Overview

Dataset statistics

Number of variables5
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 KiB
Average record size in memory50.3 B

Variable types

Text1
Numeric4

Dataset

Description인천광역시 미추홀구 의료급여 수급자에 대한 데이터로 미추홀구의 동별 1종 가구수, 1종 수급자수, 2종 가구수, 2종 수급자수 등을 제공합니다.
Author인천광역시 미추홀구
URLhttps://www.data.go.kr/data/15071330/fileData.do

Alerts

(1종)가구수 is highly overall correlated with (1종)수급권자수 and 2 other fieldsHigh correlation
(1종)수급권자수 is highly overall correlated with (1종)가구수 and 2 other fieldsHigh correlation
(2종)가구수 is highly overall correlated with (1종)가구수 and 2 other fieldsHigh correlation
(2종)수급권자수 is highly overall correlated with (1종)가구수 and 2 other fieldsHigh correlation
동명 has unique valuesUnique
(1종)가구수 has unique valuesUnique
(2종)수급권자수 has unique valuesUnique

Reproduction

Analysis started2024-04-29 22:39:29.107315
Analysis finished2024-04-29 22:39:32.518770
Duration3.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

동명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-04-30T07:39:32.644996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.1904762
Min length3

Characters and Unicode

Total characters88
Distinct characters23
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

Unique21 ?
Unique (%)100.0%

Sample

1st row숭의2동
2nd row숭의1.3동
3rd row숭의4동
4th row용현1.4동
5th row용현2동
ValueCountFrequency (%)
숭의2동 1
 
4.8%
주안1동 1
 
4.8%
관교동 1
 
4.8%
주안8동 1
 
4.8%
주안7동 1
 
4.8%
주안6동 1
 
4.8%
주안5동 1
 
4.8%
주안4동 1
 
4.8%
주안3동 1
 
4.8%
주안2동 1
 
4.8%
Other values (11) 11
52.4%
2024-04-30T07:39:32.995904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
23.9%
8
 
9.1%
8
 
9.1%
2 5
 
5.7%
1 5
 
5.7%
3 4
 
4.5%
4
 
4.5%
4
 
4.5%
3
 
3.4%
3
 
3.4%
Other values (13) 23
26.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63
71.6%
Decimal Number 22
 
25.0%
Other Punctuation 3
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
21
33.3%
8
 
12.7%
8
 
12.7%
4
 
6.3%
4
 
6.3%
3
 
4.8%
3
 
4.8%
3
 
4.8%
2
 
3.2%
2
 
3.2%
Other values (4) 5
 
7.9%
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 63
71.6%
Common 25
 
28.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
21
33.3%
8
 
12.7%
8
 
12.7%
4
 
6.3%
4
 
6.3%
3
 
4.8%
3
 
4.8%
3
 
4.8%
2
 
3.2%
2
 
3.2%
Other values (4) 5
 
7.9%
Common
ValueCountFrequency (%)
2 5
20.0%
1 5
20.0%
3 4
16.0%
4 3
12.0%
. 3
12.0%
5 2
 
8.0%
6 1
 
4.0%
7 1
 
4.0%
8 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63
71.6%
ASCII 25
 
28.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
21
33.3%
8
 
12.7%
8
 
12.7%
4
 
6.3%
4
 
6.3%
3
 
4.8%
3
 
4.8%
3
 
4.8%
2
 
3.2%
2
 
3.2%
Other values (4) 5
 
7.9%
ASCII
ValueCountFrequency (%)
2 5
20.0%
1 5
20.0%
3 4
16.0%
4 3
12.0%
. 3
12.0%
5 2
 
8.0%
6 1
 
4.0%
7 1
 
4.0%
8 1
 
4.0%

(1종)가구수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean534.33333
Minimum228
Maximum768
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-04-30T07:39:33.108329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum228
5-th percentile359
Q1431
median508
Q3640
95-th percentile748
Maximum768
Range540
Interquartile range (IQR)209

Descriptive statistics

Standard deviation143.09519
Coefficient of variation (CV)0.26780135
Kurtosis-0.48156761
Mean534.33333
Median Absolute Deviation (MAD)92
Skewness-0.0085843602
Sum11221
Variance20476.233
MonotonicityNot monotonic
2024-04-30T07:39:33.211870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
525 1
 
4.8%
392 1
 
4.8%
492 1
 
4.8%
228 1
 
4.8%
458 1
 
4.8%
425 1
 
4.8%
485 1
 
4.8%
509 1
 
4.8%
640 1
 
4.8%
428 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
228 1
4.8%
359 1
4.8%
392 1
4.8%
425 1
4.8%
428 1
4.8%
431 1
4.8%
458 1
4.8%
476 1
4.8%
485 1
4.8%
492 1
4.8%
ValueCountFrequency (%)
768 1
4.8%
748 1
4.8%
724 1
4.8%
710 1
4.8%
696 1
4.8%
640 1
4.8%
619 1
4.8%
600 1
4.8%
525 1
4.8%
509 1
4.8%

(1종)수급권자수
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean614.09524
Minimum262
Maximum903
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-04-30T07:39:33.311241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum262
5-th percentile415
Q1502
median573
Q3738
95-th percentile885
Maximum903
Range641
Interquartile range (IQR)236

Descriptive statistics

Standard deviation173.43786
Coefficient of variation (CV)0.28242827
Kurtosis-0.61607492
Mean614.09524
Median Absolute Deviation (MAD)103
Skewness0.16471429
Sum12896
Variance30080.69
MonotonicityNot monotonic
2024-04-30T07:39:33.408401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
525 2
 
9.5%
601 1
 
4.8%
655 1
 
4.8%
540 1
 
4.8%
262 1
 
4.8%
502 1
 
4.8%
549 1
 
4.8%
579 1
 
4.8%
736 1
 
4.8%
491 1
 
4.8%
Other values (10) 10
47.6%
ValueCountFrequency (%)
262 1
4.8%
415 1
4.8%
449 1
4.8%
470 1
4.8%
491 1
4.8%
502 1
4.8%
525 2
9.5%
540 1
4.8%
549 1
4.8%
573 1
4.8%
ValueCountFrequency (%)
903 1
4.8%
885 1
4.8%
850 1
4.8%
847 1
4.8%
801 1
4.8%
738 1
4.8%
736 1
4.8%
655 1
4.8%
601 1
4.8%
579 1
4.8%

(2종)가구수
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean156.19048
Minimum81
Maximum248
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-04-30T07:39:33.515779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum81
5-th percentile87
Q1118
median161
Q3187
95-th percentile234
Maximum248
Range167
Interquartile range (IQR)69

Descriptive statistics

Standard deviation49.988618
Coefficient of variation (CV)0.32004908
Kurtosis-0.98965038
Mean156.19048
Median Absolute Deviation (MAD)42
Skewness0.26549724
Sum3280
Variance2498.8619
MonotonicityNot monotonic
2024-04-30T07:39:33.620302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
123 2
 
9.5%
101 1
 
4.8%
248 1
 
4.8%
203 1
 
4.8%
102 1
 
4.8%
163 1
 
4.8%
134 1
 
4.8%
145 1
 
4.8%
161 1
 
4.8%
165 1
 
4.8%
Other values (10) 10
47.6%
ValueCountFrequency (%)
81 1
4.8%
87 1
4.8%
101 1
4.8%
102 1
4.8%
108 1
4.8%
118 1
4.8%
123 2
9.5%
134 1
4.8%
145 1
4.8%
161 1
4.8%
ValueCountFrequency (%)
248 1
4.8%
234 1
4.8%
229 1
4.8%
209 1
4.8%
203 1
4.8%
187 1
4.8%
181 1
4.8%
178 1
4.8%
165 1
4.8%
163 1
4.8%

(2종)수급권자수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean242.04762
Minimum124
Maximum379
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-04-30T07:39:33.739460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum124
5-th percentile130
Q1175
median236
Q3310
95-th percentile371
Maximum379
Range255
Interquartile range (IQR)135

Descriptive statistics

Standard deviation80.436606
Coefficient of variation (CV)0.33231728
Kurtosis-1.243682
Mean242.04762
Median Absolute Deviation (MAD)74
Skewness0.089760428
Sum5083
Variance6470.0476
MonotonicityNot monotonic
2024-04-30T07:39:33.845004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
142 1
 
4.8%
162 1
 
4.8%
300 1
 
4.8%
146 1
 
4.8%
280 1
 
4.8%
196 1
 
4.8%
229 1
 
4.8%
236 1
 
4.8%
265 1
 
4.8%
197 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
124 1
4.8%
130 1
4.8%
142 1
4.8%
146 1
4.8%
162 1
4.8%
175 1
4.8%
194 1
4.8%
196 1
4.8%
197 1
4.8%
229 1
4.8%
ValueCountFrequency (%)
379 1
4.8%
371 1
4.8%
329 1
4.8%
321 1
4.8%
316 1
4.8%
310 1
4.8%
300 1
4.8%
281 1
4.8%
280 1
4.8%
265 1
4.8%

Interactions

2024-04-30T07:39:31.994581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:30.962034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:31.326683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:31.672794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:32.070376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:31.090843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:31.406027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:31.753115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:32.172955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:31.169230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:31.500960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:31.842456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:32.259410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:31.253156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:31.590792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:39:31.922565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T07:39:33.927015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동명(1종)가구수(1종)수급권자수(2종)가구수(2종)수급권자수
동명1.0001.0001.0001.0001.000
(1종)가구수1.0001.0000.9750.0000.554
(1종)수급권자수1.0000.9751.0000.7160.627
(2종)가구수1.0000.0000.7161.0000.712
(2종)수급권자수1.0000.5540.6270.7121.000
2024-04-30T07:39:34.034092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
(1종)가구수(1종)수급권자수(2종)가구수(2종)수급권자수
(1종)가구수1.0000.9910.7610.779
(1종)수급권자수0.9911.0000.7720.802
(2종)가구수0.7610.7721.0000.963
(2종)수급권자수0.7790.8020.9631.000

Missing values

2024-04-30T07:39:32.365007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:39:32.469937image/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

동명(1종)가구수(1종)수급권자수(2종)가구수(2종)수급권자수
0숭의2동525601101142
1숭의1.3동392449108162
2숭의4동619738187329
3용현1.4동724847209310
4용현2동508573118194
5용현3동43147087124
6용현5동696801229379
7학익1동476525123175
8학익2동35941581130
9도화1동748885181321
동명(1종)가구수(1종)수급권자수(2종)가구수(2종)수급권자수
11주안1동600655248316
12주안2동768903234371
13주안3동428491123197
14주안4동640736165265
15주안5동509579161236
16주안6동485549145229
17주안7동425502134196
18주안8동458525163280
19관교동228262102146
20문학동492540203300