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.
Author인천광역시 미추홀구
URLhttps://www.data.go.kr/data/15071349/fileData.do

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
일반수급가구수 has unique valuesUnique
일반수급자수 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 started2024-04-29 22:39:54.737985
Analysis finished2024-04-29 22:40:02.722747
Duration7.98 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
2024-04-30T07:40:02.846362image/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%
2024-04-30T07:40:03.191234image/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  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean764.09091
Minimum12
Maximum1231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-30T07:40:03.319204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile419.8
Q1653
median794.5
Q3912
95-th percentile1084.65
Maximum1231
Range1219
Interquartile range (IQR)259

Descriptive statistics

Standard deviation265.26948
Coefficient of variation (CV)0.34717005
Kurtosis1.8722505
Mean764.09091
Median Absolute Deviation (MAD)138.5
Skewness-0.87010229
Sum16810
Variance70367.896
MonotonicityNot monotonic
2024-04-30T07:40:03.447811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
738 1
 
4.5%
1231 1
 
4.5%
12 1
 
4.5%
850 1
 
4.5%
416 1
 
4.5%
791 1
 
4.5%
696 1
 
4.5%
662 1
 
4.5%
842 1
 
4.5%
900 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
12 1
4.5%
416 1
4.5%
492 1
4.5%
546 1
4.5%
578 1
4.5%
650 1
4.5%
662 1
4.5%
663 1
4.5%
696 1
4.5%
738 1
4.5%
ValueCountFrequency (%)
1231 1
4.5%
1086 1
4.5%
1059 1
4.5%
1018 1
4.5%
999 1
4.5%
916 1
4.5%
900 1
4.5%
867 1
4.5%
850 1
4.5%
842 1
4.5%

일반수급자수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1039.0909
Minimum12
Maximum1743
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-30T07:40:03.569164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile596.45
Q1853.25
median1070
Q31258.25
95-th percentile1538
Maximum1743
Range1731
Interquartile range (IQR)405

Descriptive statistics

Standard deviation376.68819
Coefficient of variation (CV)0.36251707
Kurtosis1.5188521
Mean1039.0909
Median Absolute Deviation (MAD)224
Skewness-0.60181778
Sum22860
Variance141893.99
MonotonicityNot monotonic
2024-04-30T07:40:03.707473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
988 1
 
4.5%
1743 1
 
4.5%
12 1
 
4.5%
1134 1
 
4.5%
593 1
 
4.5%
1118 1
 
4.5%
942 1
 
4.5%
925 1
 
4.5%
1075 1
 
4.5%
1187 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
12 1
4.5%
593 1
4.5%
662 1
4.5%
699 1
4.5%
767 1
4.5%
834 1
4.5%
911 1
4.5%
925 1
4.5%
942 1
4.5%
988 1
4.5%
ValueCountFrequency (%)
1743 1
4.5%
1539 1
4.5%
1519 1
4.5%
1424 1
4.5%
1327 1
4.5%
1282 1
4.5%
1187 1
4.5%
1134 1
4.5%
1118 1
4.5%
1114 1
4.5%

조건부수급가구수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.13636
Minimum0
Maximum245
Zeros1
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-30T07:40:03.856685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile67.35
Q193.75
median123
Q3173.25
95-th percentile217.1
Maximum245
Range245
Interquartile range (IQR)79.5

Descriptive statistics

Standard deviation55.403537
Coefficient of variation (CV)0.42903126
Kurtosis0.43308924
Mean129.13636
Median Absolute Deviation (MAD)36.5
Skewness-0.015737105
Sum2841
Variance3069.5519
MonotonicityNot monotonic
2024-04-30T07:40:04.000077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
175 2
 
9.1%
104 1
 
4.5%
219 1
 
4.5%
0 1
 
4.5%
86 1
 
4.5%
144 1
 
4.5%
101 1
 
4.5%
117 1
 
4.5%
129 1
 
4.5%
142 1
 
4.5%
Other values (11) 11
50.0%
ValueCountFrequency (%)
0 1
4.5%
67 1
4.5%
74 1
4.5%
86 1
4.5%
87 1
4.5%
92 1
4.5%
99 1
4.5%
101 1
4.5%
104 1
4.5%
109 1
4.5%
ValueCountFrequency (%)
245 1
4.5%
219 1
4.5%
181 1
4.5%
175 2
9.1%
174 1
4.5%
171 1
4.5%
150 1
4.5%
144 1
4.5%
142 1
4.5%
129 1
4.5%

조건부수급자수
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean229.81818
Minimum0
Maximum407
Zeros1
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-30T07:40:04.114182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile111.75
Q1167.5
median215
Q3302.75
95-th percentile349.75
Maximum407
Range407
Interquartile range (IQR)135.25

Descriptive statistics

Standard deviation99.358244
Coefficient of variation (CV)0.43233413
Kurtosis-0.24349073
Mean229.81818
Median Absolute Deviation (MAD)85.5
Skewness-0.26540492
Sum5056
Variance9872.0606
MonotonicityNot monotonic
2024-04-30T07:40:04.242382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
176 1
 
4.5%
407 1
 
4.5%
0 1
 
4.5%
299 1
 
4.5%
128 1
 
4.5%
269 1
 
4.5%
175 1
 
4.5%
198 1
 
4.5%
216 1
 
4.5%
274 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
0 1
4.5%
111 1
4.5%
126 1
4.5%
128 1
4.5%
150 1
4.5%
165 1
4.5%
175 1
4.5%
176 1
4.5%
183 1
4.5%
198 1
4.5%
ValueCountFrequency (%)
407 1
4.5%
350 1
4.5%
345 1
4.5%
339 1
4.5%
326 1
4.5%
303 1
4.5%
302 1
4.5%
299 1
4.5%
274 1
4.5%
269 1
4.5%

특례수급가구수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.863636
Minimum0
Maximum37
Zeros1
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-30T07:40:04.377870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7.05
Q111.25
median15
Q319.75
95-th percentile27.8
Maximum37
Range37
Interquartile range (IQR)8.5

Descriptive statistics

Standard deviation7.7906871
Coefficient of variation (CV)0.49110348
Kurtosis1.7637401
Mean15.863636
Median Absolute Deviation (MAD)4.5
Skewness0.68354169
Sum349
Variance60.694805
MonotonicityNot monotonic
2024-04-30T07:40:04.499891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
20 2
 
9.1%
18 2
 
9.1%
13 2
 
9.1%
15 2
 
9.1%
37 1
 
4.5%
0 1
 
4.5%
8 1
 
4.5%
10 1
 
4.5%
24 1
 
4.5%
19 1
 
4.5%
Other values (8) 8
36.4%
ValueCountFrequency (%)
0 1
4.5%
7 1
4.5%
8 1
4.5%
9 1
4.5%
10 1
4.5%
11 1
4.5%
12 1
4.5%
13 2
9.1%
14 1
4.5%
15 2
9.1%
ValueCountFrequency (%)
37 1
4.5%
28 1
4.5%
24 1
4.5%
21 1
4.5%
20 2
9.1%
19 1
4.5%
18 2
9.1%
17 1
4.5%
15 2
9.1%
14 1
4.5%

특례수급자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19
Minimum0
Maximum43
Zeros1
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-30T07:40:04.623893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7.15
Q113.25
median19
Q324.5
95-th percentile31.85
Maximum43
Range43
Interquartile range (IQR)11.25

Descriptive statistics

Standard deviation9.3655905
Coefficient of variation (CV)0.49292582
Kurtosis1.0514676
Mean19
Median Absolute Deviation (MAD)6
Skewness0.49964589
Sum418
Variance87.714286
MonotonicityNot monotonic
2024-04-30T07:40:04.736793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
25 2
 
9.1%
20 2
 
9.1%
16 2
 
9.1%
19 2
 
9.1%
29 2
 
9.1%
14 2
 
9.1%
11 1
 
4.5%
7 1
 
4.5%
32 1
 
4.5%
43 1
 
4.5%
Other values (6) 6
27.3%
ValueCountFrequency (%)
0 1
4.5%
7 1
4.5%
10 1
4.5%
11 1
4.5%
12 1
4.5%
13 1
4.5%
14 2
9.1%
16 2
9.1%
19 2
9.1%
20 2
9.1%
ValueCountFrequency (%)
43 1
4.5%
32 1
4.5%
29 2
9.1%
25 2
9.1%
23 1
4.5%
21 1
4.5%
20 2
9.1%
19 2
9.1%
16 2
9.1%
14 2
9.1%

시설수급가구수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.318182
Minimum0
Maximum541
Zeros1
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-30T07:40:04.843063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median8
Q320.75
95-th percentile67.4
Maximum541
Range541
Interquartile range (IQR)17.75

Descriptive statistics

Standard deviation113.47095
Coefficient of variation (CV)2.9612821
Kurtosis20.948044
Mean38.318182
Median Absolute Deviation (MAD)7
Skewness4.5351592
Sum843
Variance12875.656
MonotonicityNot monotonic
2024-04-30T07:40:04.986236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
3 3
13.6%
6 2
 
9.1%
1 2
 
9.1%
4 2
 
9.1%
14 1
 
4.5%
69 1
 
4.5%
541 1
 
4.5%
2 1
 
4.5%
30 1
 
4.5%
21 1
 
4.5%
Other values (7) 7
31.8%
ValueCountFrequency (%)
0 1
 
4.5%
1 2
9.1%
2 1
 
4.5%
3 3
13.6%
4 2
9.1%
6 2
9.1%
10 1
 
4.5%
14 1
 
4.5%
16 1
 
4.5%
19 1
 
4.5%
ValueCountFrequency (%)
541 1
4.5%
69 1
4.5%
37 1
4.5%
33 1
4.5%
30 1
4.5%
21 1
4.5%
20 1
4.5%
19 1
4.5%
16 1
4.5%
14 1
4.5%

시설수급자수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.318182
Minimum0
Maximum541
Zeros1
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-30T07:40:05.121318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median8
Q320.75
95-th percentile67.4
Maximum541
Range541
Interquartile range (IQR)17.75

Descriptive statistics

Standard deviation113.47095
Coefficient of variation (CV)2.9612821
Kurtosis20.948044
Mean38.318182
Median Absolute Deviation (MAD)7
Skewness4.5351592
Sum843
Variance12875.656
MonotonicityNot monotonic
2024-04-30T07:40:05.244695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
3 3
13.6%
6 2
 
9.1%
1 2
 
9.1%
4 2
 
9.1%
14 1
 
4.5%
69 1
 
4.5%
541 1
 
4.5%
2 1
 
4.5%
30 1
 
4.5%
21 1
 
4.5%
Other values (7) 7
31.8%
ValueCountFrequency (%)
0 1
 
4.5%
1 2
9.1%
2 1
 
4.5%
3 3
13.6%
4 2
9.1%
6 2
9.1%
10 1
 
4.5%
14 1
 
4.5%
16 1
 
4.5%
19 1
 
4.5%
ValueCountFrequency (%)
541 1
4.5%
69 1
4.5%
37 1
4.5%
33 1
4.5%
30 1
4.5%
21 1
4.5%
20 1
4.5%
19 1
4.5%
16 1
4.5%
14 1
4.5%

Interactions

2024-04-30T07:40:01.662899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:56.668273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:57.379221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:58.060722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:58.742259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:59.439203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:00.126771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:01.009634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:01.739033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:56.801385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:57.462280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:58.136226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:58.845212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:59.526302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:00.210612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:01.086359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:01.819248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:56.886557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:57.551419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:58.217379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:58.951929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:59.606466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:00.289247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:01.169701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:01.922609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:56.963803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:57.631874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:58.293574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:59.034554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:59.682602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:00.363731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:01.244082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:02.049619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:57.054326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:57.734729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:58.386002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:59.119815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:59.767881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:00.656978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:01.340949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:02.176351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:57.138126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:57.829187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:58.471555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:59.203744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:59.853558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:00.731413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:01.441669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:02.296932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:57.212509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:57.904670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:58.548033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:59.277884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:59.931497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:00.817356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:01.514225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:02.397319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:57.296786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:57.984101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:58.636505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:59.362455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:00.021856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:00.916609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:40:01.591386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T07:40:05.341013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동명일반수급가구수일반수급자수조건부수급가구수조건부수급자수특례수급가구수특례수급자수시설수급가구수시설수급자수
동명1.0001.0001.0001.0001.0001.0001.0001.0001.000
일반수급가구수1.0001.0000.9760.8700.8890.7730.7250.7480.748
일반수급자수1.0000.9761.0000.8560.8360.6100.7070.7820.782
조건부수급가구수1.0000.8700.8561.0000.9340.9510.9000.8870.887
조건부수급자수1.0000.8890.8360.9341.0000.8490.8530.8870.887
특례수급가구수1.0000.7730.6100.9510.8491.0000.9830.8870.887
특례수급자수1.0000.7250.7070.9000.8530.9831.0001.0001.000
시설수급가구수1.0000.7480.7820.8870.8870.8871.0001.0001.000
시설수급자수1.0000.7480.7820.8870.8870.8871.0001.0001.000
2024-04-30T07:40:05.453523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일반수급가구수일반수급자수조건부수급가구수조건부수급자수특례수급가구수특례수급자수시설수급가구수시설수급자수
일반수급가구수1.0000.9880.9000.9290.7250.729-0.144-0.144
일반수급자수0.9881.0000.9000.9240.7020.701-0.124-0.124
조건부수급가구수0.9000.9001.0000.9660.7760.747-0.065-0.065
조건부수급자수0.9290.9240.9661.0000.7340.710-0.095-0.095
특례수급가구수0.7250.7020.7760.7341.0000.972-0.150-0.150
특례수급자수0.7290.7010.7470.7100.9721.000-0.092-0.092
시설수급가구수-0.144-0.124-0.065-0.095-0.150-0.0921.0001.000
시설수급자수-0.144-0.124-0.065-0.095-0.150-0.0921.0001.000

Missing values

2024-04-30T07:40:02.527666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:40:02.671564image/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
0숭의2동73898810417620251414
1숭의1.3동5467678716515192020
2숭의4동9161282174345181966
3용현1.4동999132717530220253737
4용현2동798106510921414211010
5용현3동57869974111131400
6용현5동10861519171339172033
7학익1동650834991839113333
8학익2동49266267126771919
9도화1동1059153915030312141616
동명일반수급가구수일반수급자수조건부수급가구수조건부수급자수특례수급가구수특례수급자수시설수급가구수시설수급자수
12주안2동12311743219407374311
13주안3동66391192150111233
14주안4동9001187142274192311
15주안5동842107512921624292121
16주안6동66292511719810133030
17주안7동696942101175131644
18주안8동7911118144269182033
19관교동4165938612881022
20문학동8501134175299151666
21기타12120000541541