation (CV)0.98963219
Kurtosis6.1252451
Mean5222.4545
Median Absolute Deviation (MAD)1693
Skewness2.1925827
Sum114894
Variance26711419
MonotonicityNot monotonic
2023-12-16T15:29:06.894643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
23161 1
 
4.5%
940 1
 
4.5%
274 1
 
4.5%
2701 1
 
4.5%
1466 1
 
4.5%
2447 1
 
4.5%
4705 1
 
4.5%
1994 1
 
4.5%
1809 1
 
4.5%
2006 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
274 1
4.5%
940 1
4.5%
1319 1
4.5%
1466 1
4.5%
1809 1
4.5%
1994 1
4.5%
2006 1
4.5%
2447 1
4.5%
2456 1
4.5%
2701 1
4.5%
ValueCountFrequency (%)
23161 1
4.5%
10677 1
4.5%
10588 1
4.5%
10428 1
4.5%
8817 1
4.5%
6535 1
4.5%
6135 1
4.5%
6008 1
4.5%
4705 1
4.5%
4536 1
4.5%

수급권자수(계)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6864.9545
Minimum341
Maximum31347
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-16T15:29:07.699709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum341
5-th percentile1250.3
Q12460.75
median3520
Q38410.75
95-th percentile14662.6
Maximum31347
Range31006
Interquartile range (IQR)5950

Descriptive statistics

Standard deviation7051.1909
Coefficient of variation (CV)1.0271286
Kurtosis6.1472636
Mean6864.9545
Median Absolute Deviation (MAD)2230.5
Skewness2.2122818
Sum151029
Variance49719293
MonotonicityNot monotonic
2023-12-16T15:29:08.335346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
31347 1
 
4.5%
1232 1
 
4.5%
341 1
 
4.5%
3306 1
 
4.5%
1805 1
 
4.5%
3159 1
 
4.5%
6624 1
 
4.5%
2499 1
 
4.5%
2338 1
 
4.5%
2448 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
341 1
4.5%
1232 1
4.5%
1598 1
4.5%
1805 1
4.5%
2338 1
4.5%
2448 1
4.5%
2499 1
4.5%
2988 1
4.5%
3159 1
4.5%
3306 1
4.5%
ValueCountFrequency (%)
31347 1
4.5%
14671 1
4.5%
14503 1
4.5%
13853 1
4.5%
11318 1
4.5%
8574 1
4.5%
7921 1
4.5%
7771 1
4.5%
6624 1
4.5%
5693 1
4.5%

일반수급 가구수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4419.0909
Minimum261
Maximum20326
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-16T15:29:09.129588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum261
5-th percentile850.8
Q11764
median2586
Q35454.5
95-th percentile8984.75
Maximum20326
Range20065
Interquartile range (IQR)3690.5

Descriptive statistics

Standard deviation4407.426
Coefficient of variation (CV)0.99736035
Kurtosis7.6007425
Mean4419.0909
Median Absolute Deviation (MAD)1438.5
Skewness2.4353737
Sum97220
Variance19425404
MonotonicityNot monotonic
2023-12-16T15:29:10.461559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
20326 1
 
4.5%
836 1
 
4.5%
261 1
 
4.5%
2446 1
 
4.5%
1330 1
 
4.5%
2187 1
 
4.5%
4009 1
 
4.5%
1740 1
 
4.5%
1498 1
 
4.5%
1836 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
261 1
4.5%
836 1
4.5%
1132 1
4.5%
1330 1
4.5%
1498 1
4.5%
1740 1
4.5%
1836 1
4.5%
2187 1
4.5%
2244 1
4.5%
2446 1
4.5%
ValueCountFrequency (%)
20326 1
4.5%
9008 1
4.5%
8543 1
4.5%
8347 1
4.5%
6727 1
4.5%
5505 1
4.5%
5303 1
4.5%
4995 1
4.5%
4009 1
4.5%
3775 1
4.5%

일반 수급권자수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5734.0455
Minimum328
Maximum26754
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-16T15:29:11.343415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum328
5-th percentile1118.7
Q12206.75
median3086.5
Q37146.25
95-th percentile11591.95
Maximum26754
Range26426
Interquartile range (IQR)4939.5

Descriptive statistics

Standard deviation5844.035
Coefficient of variation (CV)1.0191818
Kurtosis7.4596666
Mean5734.0455
Median Absolute Deviation (MAD)1844.5
Skewness2.4189793
Sum126149
Variance34152746
MonotonicityNot monotonic
2023-12-16T15:29:12.090578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
26754 1
 
4.5%
1105 1
 
4.5%
328 1
 
4.5%
2969 1
 
4.5%
1648 1
 
4.5%
2805 1
 
4.5%
5683 1
 
4.5%
2194 1
 
4.5%
2000 1
 
4.5%
2245 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
328 1
4.5%
1105 1
4.5%
1379 1
4.5%
1648 1
4.5%
2000 1
4.5%
2194 1
4.5%
2245 1
4.5%
2746 1
4.5%
2805 1
4.5%
2959 1
4.5%
ValueCountFrequency (%)
26754 1
4.5%
11600 1
4.5%
11439 1
4.5%
11312 1
4.5%
8535 1
4.5%
7219 1
4.5%
6928 1
4.5%
6424 1
4.5%
5683 1
4.5%
4673 1
4.5%

조건부 수급자 가구수
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean386.63636
Minimum2
Maximum1908
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-16T15:29:13.098445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile26.3
Q147.75
median106
Q3442.25
95-th percentile1486.3
Maximum1908
Range1906
Interquartile range (IQR)394.5

Descriptive statistics

Standard deviation533.66322
Coefficient of variation (CV)1.3802717
Kurtosis2.3435212
Mean386.63636
Median Absolute Deviation (MAD)77
Skewness1.7386981
Sum8506
Variance284796.43
MonotonicityNot monotonic
2023-12-16T15:29:13.876439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
52 2
 
9.1%
1908 1
 
4.5%
998 1
 
4.5%
2 1
 
4.5%
90 1
 
4.5%
32 1
 
4.5%
96 1
 
4.5%
276 1
 
4.5%
35 1
 
4.5%
47 1
 
4.5%
Other values (11) 11
50.0%
ValueCountFrequency (%)
2 1
4.5%
26 1
4.5%
32 1
4.5%
35 1
4.5%
40 1
4.5%
47 1
4.5%
50 1
4.5%
52 2
9.1%
90 1
4.5%
96 1
4.5%
ValueCountFrequency (%)
1908 1
4.5%
1512 1
4.5%
998 1
4.5%
995 1
4.5%
871 1
4.5%
459 1
4.5%
392 1
4.5%
291 1
4.5%
276 1
4.5%
166 1
4.5%

조건부 수급권자수
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean698.86364
Minimum2
Maximum3632
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-16T15:29:14.528341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile49.1
Q169.5
median200.5
Q3761.5
95-th percentile2597.55
Maximum3632
Range3630
Interquartile range (IQR)692

Descriptive statistics

Standard deviation981.59255
Coefficient of variation (CV)1.4045552
Kurtosis2.9046703
Mean698.86364
Median Absolute Deviation (MAD)150.5
Skewness1.8306683
Sum15375
Variance963523.93
MonotonicityNot monotonic
2023-12-16T15:29:14.994602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
66 2
 
9.1%
80 2
 
9.1%
82 1
 
4.5%
2 1
 
4.5%
158 1
 
4.5%
51 1
 
4.5%
187 1
 
4.5%
514 1
 
4.5%
60 1
 
4.5%
49 1
 
4.5%
Other values (10) 10
45.5%
ValueCountFrequency (%)
2 1
4.5%
49 1
4.5%
51 1
4.5%
60 1
4.5%
66 2
9.1%
80 2
9.1%
82 1
4.5%
158 1
4.5%
187 1
4.5%
214 1
4.5%
ValueCountFrequency (%)
3632 1
4.5%
2638 1
4.5%
1829 1
4.5%
1806 1
4.5%
1524 1
4.5%
783 1
4.5%
697 1
4.5%
543 1
4.5%
514 1
4.5%
314 1
4.5%

특례수급 가구수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.681818
Minimum1
Maximum187
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-16T15:29:15.758569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.25
Q120
median45.5
Q378
95-th percentile180.7
Maximum187
Range186
Interquartile range (IQR)58

Descriptive statistics

Standard deviation60.806004
Coefficient of variation (CV)0.92576615
Kurtosis-0.086130737
Mean65.681818
Median Absolute Deviation (MAD)31
Skewness1.0858396
Sum1445
Variance3697.3701
MonotonicityNot monotonic
2023-12-16T15:29:16.501152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
187 1
 
4.5%
10 1
 
4.5%
1 1
 
4.5%
50 1
 
4.5%
14 1
 
4.5%
15 1
 
4.5%
43 1
 
4.5%
54 1
 
4.5%
8 1
 
4.5%
41 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
1 1
4.5%
3 1
4.5%
8 1
4.5%
10 1
4.5%
14 1
4.5%
15 1
4.5%
35 1
4.5%
39 1
4.5%
41 1
4.5%
43 1
4.5%
ValueCountFrequency (%)
187 1
4.5%
181 1
4.5%
175 1
4.5%
170 1
4.5%
118 1
4.5%
80 1
4.5%
72 1
4.5%
58 1
4.5%
54 1
4.5%
50 1
4.5%

특례 수급권자수
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81
Minimum1
Maximum221
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-16T15:29:17.112329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.35
Q124
median60
Q392.75
95-th percentile220.8
Maximum221
Range220
Interquartile range (IQR)68.75

Descriptive statistics

Standard deviation74.570516
Coefficient of variation (CV)0.92062366
Kurtosis-0.14709761
Mean81
Median Absolute Deviation (MAD)37.5
Skewness1.0469956
Sum1782
Variance5560.7619
MonotonicityNot monotonic
2023-12-16T15:29:17.894207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
221 2
 
9.1%
10 2
 
9.1%
1 1
 
4.5%
64 1
 
4.5%
16 1
 
4.5%
18 1
 
4.5%
50 1
 
4.5%
77 1
 
4.5%
46 1
 
4.5%
56 1
 
4.5%
Other values (10) 10
45.5%
ValueCountFrequency (%)
1 1
4.5%
3 1
4.5%
10 2
9.1%
16 1
4.5%
18 1
4.5%
42 1
4.5%
46 1
4.5%
49 1
4.5%
50 1
4.5%
56 1
4.5%
ValueCountFrequency (%)
221 2
9.1%
217 1
4.5%
216 1
4.5%
143 1
4.5%
93 1
4.5%
92 1
4.5%
77 1
4.5%
71 1
4.5%
66 1
4.5%
64 1
4.5%

기타 수급 가구수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
0
21 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.5%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21
95.5%
1 1
 
4.5%

Length

2023-12-16T15:29:18.556586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:29:19.095138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
95.5%
1 1
 
4.5%

기타 수급권자수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
0
21 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.5%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21
95.5%
1 1
 
4.5%

Length

2023-12-16T15:29:19.602790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T15:29:20.092955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
95.5%
1 1
 
4.5%

시설수급자 가구수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean351
Minimum10
Maximum1038
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-16T15:29:20.574008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile68.45
Q1123.5
median265.5
Q3510.25
95-th percentile872.95
Maximum1038
Range1028
Interquartile range (IQR)386.75

Descriptive statistics

Standard deviation283.30801
Coefficient of variation (CV)0.80714533
Kurtosis0.18622393
Mean351
Median Absolute Deviation (MAD)180.5
Skewness0.93248919
Sum7722
Variance80263.429
MonotonicityNot monotonic
2023-12-16T15:29:21.201198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
739 1
 
4.5%
68 1
 
4.5%
10 1
 
4.5%
115 1
 
4.5%
90 1
 
4.5%
149 1
 
4.5%
377 1
 
4.5%
148 1
 
4.5%
268 1
 
4.5%
77 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
10 1
4.5%
68 1
4.5%
77 1
4.5%
90 1
4.5%
115 1
4.5%
120 1
4.5%
134 1
4.5%
148 1
4.5%
149 1
4.5%
197 1
4.5%
ValueCountFrequency (%)
1038 1
4.5%
880 1
4.5%
739 1
4.5%
586 1
4.5%
566 1
4.5%
515 1
4.5%
496 1
4.5%
451 1
4.5%
435 1
4.5%
377 1
4.5%

시설 수급권자수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean351
Minimum10
Maximum1038
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-16T15:29:21.928376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile68.45
Q1123.5
median265.5
Q3510.25
95-th percentile872.95
Maximum1038
Range1028
Interquartile range (IQR)386.75

Descriptive statistics

Standard deviation283.30801
Coefficient of variation (CV)0.80714533
Kurtosis0.18622393
Mean351
Median Absolute Deviation (MAD)180.5
Skewness0.93248919
Sum7722
Variance80263.429
MonotonicityNot monotonic
2023-12-16T15:29:22.525884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
739 1
 
4.5%
68 1
 
4.5%
10 1
 
4.5%
115 1
 
4.5%
90 1
 
4.5%
149 1
 
4.5%
377 1
 
4.5%
148 1
 
4.5%
268 1
 
4.5%
77 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
10 1
4.5%
68 1
4.5%
77 1
4.5%
90 1
4.5%
115 1
4.5%
120 1
4.5%
134 1
4.5%
148 1
4.5%
149 1
4.5%
197 1
4.5%
ValueCountFrequency (%)
1038 1
4.5%
880 1
4.5%
739 1
4.5%
586 1
4.5%
566 1
4.5%
515 1
4.5%
496 1
4.5%
451 1
4.5%
435 1
4.5%
377 1
4.5%

Interactions

2023-12-16T15:28:55.113685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:09.812022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:15.205072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:19.572227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:25.506457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:29.475229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:33.583129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:40.055826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:45.281398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:50.226815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:55.536759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:10.319916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:15.803314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:20.023086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:25.728538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:29.997104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:34.574224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:40.435065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:45.742809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:50.478076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:56.193913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:11.119656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:16.095543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:20.530795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:26.099369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:30.614321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:34.958059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:40.857784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:46.358759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:50.862301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:57.010090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:11.771291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:16.449396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:21.047959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:26.442217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:30.937800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:35.921170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:41.398879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:47.000534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:51.376116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:57.760001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:12.157024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:16.907858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:21.626857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:26.822473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:31.218877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:36.327253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:42.137569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:47.464528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:51.755139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:58.336771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:12.620841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:17.441665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:22.260378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:27.312195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:31.642700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:37.192414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:42.651799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:48.003694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:52.437690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:58.789098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:13.335669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:17.993918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:22.973447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:27.778320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:32.137292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:37.692886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:43.469224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:48.538836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:53.018049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:59.212587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:13.894080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:18.456578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:23.641008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:28.167232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:32.576814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:38.370444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:43.960458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:49.004087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:53.713203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:59.896328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:14.534392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:18.759756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:24.372555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:28.642000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:32.925802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:39.059077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:44.399321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:49.562593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:54.236692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:29:00.365005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:14.921604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:19.186491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:24.874780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:29.014597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:33.210309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:39.566756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:44.919288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:49.868119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T15:28:54.594303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-16T15:29:22.897766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명가구수(계)수급권자수(계)일반수급 가구수일반 수급권자수조건부 수급자 가구수조건부 수급권자수특례수급 가구수특례 수급권자수기타 수급 가구수기타 수급권자수시설수급자 가구수시설 수급권자수
시군명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
가구수(계)1.0001.0000.9961.0000.9930.9190.8030.6080.6721.0001.0000.9240.924
수급권자수(계)1.0000.9961.0000.9960.9990.8980.8060.6030.6451.0001.0000.9200.920
일반수급 가구수1.0001.0000.9961.0000.9930.9190.8030.6080.6721.0001.0000.9240.924
일반 수급권자수1.0000.9930.9990.9931.0000.9070.8170.6810.7091.0001.0000.9170.917
조건부 수급자 가구수1.0000.9190.8980.9190.9071.0000.9870.8810.8851.0001.0000.8410.841
조건부 수급권자수1.0000.8030.8060.8030.8170.9871.0000.8490.8561.0001.0000.7610.761
특례수급 가구수1.0000.6080.6030.6080.6810.8810.8491.0000.9930.0000.0000.1770.177
특례 수급권자수1.0000.6720.6450.6720.7090.8850.8560.9931.0000.0000.0000.5790.579
기타 수급 가구수1.0001.0001.0001.0001.0001.0001.0000.0000.0001.0000.6321.0001.000
기타 수급권자수1.0001.0001.0001.0001.0001.0001.0000.0000.0000.6321.0001.0001.000
시설수급자 가구수1.0000.9240.9200.9240.9170.8410.7610.1770.5791.0001.0001.0001.000
시설 수급권자수1.0000.9240.9200.9240.9170.8410.7610.1770.5791.0001.0001.0001.000
2023-12-16T15:29:23.673537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기타 수급권자수기타 수급 가구수
기타 수급권자수1.0000.434
기타 수급 가구수0.4341.000
2023-12-16T15:29:24.057740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가구수(계)수급권자수(계)일반수급 가구수일반 수급권자수조건부 수급자 가구수조건부 수급권자수특례수급 가구수특례 수급권자수시설수급자 가구수시설 수급권자수기타 수급 가구수기타 수급권자수
가구수(계)1.0000.9931.0000.9940.9330.9270.8760.8780.8860.8860.8940.894
수급권자수(계)0.9931.0000.9930.9970.9410.9360.8710.8780.8930.8930.8940.894
일반수급 가구수1.0000.9931.0000.9940.9330.9270.8760.8780.8860.8860.8940.894
일반 수급권자수0.9940.9970.9941.0000.9360.9310.8680.8710.8870.8870.8940.894
조건부 수급자 가구수0.9330.9410.9330.9361.0000.9960.7640.7780.8480.8480.8660.866
조건부 수급권자수0.9270.9360.9270.9310.9961.0000.7450.7580.8540.8540.8660.866
특례수급 가구수0.8760.8710.8760.8680.7640.7451.0000.9950.7240.7240.0000.000
특례 수급권자수0.8780.8780.8780.8710.7780.7580.9951.0000.7580.7580.0000.000
시설수급자 가구수0.8860.8930.8860.8870.8480.8540.7240.7581.0001.0000.8060.806
시설 수급권자수0.8860.8930.8860.8870.8480.8540.7240.7581.0001.0000.8060.806
기타 수급 가구수0.8940.8940.8940.8940.8660.8660.0000.0000.8060.8061.0000.434
기타 수급권자수0.8940.8940.8940.8940.8660.8660.0000.0000.8060.8060.4341.000

Missing values

2023-12-16T15:29:01.033300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-16T15:29:02.180785image/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

시군명가구수(계)수급권자수(계)일반수급 가구수일반 수급권자수조건부 수급자 가구수조건부 수급권자수특례수급 가구수특례 수급권자수기타 수급 가구수기타 수급권자수시설수급자 가구수시설 수급권자수
0포항시231613134720326267541908363218722111739739
1경주시1067713853900811312998182917521600496496
2김천시6535857455057219392697729200566566
3안동시8817113186727853587115241812210010381038
4구미시10428146718347114391512263811814300451451
5영주시6008777149956424459783394900515515
6영천시6135792153036928166314809300586586
7상주시4536569337754673291543354200435435
8문경시2902350224772959116214466600263263
9경산시1058814503854311600995180617021700880880
시군명가구수(계)수급권자수(계)일반수급 가구수일반 수급권자수조건부 수급자 가구수조건부 수급권자수특례수급 가구수특례 수급권자수기타 수급 가구수기타 수급권자수시설수급자 가구수시설 수급권자수
12영양군9401232836110526491010006868
13영덕군24562988224427464766455600120120
14청도군200624481836224552804146007777
15고령군1809233814982000356081000268268
16성주군19942499174021945280547700148148
17칠곡군4705662440095683276514435000377377
18예천군244731592187280596187151800149149
19봉화군146618051330164832511416009090
20울진군270133062446296990158506400115115
21울릉군2743412613282211001010