Overview

Dataset statistics

Number of variables9
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory86.0 B

Variable types

Text1
Numeric8

Dataset

Description인천광역시 미추홀구 기초생활수급현황에 대한 데이터로 가구수 및 수급권자수를 일반수급자, 조건부수급자, 특례수급자, 시설수급자로 구분하여 제공합니다.<br/>
Author인천광역시 미추홀구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15071349&srcSe=7661IVAWM27C61E190

Alerts

일반수급가구수 is highly overall correlated with 일반수급자수 and 4 other fieldsHigh correlation
일반수급자수 is highly overall correlated with 일반수급가구수 and 4 other fieldsHigh correlation
조건부수급가구수 is highly overall correlated with 일반수급가구수 and 4 other fieldsHigh correlation
조건부수급자수 is highly overall correlated with 일반수급가구수 and 4 other fieldsHigh correlation
특례수급가구수 is highly overall correlated with 일반수급가구수 and 4 other fieldsHigh correlation
특례수급자수 is highly overall correlated with 일반수급가구수 and 4 other fieldsHigh correlation
시설수급가구수 is highly overall correlated with 시설수급자수High correlation
시설수급자수 is highly overall correlated with 시설수급가구수High correlation
동명 has unique valuesUnique
조건부수급자수 has unique valuesUnique
조건부수급가구수 has 1 (4.5%) zerosZeros
조건부수급자수 has 1 (4.5%) zerosZeros
특례수급가구수 has 1 (4.5%) zerosZeros
특례수급자수 has 1 (4.5%) zerosZeros
시설수급가구수 has 1 (4.5%) zerosZeros
시설수급자수 has 1 (4.5%) zerosZeros

Reproduction

Analysis started2024-05-03 19:44:06.273575
Analysis finished2024-05-03 19:44:28.834342
Duration22.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

동명
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-05-03T19:44:29.201388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.0909091
Min length2

Characters and Unicode

Total characters90
Distinct characters25
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

Unique22 ?
Unique (%)100.0%

Sample

1st row숭의2동
2nd row숭의1,3동
3rd row숭의4동
4th row용현1,4동
5th row용현2동
ValueCountFrequency (%)
숭의2동 1
 
4.5%
숭의1,3동 1
 
4.5%
문학동 1
 
4.5%
관교동 1
 
4.5%
주안8동 1
 
4.5%
주안7동 1
 
4.5%
주안6동 1
 
4.5%
주안5동 1
 
4.5%
주안4동 1
 
4.5%
주안3동 1
 
4.5%
Other values (12) 12
54.5%
2024-05-03T19:44:30.410389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 21
23.3%
안 8
 
8.9%
주 8
 
8.9%
2 5
 
5.6%
1 5
 
5.6%
3 4
 
4.4%
용 4
 
4.4%
현 4
 
4.4%
숭 3
 
3.3%
, 3
 
3.3%
Other values (15) 25
27.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 65
72.2%
Decimal Number 22
 
24.4%
Other Punctuation 3
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 21
32.3%
안 8
 
12.3%
주 8
 
12.3%
용 4
 
6.2%
현 4
 
6.2%
숭 3
 
4.6%
학 3
 
4.6%
의 3
 
4.6%
화 2
 
3.1%
익 2
 
3.1%
Other values (6) 7
 
10.8%
Decimal Number
ValueCountFrequency (%)
2 5
22.7%
1 5
22.7%
3 4
18.2%
4 3
13.6%
5 2
 
9.1%
6 1
 
4.5%
7 1
 
4.5%
8 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 65
72.2%
Common 25
 
27.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 21
32.3%
안 8
 
12.3%
주 8
 
12.3%
용 4
 
6.2%
현 4
 
6.2%
숭 3
 
4.6%
학 3
 
4.6%
의 3
 
4.6%
화 2
 
3.1%
익 2
 
3.1%
Other values (6) 7
 
10.8%
Common
ValueCountFrequency (%)
2 5
20.0%
1 5
20.0%
3 4
16.0%
, 3
12.0%
4 3
12.0%
5 2
 
8.0%
6 1
 
4.0%
7 1
 
4.0%
8 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 65
72.2%
ASCII 25
 
27.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 21
32.3%
안 8
 
12.3%
주 8
 
12.3%
용 4
 
6.2%
현 4
 
6.2%
숭 3
 
4.6%
학 3
 
4.6%
의 3
 
4.6%
화 2
 
3.1%
익 2
 
3.1%
Other values (6) 7
 
10.8%
ASCII
ValueCountFrequency (%)
2 5
20.0%
1 5
20.0%
3 4
16.0%
, 3
12.0%
4 3
12.0%
5 2
 
8.0%
6 1
 
4.0%
7 1
 
4.0%
8 1
 
4.0%

일반수급가구수
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean725.31818
Minimum5
Maximum1171
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-05-03T19:44:30.918186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile399.9
Q1601.25
median731.5
Q3882.5
95-th percentile1030.6
Maximum1171
Range1166
Interquartile range (IQR)281.25

Descriptive statistics

Standard deviation254.71747
Coefficient of variation (CV)0.35118032
Kurtosis1.7982237
Mean725.31818
Median Absolute Deviation (MAD)147
Skewness-0.84269531
Sum15957
Variance64880.989
MonotonicityNot monotonic
2024-05-03T19:44:31.558235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
611 2
 
9.1%
707 1
 
4.5%
1171 1
 
4.5%
5 1
 
4.5%
796 1
 
4.5%
395 1
 
4.5%
735 1
 
4.5%
689 1
 
4.5%
598 1
 
4.5%
794 1
 
4.5%
Other values (11) 11
50.0%
ValueCountFrequency (%)
5 1
4.5%
395 1
4.5%
493 1
4.5%
512 1
4.5%
544 1
4.5%
598 1
4.5%
611 2
9.1%
689 1
4.5%
707 1
4.5%
728 1
4.5%
ValueCountFrequency (%)
1171 1
4.5%
1032 1
4.5%
1004 1
4.5%
981 1
4.5%
955 1
4.5%
892 1
4.5%
854 1
4.5%
850 1
4.5%
796 1
4.5%
794 1
4.5%

일반수급자수
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1004.3182
Minimum5
Maximum1690
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-05-03T19:44:32.083839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile579.95
Q1810.75
median1019
Q31243.25
95-th percentile1509.5
Maximum1690
Range1685
Interquartile range (IQR)432.5

Descriptive statistics

Standard deviation369.8506
Coefficient of variation (CV)0.36826038
Kurtosis1.3613081
Mean1004.3182
Median Absolute Deviation (MAD)235.5
Skewness-0.54700266
Sum22095
Variance136789.47
MonotonicityNot monotonic
2024-05-03T19:44:32.487933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1082 2
 
9.1%
736 1
 
4.5%
5 1
 
4.5%
1075 1
 
4.5%
575 1
 
4.5%
945 1
 
4.5%
834 1
 
4.5%
1060 1
 
4.5%
1151 1
 
4.5%
841 1
 
4.5%
Other values (11) 11
50.0%
ValueCountFrequency (%)
5 1
4.5%
575 1
4.5%
674 1
4.5%
676 1
4.5%
736 1
4.5%
803 1
4.5%
834 1
4.5%
841 1
4.5%
933 1
4.5%
945 1
4.5%
ValueCountFrequency (%)
1690 1
4.5%
1514 1
4.5%
1424 1
4.5%
1422 1
4.5%
1321 1
4.5%
1274 1
4.5%
1151 1
4.5%
1082 2
9.1%
1075 1
4.5%
1060 1
4.5%

조건부수급가구수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean104.45455
Minimum0
Maximum199
Zeros1
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-05-03T19:44:32.867850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile57
Q170.75
median86
Q3147
95-th percentile175.65
Maximum199
Range199
Interquartile range (IQR)76.25

Descriptive statistics

Standard deviation49.099246
Coefficient of variation (CV)0.4700537
Kurtosis-0.45165624
Mean104.45455
Median Absolute Deviation (MAD)29
Skewness0.11640353
Sum2298
Variance2410.7359
MonotonicityNot monotonic
2024-05-03T19:44:33.468857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
57 2
 
9.1%
68 1
 
4.5%
0 1
 
4.5%
150 1
 
4.5%
87 1
 
4.5%
73 1
 
4.5%
75 1
 
4.5%
103 1
 
4.5%
125 1
 
4.5%
82 1
 
4.5%
Other values (11) 11
50.0%
ValueCountFrequency (%)
0 1
4.5%
57 2
9.1%
65 1
4.5%
68 1
4.5%
70 1
4.5%
73 1
4.5%
75 1
4.5%
78 1
4.5%
82 1
4.5%
85 1
4.5%
ValueCountFrequency (%)
199 1
4.5%
176 1
4.5%
169 1
4.5%
153 1
4.5%
150 1
4.5%
149 1
4.5%
141 1
4.5%
136 1
4.5%
125 1
4.5%
103 1
4.5%

조건부수급자수
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean183.36364
Minimum0
Maximum337
Zeros1
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-05-03T19:44:34.032132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile92.35
Q1124.5
median160
Q3257.75
95-th percentile298.35
Maximum337
Range337
Interquartile range (IQR)133.25

Descriptive statistics

Standard deviation84.083601
Coefficient of variation (CV)0.45856203
Kurtosis-0.52928468
Mean183.36364
Median Absolute Deviation (MAD)63.5
Skewness-0.026715965
Sum4034
Variance7070.0519
MonotonicityNot monotonic
2024-05-03T19:44:34.701411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
121 1
 
4.5%
337 1
 
4.5%
0 1
 
4.5%
255 1
 
4.5%
99 1
 
4.5%
177 1
 
4.5%
130 1
 
4.5%
137 1
 
4.5%
166 1
 
4.5%
226 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
0 1
4.5%
92 1
4.5%
99 1
4.5%
120 1
4.5%
121 1
4.5%
123 1
4.5%
129 1
4.5%
130 1
4.5%
137 1
4.5%
147 1
4.5%
ValueCountFrequency (%)
337 1
4.5%
299 1
4.5%
286 1
4.5%
262 1
4.5%
259 1
4.5%
258 1
4.5%
257 1
4.5%
255 1
4.5%
226 1
4.5%
177 1
4.5%

특례수급가구수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)68.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.5
Minimum0
Maximum40
Zeros1
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-05-03T19:44:35.253713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8
Q19.25
median15
Q319.5
95-th percentile24.9
Maximum40
Range40
Interquartile range (IQR)10.25

Descriptive statistics

Standard deviation8.1459894
Coefficient of variation (CV)0.5255477
Kurtosis2.9265563
Mean15.5
Median Absolute Deviation (MAD)5
Skewness1.0494707
Sum341
Variance66.357143
MonotonicityNot monotonic
2024-05-03T19:44:35.854509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
18 3
13.6%
9 3
13.6%
12 2
 
9.1%
20 2
 
9.1%
8 2
 
9.1%
22 1
 
4.5%
25 1
 
4.5%
17 1
 
4.5%
16 1
 
4.5%
23 1
 
4.5%
Other values (5) 5
22.7%
ValueCountFrequency (%)
0 1
 
4.5%
8 2
9.1%
9 3
13.6%
10 1
 
4.5%
12 2
9.1%
13 1
 
4.5%
14 1
 
4.5%
16 1
 
4.5%
17 1
 
4.5%
18 3
13.6%
ValueCountFrequency (%)
40 1
 
4.5%
25 1
 
4.5%
23 1
 
4.5%
22 1
 
4.5%
20 2
9.1%
18 3
13.6%
17 1
 
4.5%
16 1
 
4.5%
14 1
 
4.5%
13 1
 
4.5%

특례수급자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)63.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.272727
Minimum0
Maximum51
Zeros1
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-05-03T19:44:36.464226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.1
Q113
median17.5
Q322.75
95-th percentile34.75
Maximum51
Range51
Interquartile range (IQR)9.75

Descriptive statistics

Standard deviation10.709061
Coefficient of variation (CV)0.55565881
Kurtosis2.6788708
Mean19.272727
Median Absolute Deviation (MAD)4.5
Skewness1.1644767
Sum424
Variance114.68398
MonotonicityNot monotonic
2024-05-03T19:44:36.954719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
13 4
18.2%
30 2
9.1%
22 2
9.1%
18 2
9.1%
17 2
9.1%
10 2
9.1%
15 1
 
4.5%
25 1
 
4.5%
23 1
 
4.5%
8 1
 
4.5%
Other values (4) 4
18.2%
ValueCountFrequency (%)
0 1
 
4.5%
8 1
 
4.5%
10 2
9.1%
13 4
18.2%
15 1
 
4.5%
17 2
9.1%
18 2
9.1%
21 1
 
4.5%
22 2
9.1%
23 1
 
4.5%
ValueCountFrequency (%)
51 1
4.5%
35 1
4.5%
30 2
9.1%
25 1
4.5%
23 1
4.5%
22 2
9.1%
21 1
4.5%
18 2
9.1%
17 2
9.1%
15 1
4.5%

시설수급가구수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.909091
Minimum0
Maximum421
Zeros1
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-05-03T19:44:37.494943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median8
Q323.25
95-th percentile73.4
Maximum421
Range421
Interquartile range (IQR)20.25

Descriptive statistics

Standard deviation88.408634
Coefficient of variation (CV)2.6072251
Kurtosis19.83633
Mean33.909091
Median Absolute Deviation (MAD)7
Skewness4.3742494
Sum746
Variance7816.0866
MonotonicityNot monotonic
2024-05-03T19:44:38.075994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1 3
13.6%
17 2
 
9.1%
5 2
 
9.1%
3 2
 
9.1%
7 2
 
9.1%
11 1
 
4.5%
421 1
 
4.5%
39 1
 
4.5%
75 1
 
4.5%
18 1
 
4.5%
Other values (6) 6
27.3%
ValueCountFrequency (%)
0 1
 
4.5%
1 3
13.6%
2 1
 
4.5%
3 2
9.1%
5 2
9.1%
7 2
9.1%
9 1
 
4.5%
11 1
 
4.5%
17 2
9.1%
18 1
 
4.5%
ValueCountFrequency (%)
421 1
4.5%
75 1
4.5%
43 1
4.5%
39 1
4.5%
36 1
4.5%
25 1
4.5%
18 1
4.5%
17 2
9.1%
11 1
4.5%
9 1
4.5%

시설수급자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.909091
Minimum0
Maximum421
Zeros1
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-05-03T19:44:38.669953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median8
Q323.25
95-th percentile73.4
Maximum421
Range421
Interquartile range (IQR)20.25

Descriptive statistics

Standard deviation88.408634
Coefficient of variation (CV)2.6072251
Kurtosis19.83633
Mean33.909091
Median Absolute Deviation (MAD)7
Skewness4.3742494
Sum746
Variance7816.0866
MonotonicityNot monotonic
2024-05-03T19:44:39.181643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1 3
13.6%
17 2
 
9.1%
5 2
 
9.1%
3 2
 
9.1%
7 2
 
9.1%
11 1
 
4.5%
421 1
 
4.5%
39 1
 
4.5%
75 1
 
4.5%
18 1
 
4.5%
Other values (6) 6
27.3%
ValueCountFrequency (%)
0 1
 
4.5%
1 3
13.6%
2 1
 
4.5%
3 2
9.1%
5 2
9.1%
7 2
9.1%
9 1
 
4.5%
11 1
 
4.5%
17 2
9.1%
18 1
 
4.5%
ValueCountFrequency (%)
421 1
4.5%
75 1
4.5%
43 1
4.5%
39 1
4.5%
36 1
4.5%
25 1
4.5%
18 1
4.5%
17 2
9.1%
11 1
4.5%
9 1
4.5%

Interactions

2024-05-03T19:44:25.720111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:06.715841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:09.557557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:12.059544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:15.022330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:17.816820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:20.633450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:23.391504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:25.965293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:07.015557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:09.848047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:12.382663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:15.419448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:18.166238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:20.973374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:23.657345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:26.201944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:07.346127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:10.142419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:12.730494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:15.819905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:18.565303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:21.454129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:24.013712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:26.456672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:07.644687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:10.504291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:13.070341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:16.139926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:18.918590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:21.768211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:24.354194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:26.709120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:07.959972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:10.868851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:13.493534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:16.529688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:19.220631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:22.098890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:24.663185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:27.018708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:08.601942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:11.244891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:13.932997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:16.872796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:19.713542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:22.374650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:24.989719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:27.285059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:08.922119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:11.514659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:14.311326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:17.159893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:20.036132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:22.724020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:25.281397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:27.796211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:09.188998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:11.786094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:14.646526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:17.435002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:20.335034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:23.124132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:44:25.512517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T19:44:39.523995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동명일반수급가구수일반수급자수조건부수급가구수조건부수급자수특례수급가구수특례수급자수시설수급가구수시설수급자수
동명1.0001.0001.0001.0001.0001.0001.0001.0001.000
일반수급가구수1.0001.0000.9600.7050.8100.8040.8730.8310.831
일반수급자수1.0000.9601.0000.7050.7990.8140.9310.8010.801
조건부수급가구수1.0000.7050.7051.0000.8310.5810.6740.9220.922
조건부수급자수1.0000.8100.7990.8311.0000.7810.7570.9130.913
특례수급가구수1.0000.8040.8140.5810.7811.0000.8660.8630.863
특례수급자수1.0000.8730.9310.6740.7570.8661.0000.9060.906
시설수급가구수1.0000.8310.8010.9220.9130.8630.9061.0001.000
시설수급자수1.0000.8310.8010.9220.9130.8630.9061.0001.000
2024-05-03T19:44:40.092054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일반수급가구수일반수급자수조건부수급가구수조건부수급자수특례수급가구수특례수급자수시설수급가구수시설수급자수
일반수급가구수1.0000.9910.8890.9420.7740.749-0.195-0.195
일반수급자수0.9911.0000.8720.9420.7490.724-0.199-0.199
조건부수급가구수0.8890.8721.0000.9500.6710.595-0.157-0.157
조건부수급자수0.9420.9420.9501.0000.6880.652-0.138-0.138
특례수급가구수0.7740.7490.6710.6881.0000.974-0.123-0.123
특례수급자수0.7490.7240.5950.6520.9741.000-0.084-0.084
시설수급가구수-0.195-0.199-0.157-0.138-0.123-0.0841.0001.000
시설수급자수-0.195-0.199-0.157-0.138-0.123-0.0841.0001.000

Missing values

2024-05-03T19:44:28.128453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T19:44:28.661228image/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

동명일반수급가구수일반수급자수조건부수급가구수조건부수급자수특례수급가구수특례수급자수시설수급가구수시설수급자수
0숭의2동7079336812122301717
1숭의1,3동5127365712012152525
2숭의4동8921274153299202222
3용현1,4동955132114925925304343
4용현2동72897878154182599
5용현3동5446766592171800
6용현5동10041424141262182333
7학익1동611803851479133636
8학익2동49367470123881818
9도화1동1032151413625816181111
동명일반수급가구수일반수급자수조건부수급가구수조건부수급자수특례수급가구수특례수급자수시설수급가구수시설수급자수
12주안2동11711690176337405111
13주안3동61184182129101355
14주안4동8541151125226131711
15주안5동794106010316618221717
16주안6동598834751379133939
17주안7동6899457313091077
18주안8동735108287177141733
19관교동395575579981011
20문학동7961075150255121355
21기타550000421421