Overview

Dataset statistics

Number of variables18
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory164.7 B

Variable types

Text1
Numeric15
Categorical1
DateTime1

Dataset

Description대구광역시 달서구 내 장애인 등록 현황에 대한 내용 및 정보가 담겨있음. (동명, 지체, 시각, 청각, 언어, 지적, 뇌병변, 자폐성, 정신, 신장, 심장, 호흡기, 간, 안면, 장루_요루, 뇌전증)
URLhttps://www.data.go.kr/data/3075309/fileData.do

Alerts

관리부서 has constant value ""Constant
기준일자 has constant value ""Constant
지체 is highly overall correlated with 시각 and 8 other fieldsHigh correlation
시각 is highly overall correlated with 지체 and 10 other fieldsHigh correlation
청각 is highly overall correlated with 지체 and 8 other fieldsHigh correlation
언어 is highly overall correlated with 지체 and 6 other fieldsHigh correlation
지적 is highly overall correlated with 지체 and 8 other fieldsHigh correlation
뇌병변 is highly overall correlated with 지체 and 8 other fieldsHigh correlation
정신 is highly overall correlated with 지체 and 7 other fieldsHigh correlation
신장 is highly overall correlated with 지체 and 8 other fieldsHigh correlation
호흡기 is highly overall correlated with 지체 and 7 other fieldsHigh correlation
안면 is highly overall correlated with 시각High correlation
장루_요루 is highly overall correlated with 지체 and 8 other fieldsHigh correlation
뇌전증 is highly overall correlated with 시각 and 2 other fieldsHigh correlation
동명 has unique valuesUnique
지체 has unique valuesUnique
심장 has 5 (21.7%) zerosZeros
안면 has 10 (43.5%) zerosZeros
뇌전증 has 2 (8.7%) zerosZeros

Reproduction

Analysis started2023-12-12 10:41:46.842270
Analysis finished2023-12-12 10:42:15.332475
Duration28.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

동명
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-12T19:42:15.470023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.6086957
Min length2

Characters and Unicode

Total characters83
Distinct characters32
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

Unique23 ?
Unique (%)100.0%

Sample

1st row성당동
2nd row두류1.2동
3rd row두류3동
4th row본리동
5th row감삼동
ValueCountFrequency (%)
성당동 1
 
4.3%
월성1동 1
 
4.3%
송현2동 1
 
4.3%
송현1동 1
 
4.3%
도원동 1
 
4.3%
상인3동 1
 
4.3%
상인2동 1
 
4.3%
상인1동 1
 
4.3%
유천동 1
 
4.3%
진천동 1
 
4.3%
Other values (13) 13
56.5%
2023-12-12T19:42:15.835512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23
27.7%
1 6
 
7.2%
2 6
 
7.2%
3
 
3.6%
3
 
3.6%
3
 
3.6%
2
 
2.4%
2
 
2.4%
2
 
2.4%
2
 
2.4%
Other values (22) 31
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68
81.9%
Decimal Number 14
 
16.9%
Other Punctuation 1
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
23
33.8%
3
 
4.4%
3
 
4.4%
3
 
4.4%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
Other values (18) 24
35.3%
Decimal Number
ValueCountFrequency (%)
1 6
42.9%
2 6
42.9%
3 2
 
14.3%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68
81.9%
Common 15
 
18.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
23
33.8%
3
 
4.4%
3
 
4.4%
3
 
4.4%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
Other values (18) 24
35.3%
Common
ValueCountFrequency (%)
1 6
40.0%
2 6
40.0%
3 2
 
13.3%
. 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68
81.9%
ASCII 15
 
18.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
23
33.8%
3
 
4.4%
3
 
4.4%
3
 
4.4%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
2
 
2.9%
Other values (18) 24
35.3%
ASCII
ValueCountFrequency (%)
1 6
40.0%
2 6
40.0%
3 2
 
13.3%
. 1
 
6.7%

지체
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean477.6087
Minimum184
Maximum885
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:42:16.312690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184
5-th percentile272.1
Q1331.5
median457
Q3563
95-th percentile844.6
Maximum885
Range701
Interquartile range (IQR)231.5

Descriptive statistics

Standard deviation193.72725
Coefficient of variation (CV)0.40561919
Kurtosis-0.084583543
Mean477.6087
Median Absolute Deviation (MAD)133
Skewness0.78207926
Sum10985
Variance37530.249
MonotonicityNot monotonic
2023-12-12T19:42:16.469835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
536 1
 
4.3%
396 1
 
4.3%
306 1
 
4.3%
590 1
 
4.3%
511 1
 
4.3%
672 1
 
4.3%
629 1
 
4.3%
354 1
 
4.3%
457 1
 
4.3%
272 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
184 1
4.3%
272 1
4.3%
273 1
4.3%
305 1
4.3%
306 1
4.3%
309 1
4.3%
354 1
4.3%
359 1
4.3%
376 1
4.3%
386 1
4.3%
ValueCountFrequency (%)
885 1
4.3%
845 1
4.3%
841 1
4.3%
672 1
4.3%
629 1
4.3%
590 1
4.3%
536 1
4.3%
511 1
4.3%
507 1
4.3%
503 1
4.3%

시각
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean118.91304
Minimum39
Maximum229
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:42:16.661357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum39
5-th percentile69.4
Q180.5
median108
Q3135.5
95-th percentile221.7
Maximum229
Range190
Interquartile range (IQR)55

Descriptive statistics

Standard deviation48.761864
Coefficient of variation (CV)0.41006321
Kurtosis0.57300027
Mean118.91304
Median Absolute Deviation (MAD)31
Skewness0.91708766
Sum2735
Variance2377.7194
MonotonicityNot monotonic
2023-12-12T19:42:16.829904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
127 2
 
8.7%
77 2
 
8.7%
124 1
 
4.3%
100 1
 
4.3%
69 1
 
4.3%
149 1
 
4.3%
161 1
 
4.3%
140 1
 
4.3%
229 1
 
4.3%
201 1
 
4.3%
Other values (11) 11
47.8%
ValueCountFrequency (%)
39 1
4.3%
69 1
4.3%
73 1
4.3%
76 1
4.3%
77 2
8.7%
84 1
4.3%
96 1
4.3%
100 1
4.3%
104 1
4.3%
106 1
4.3%
ValueCountFrequency (%)
229 1
4.3%
224 1
4.3%
201 1
4.3%
161 1
4.3%
149 1
4.3%
140 1
4.3%
131 1
4.3%
127 2
8.7%
124 1
4.3%
113 1
4.3%

청각
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean257
Minimum108
Maximum511
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:42:17.010103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum108
5-th percentile127
Q1169
median237
Q3323.5
95-th percentile415.9
Maximum511
Range403
Interquartile range (IQR)154.5

Descriptive statistics

Standard deviation106.61912
Coefficient of variation (CV)0.41486038
Kurtosis-0.2307753
Mean257
Median Absolute Deviation (MAD)71
Skewness0.69148684
Sum5911
Variance11367.636
MonotonicityNot monotonic
2023-12-12T19:42:17.157249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
379 2
 
8.7%
237 2
 
8.7%
169 2
 
8.7%
418 1
 
4.3%
319 1
 
4.3%
292 1
 
4.3%
397 1
 
4.3%
213 1
 
4.3%
328 1
 
4.3%
108 1
 
4.3%
Other values (10) 10
43.5%
ValueCountFrequency (%)
108 1
4.3%
125 1
4.3%
145 1
4.3%
165 1
4.3%
166 1
4.3%
169 2
8.7%
180 1
4.3%
191 1
4.3%
213 1
4.3%
222 1
4.3%
ValueCountFrequency (%)
511 1
4.3%
418 1
4.3%
397 1
4.3%
379 2
8.7%
328 1
4.3%
319 1
4.3%
295 1
4.3%
292 1
4.3%
266 1
4.3%
237 2
8.7%

언어
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.434783
Minimum2
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:42:17.319631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q15
median11
Q312.5
95-th percentile19.6
Maximum28
Range26
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation6.0289158
Coefficient of variation (CV)0.5777711
Kurtosis1.9805576
Mean10.434783
Median Absolute Deviation (MAD)4
Skewness1.0393633
Sum240
Variance36.347826
MonotonicityNot monotonic
2023-12-12T19:42:17.454473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
11 5
21.7%
5 4
17.4%
12 2
 
8.7%
3 2
 
8.7%
15 2
 
8.7%
2 1
 
4.3%
10 1
 
4.3%
13 1
 
4.3%
28 1
 
4.3%
16 1
 
4.3%
Other values (3) 3
13.0%
ValueCountFrequency (%)
2 1
 
4.3%
3 2
 
8.7%
5 4
17.4%
7 1
 
4.3%
9 1
 
4.3%
10 1
 
4.3%
11 5
21.7%
12 2
 
8.7%
13 1
 
4.3%
15 2
 
8.7%
ValueCountFrequency (%)
28 1
 
4.3%
20 1
 
4.3%
16 1
 
4.3%
15 2
 
8.7%
13 1
 
4.3%
12 2
 
8.7%
11 5
21.7%
10 1
 
4.3%
9 1
 
4.3%
7 1
 
4.3%

지적
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean102.47826
Minimum37
Maximum241
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:42:17.602985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37
5-th percentile48.2
Q171.5
median93
Q3119.5
95-th percentile178.5
Maximum241
Range204
Interquartile range (IQR)48

Descriptive statistics

Standard deviation47.778723
Coefficient of variation (CV)0.46623276
Kurtosis1.9071717
Mean102.47826
Median Absolute Deviation (MAD)24
Skewness1.277634
Sum2357
Variance2282.8063
MonotonicityNot monotonic
2023-12-12T19:42:17.751810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
101 2
 
8.7%
77 2
 
8.7%
105 1
 
4.3%
165 1
 
4.3%
61 1
 
4.3%
108 1
 
4.3%
127 1
 
4.3%
154 1
 
4.3%
74 1
 
4.3%
47 1
 
4.3%
Other values (11) 11
47.8%
ValueCountFrequency (%)
37 1
4.3%
47 1
4.3%
59 1
4.3%
61 1
4.3%
66 1
4.3%
69 1
4.3%
74 1
4.3%
77 2
8.7%
78 1
4.3%
87 1
4.3%
ValueCountFrequency (%)
241 1
4.3%
180 1
4.3%
165 1
4.3%
154 1
4.3%
138 1
4.3%
127 1
4.3%
112 1
4.3%
108 1
4.3%
105 1
4.3%
101 2
8.7%

뇌병변
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean117.3913
Minimum54
Maximum246
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:42:17.921876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54
5-th percentile55.3
Q182
median100
Q3141
95-th percentile224.3
Maximum246
Range192
Interquartile range (IQR)59

Descriptive statistics

Standard deviation55.411468
Coefficient of variation (CV)0.47202362
Kurtosis0.28278094
Mean117.3913
Median Absolute Deviation (MAD)30
Skewness1.0496791
Sum2700
Variance3070.4308
MonotonicityNot monotonic
2023-12-12T19:42:18.060796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
82 2
 
8.7%
109 2
 
8.7%
129 1
 
4.3%
218 1
 
4.3%
58 1
 
4.3%
174 1
 
4.3%
100 1
 
4.3%
151 1
 
4.3%
166 1
 
4.3%
98 1
 
4.3%
Other values (11) 11
47.8%
ValueCountFrequency (%)
54 1
4.3%
55 1
4.3%
58 1
4.3%
63 1
4.3%
70 1
4.3%
82 2
8.7%
83 1
4.3%
93 1
4.3%
96 1
4.3%
98 1
4.3%
ValueCountFrequency (%)
246 1
4.3%
225 1
4.3%
218 1
4.3%
174 1
4.3%
166 1
4.3%
151 1
4.3%
131 1
4.3%
129 1
4.3%
109 2
8.7%
108 1
4.3%

자폐성
Real number (ℝ)

Distinct16
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.217391
Minimum3
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:42:18.196661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile6
Q18
median14
Q320.5
95-th percentile28.5
Maximum36
Range33
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation8.5064495
Coefficient of variation (CV)0.55899526
Kurtosis-0.11172865
Mean15.217391
Median Absolute Deviation (MAD)6
Skewness0.6307471
Sum350
Variance72.359684
MonotonicityNot monotonic
2023-12-12T19:42:18.347252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
19 3
13.0%
9 2
 
8.7%
6 2
 
8.7%
8 2
 
8.7%
7 2
 
8.7%
23 2
 
8.7%
13 1
 
4.3%
36 1
 
4.3%
10 1
 
4.3%
24 1
 
4.3%
Other values (6) 6
26.1%
ValueCountFrequency (%)
3 1
 
4.3%
6 2
8.7%
7 2
8.7%
8 2
8.7%
9 2
8.7%
10 1
 
4.3%
13 1
 
4.3%
14 1
 
4.3%
17 1
 
4.3%
19 3
13.0%
ValueCountFrequency (%)
36 1
 
4.3%
29 1
 
4.3%
24 1
 
4.3%
23 2
8.7%
21 1
 
4.3%
20 1
 
4.3%
19 3
13.0%
17 1
 
4.3%
14 1
 
4.3%
13 1
 
4.3%

정신
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60
Minimum12
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:42:18.495958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile20
Q127.5
median38
Q358.5
95-th percentile192.7
Maximum200
Range188
Interquartile range (IQR)31

Descriptive statistics

Standard deviation55.295898
Coefficient of variation (CV)0.9215983
Kurtosis2.0316823
Mean60
Median Absolute Deviation (MAD)14
Skewness1.7646272
Sum1380
Variance3057.6364
MonotonicityNot monotonic
2023-12-12T19:42:18.665846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
56 2
 
8.7%
24 2
 
8.7%
31 2
 
8.7%
20 2
 
8.7%
38 2
 
8.7%
12 1
 
4.3%
46 1
 
4.3%
131 1
 
4.3%
61 1
 
4.3%
41 1
 
4.3%
Other values (8) 8
34.8%
ValueCountFrequency (%)
12 1
4.3%
20 2
8.7%
24 2
8.7%
26 1
4.3%
29 1
4.3%
31 2
8.7%
32 1
4.3%
37 1
4.3%
38 2
8.7%
41 1
4.3%
ValueCountFrequency (%)
200 1
4.3%
197 1
4.3%
154 1
4.3%
131 1
4.3%
76 1
4.3%
61 1
4.3%
56 2
8.7%
46 1
4.3%
41 1
4.3%
38 2
8.7%

신장
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.869565
Minimum24
Maximum114
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:42:18.859674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24
5-th percentile31.3
Q137
median39
Q364.5
95-th percentile104
Maximum114
Range90
Interquartile range (IQR)27.5

Descriptive statistics

Standard deviation24.049767
Coefficient of variation (CV)0.45488869
Kurtosis1.0531263
Mean52.869565
Median Absolute Deviation (MAD)10
Skewness1.2809716
Sum1216
Variance578.3913
MonotonicityNot monotonic
2023-12-12T19:42:19.010841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
37 3
 
13.0%
38 3
 
13.0%
34 2
 
8.7%
55 1
 
4.3%
78 1
 
4.3%
64 1
 
4.3%
54 1
 
4.3%
86 1
 
4.3%
66 1
 
4.3%
65 1
 
4.3%
Other values (8) 8
34.8%
ValueCountFrequency (%)
24 1
 
4.3%
31 1
 
4.3%
34 2
8.7%
35 1
 
4.3%
37 3
13.0%
38 3
13.0%
39 1
 
4.3%
49 1
 
4.3%
54 1
 
4.3%
55 1
 
4.3%
ValueCountFrequency (%)
114 1
4.3%
106 1
4.3%
86 1
4.3%
78 1
4.3%
66 1
4.3%
65 1
4.3%
64 1
4.3%
57 1
4.3%
55 1
4.3%
54 1
4.3%

심장
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)30.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1304348
Minimum0
Maximum6
Zeros5
Zeros (%)21.7%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:42:19.140336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4.9
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.6598014
Coefficient of variation (CV)0.77909046
Kurtosis-0.094499396
Mean2.1304348
Median Absolute Deviation (MAD)1
Skewness0.49245687
Sum49
Variance2.7549407
MonotonicityNot monotonic
2023-12-12T19:42:19.285771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 6
26.1%
3 5
21.7%
0 5
21.7%
1 3
13.0%
4 2
 
8.7%
6 1
 
4.3%
5 1
 
4.3%
ValueCountFrequency (%)
0 5
21.7%
1 3
13.0%
2 6
26.1%
3 5
21.7%
4 2
 
8.7%
5 1
 
4.3%
6 1
 
4.3%
ValueCountFrequency (%)
6 1
 
4.3%
5 1
 
4.3%
4 2
 
8.7%
3 5
21.7%
2 6
26.1%
1 3
13.0%
0 5
21.7%

호흡기
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9130435
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:42:19.432024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12.5
median3
Q35.5
95-th percentile8
Maximum8
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.3915199
Coefficient of variation (CV)0.61116621
Kurtosis-0.87004518
Mean3.9130435
Median Absolute Deviation (MAD)2
Skewness0.50533144
Sum90
Variance5.7193676
MonotonicityNot monotonic
2023-12-12T19:42:19.580456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3 6
26.1%
1 5
21.7%
4 4
17.4%
8 3
13.0%
7 2
 
8.7%
2 1
 
4.3%
5 1
 
4.3%
6 1
 
4.3%
ValueCountFrequency (%)
1 5
21.7%
2 1
 
4.3%
3 6
26.1%
4 4
17.4%
5 1
 
4.3%
6 1
 
4.3%
7 2
 
8.7%
8 3
13.0%
ValueCountFrequency (%)
8 3
13.0%
7 2
 
8.7%
6 1
 
4.3%
5 1
 
4.3%
4 4
17.4%
3 6
26.1%
2 1
 
4.3%
1 5
21.7%


Real number (ℝ)

Distinct8
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.8695652
Minimum5
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:42:19.726236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5
Q16
median8
Q39.5
95-th percentile11
Maximum12
Range7
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation2.1805827
Coefficient of variation (CV)0.27709061
Kurtosis-1.1497463
Mean7.8695652
Median Absolute Deviation (MAD)2
Skewness0.21118914
Sum181
Variance4.7549407
MonotonicityNot monotonic
2023-12-12T19:42:19.948831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
9 4
17.4%
5 4
17.4%
6 4
17.4%
10 3
13.0%
7 3
13.0%
11 2
8.7%
8 2
8.7%
12 1
 
4.3%
ValueCountFrequency (%)
5 4
17.4%
6 4
17.4%
7 3
13.0%
8 2
8.7%
9 4
17.4%
10 3
13.0%
11 2
8.7%
12 1
 
4.3%
ValueCountFrequency (%)
12 1
 
4.3%
11 2
8.7%
10 3
13.0%
9 4
17.4%
8 2
8.7%
7 3
13.0%
6 4
17.4%
5 4
17.4%

안면
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4782609
Minimum0
Maximum7
Zeros10
Zeros (%)43.5%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:42:20.180055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32.5
95-th percentile3.9
Maximum7
Range7
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation1.7804383
Coefficient of variation (CV)1.2044141
Kurtosis2.7240486
Mean1.4782609
Median Absolute Deviation (MAD)1
Skewness1.4679781
Sum34
Variance3.1699605
MonotonicityNot monotonic
2023-12-12T19:42:20.323850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 10
43.5%
2 4
 
17.4%
3 4
 
17.4%
1 3
 
13.0%
4 1
 
4.3%
7 1
 
4.3%
ValueCountFrequency (%)
0 10
43.5%
1 3
 
13.0%
2 4
 
17.4%
3 4
 
17.4%
4 1
 
4.3%
7 1
 
4.3%
ValueCountFrequency (%)
7 1
 
4.3%
4 1
 
4.3%
3 4
 
17.4%
2 4
 
17.4%
1 3
 
13.0%
0 10
43.5%

장루_요루
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)47.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.3913043
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:42:20.477524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.1
Q14
median6
Q39
95-th percentile11
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.0709657
Coefficient of variation (CV)0.48049122
Kurtosis-0.8358586
Mean6.3913043
Median Absolute Deviation (MAD)2
Skewness0.29576184
Sum147
Variance9.43083
MonotonicityNot monotonic
2023-12-12T19:42:20.679271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
4 4
17.4%
5 4
17.4%
7 3
13.0%
10 3
13.0%
6 2
8.7%
11 2
8.7%
2 1
 
4.3%
3 1
 
4.3%
8 1
 
4.3%
1 1
 
4.3%
ValueCountFrequency (%)
1 1
 
4.3%
2 1
 
4.3%
3 1
 
4.3%
4 4
17.4%
5 4
17.4%
6 2
8.7%
7 3
13.0%
8 1
 
4.3%
10 3
13.0%
11 2
8.7%
ValueCountFrequency (%)
12 1
 
4.3%
11 2
8.7%
10 3
13.0%
8 1
 
4.3%
7 3
13.0%
6 2
8.7%
5 4
17.4%
4 4
17.4%
3 1
 
4.3%
2 1
 
4.3%

뇌전증
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)43.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4347826
Minimum0
Maximum12
Zeros2
Zeros (%)8.7%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:42:20.866183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q11.5
median3
Q34
95-th percentile8.9
Maximum12
Range12
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation2.9668791
Coefficient of variation (CV)0.86377493
Kurtosis2.144864
Mean3.4347826
Median Absolute Deviation (MAD)1
Skewness1.4554814
Sum79
Variance8.8023715
MonotonicityNot monotonic
2023-12-12T19:42:21.028544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2 5
21.7%
1 4
17.4%
4 4
17.4%
3 3
13.0%
0 2
 
8.7%
8 1
 
4.3%
12 1
 
4.3%
5 1
 
4.3%
9 1
 
4.3%
6 1
 
4.3%
ValueCountFrequency (%)
0 2
 
8.7%
1 4
17.4%
2 5
21.7%
3 3
13.0%
4 4
17.4%
5 1
 
4.3%
6 1
 
4.3%
8 1
 
4.3%
9 1
 
4.3%
12 1
 
4.3%
ValueCountFrequency (%)
12 1
 
4.3%
9 1
 
4.3%
8 1
 
4.3%
6 1
 
4.3%
5 1
 
4.3%
4 4
17.4%
3 3
13.0%
2 5
21.7%
1 4
17.4%
0 2
 
8.7%

관리부서
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
어르신장애인과
23 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
어르신장애인과 23
100.0%

Length

2023-12-12T19:42:21.207961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:42:21.338226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어르신장애인과 23
100.0%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
Minimum2023-03-22 00:00:00
Maximum2023-03-22 00:00:00
2023-12-12T19:42:21.441771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:21.564343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T19:42:13.189123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:47.363095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:49.577830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:51.514385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:53.319627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:55.079185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:57.269074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:58.815265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:00.743761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:02.861315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:04.309918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:06.059793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:07.804315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:09.792469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:11.524036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:13.313738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:47.481427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:49.734119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:51.647134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:53.425902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:55.582734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:57.369418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:58.943971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:00.899957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:02.960142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:04.428987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:06.184163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:07.927079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:09.915451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:11.623749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:13.443238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:47.638310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:49.878532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:51.759157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:53.542935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:55.745932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:57.457906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:59.098068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:01.066976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:03.060978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:04.541438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:06.300940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:08.039997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:10.019803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:11.728450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:13.551108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:47.741473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:50.033527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:51.883946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:53.667251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:55.891073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:57.547449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:59.227662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:01.187123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:03.154344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:04.672991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:06.409697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:08.150372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:10.151917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:11.835286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:13.663161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:47.843511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:50.143577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:51.990726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:53.769502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:56.018245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:57.620052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:59.352331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:01.293621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:03.236492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:04.787054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:06.514854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:08.253721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:10.290421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:11.934523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:13.819383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:48.312910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:50.273180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:52.102955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:53.875231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:56.145689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:57.706129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:59.492015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:01.396944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:03.331864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:04.904219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:06.630552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:08.363035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:10.431453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:12.054332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:13.930119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:48.434174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:50.412160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:52.233986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:53.978206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:56.286723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:57.788708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:59.629745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:01.511978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:03.423730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:05.035449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:06.759516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:08.492607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:10.542807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:12.191183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:14.044340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:48.589074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:50.524277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:52.355969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:54.094083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:56.394926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:57.876298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:59.766768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:01.621310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:03.497200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:05.146727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:06.866835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:08.597635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:10.643168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:12.291931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:14.159656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:48.694151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:50.629546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:52.478693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:54.201844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:56.519349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:57.956352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:59.884382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:01.734694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:03.587449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:05.251528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:06.981448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:08.712574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:10.737443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:12.396538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:14.266411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:48.801644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:50.734289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:52.605818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:54.307056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:56.622316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:58.029757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:59.995616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:01.855683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:03.666267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:05.346202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:07.083416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:08.804106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:10.830775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:12.486355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:14.402120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:48.929786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:50.863033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:52.740419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:54.434286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:56.757114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:58.123480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:00.121257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:01.971341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:03.760355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:05.474734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:07.199981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:09.203112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:10.929924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:12.622570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:14.529328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:49.082039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:50.983132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:52.866558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:54.569375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:56.886519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:58.233845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:00.236697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:02.425425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:03.880797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:05.623144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:07.338077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:09.303380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:11.048886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:12.746271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:14.627875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:49.186266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:51.113742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:52.983087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:54.715455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:56.993412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:58.409538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:00.363006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:02.564650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:03.989004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:05.737611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:07.472122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:09.406859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:11.156364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:12.869100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:14.726080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:49.326214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:51.244097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:53.095291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:54.854641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:57.093408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:58.564800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:00.501925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:02.665385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:04.100544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:05.848056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:07.575844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:09.530719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:11.273074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:12.974346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:14.823117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:49.459483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:51.389752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:53.193417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:54.969566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:57.178538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:58.671921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:00.622203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:02.755734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:04.196848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:05.948251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:07.686156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:09.663875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:11.406576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:42:13.064933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:42:21.659309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동명지체시각청각언어지적뇌병변자폐성정신신장심장호흡기안면장루_요루뇌전증
동명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
지체1.0001.0000.7220.7530.4960.6630.8790.3240.8340.5970.4830.4820.3210.0000.4440.698
시각1.0000.7221.0000.8980.6730.9060.8180.5300.6100.9000.5580.3270.0000.4500.8270.851
청각1.0000.7530.8981.0000.7300.9240.8530.8110.7730.8380.5010.6610.0000.6800.7530.839
언어1.0000.4960.6730.7301.0000.6580.2900.4250.5160.7510.5720.7310.0000.5380.0000.452
지적1.0000.6630.9060.9240.6581.0000.9250.7130.8170.8140.7100.5650.2740.7520.4020.902
뇌병변1.0000.8790.8180.8530.2900.9251.0000.8410.7720.8100.0000.7090.0000.0000.7080.894
자폐성1.0000.3240.5300.8110.4250.7130.8411.0000.7520.5790.2100.4260.0000.5800.0000.690
정신1.0000.8340.6100.7730.5160.8170.7720.7521.0000.6040.6680.4430.2750.5100.4680.793
신장1.0000.5970.9000.8380.7510.8140.8100.5790.6041.0000.6710.8230.0000.0000.6900.697
심장1.0000.4830.5580.5010.5720.7100.0000.2100.6680.6711.0000.0000.0000.0000.0000.685
호흡기1.0000.4820.3270.6610.7310.5650.7090.4260.4430.8230.0001.0000.0000.0000.0000.437
1.0000.3210.0000.0000.0000.2740.0000.0000.2750.0000.0000.0001.0000.6710.5390.000
안면1.0000.0000.4500.6800.5380.7520.0000.5800.5100.0000.0000.0000.6711.0000.6000.000
장루_요루1.0000.4440.8270.7530.0000.4020.7080.0000.4680.6900.0000.0000.5390.6001.0000.000
뇌전증1.0000.6980.8510.8390.4520.9020.8940.6900.7930.6970.6850.4370.0000.0000.0001.000
2023-12-12T19:42:21.870497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지체시각청각언어지적뇌병변자폐성정신신장심장호흡기안면장루_요루뇌전증
지체1.0000.9220.9500.5170.9670.9650.1100.7180.8730.3850.6440.0620.2940.8550.435
시각0.9221.0000.8940.6220.8890.8860.2710.5900.9060.3210.6310.0480.5100.7760.503
청각0.9500.8941.0000.5100.9090.9000.0720.7520.8590.3760.6910.0220.3040.8400.487
언어0.5170.6220.5101.0000.5280.5040.3070.2240.6260.0670.408-0.0330.3430.5680.267
지적0.9670.8890.9090.5281.0000.9610.1460.6360.8380.3530.6400.0830.2260.8410.442
뇌병변0.9650.8860.9000.5040.9611.0000.1260.6910.8390.2910.5990.0200.3300.8390.426
자폐성0.1100.2710.0720.3070.1460.1261.000-0.3970.354-0.0880.0230.4190.3360.011-0.287
정신0.7180.5900.7520.2240.6360.691-0.3971.0000.5900.2960.421-0.3950.2440.5970.563
신장0.8730.9060.8590.6260.8380.8390.3540.5901.0000.3670.553-0.0160.4500.6930.458
심장0.3850.3210.3760.0670.3530.291-0.0880.2960.3671.0000.296-0.012-0.1220.2870.288
호흡기0.6440.6310.6910.4080.6400.5990.0230.4210.5530.2961.0000.0910.1130.5950.519
0.0620.0480.022-0.0330.0830.0200.419-0.395-0.016-0.0120.0911.000-0.1050.100-0.433
안면0.2940.5100.3040.3430.2260.3300.3360.2440.450-0.1220.113-0.1051.0000.1540.233
장루_요루0.8550.7760.8400.5680.8410.8390.0110.5970.6930.2870.5950.1000.1541.0000.387
뇌전증0.4350.5030.4870.2670.4420.426-0.2870.5630.4580.2880.519-0.4330.2330.3871.000

Missing values

2023-12-12T19:42:14.981770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:42:15.240094image/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

동명지체시각청각언어지적뇌병변자폐성정신신장심장호흡기안면장루_요루뇌전증관리부서기준일자
0성당동53612429512105129135655329070어르신장애인과2023-03-22
1두류1.2동396100222118710975635045173어르신장애인과2023-03-22
2두류3동184391453375433824215022어르신장애인과2023-03-22
3본리동3097316636682203237316230어르신장애인과2023-03-22
4감삼동48913123711931081937390312481어르신장애인과2023-03-22
5죽전동2737616925970926342310242어르신장애인과2023-03-22
6장기동359104165107896192438116154어르신장애인과2023-03-22
7용산1동50710623751381312131490511051어르신장애인과2023-03-22
8용산2동5031082661311210919243834100101어르신장애인과2023-03-22
9이곡1동3769618011778382934038062어르신장애인과2023-03-22
동명지체시각청각언어지적뇌병변자폐성정신신장심장호흡기안면장루_요루뇌전증관리부서기준일자
13월성2동8452014181116521871977848721012어르신장애인과2023-03-22
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