Overview

Dataset statistics

Number of variables7
Number of observations55
Missing cells36
Missing cells (%)9.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory64.4 B

Variable types

Text1
Numeric6

Dataset

Description근로복지공단 지사별, 의료기관 등급별 진료일수 현황입니다.
Author근로복지공단
URLhttps://www.data.go.kr/data/15051517/fileData.do

Alerts

상급종합 has 25 (45.5%) missing valuesMissing
종합병원 has 2 (3.6%) missing valuesMissing
치과 has 2 (3.6%) missing valuesMissing
한방 has 7 (12.7%) missing valuesMissing
지사명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:11:47.741051
Analysis finished2023-12-12 02:11:52.383038
Duration4.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지사명
Text

UNIQUE 

Distinct55
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size572.0 B
2023-12-12T11:11:52.555923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.7454545
Min length4

Characters and Unicode

Total characters261
Distinct characters56
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)100.0%

Sample

1st row서울지역본부
2nd row서울강남지사
3rd row서울서초지사
4th row서울동부지사
5th row서울성동지사
ValueCountFrequency (%)
서울지역본부 1
 
1.8%
포항지사 1
 
1.8%
영주지사 1
 
1.8%
안동지사 1
 
1.8%
경인지역본부 1
 
1.8%
인천북부지사 1
 
1.8%
수원지사 1
 
1.8%
부천지사 1
 
1.8%
안양지사 1
 
1.8%
안산지사 1
 
1.8%
Other values (45) 45
81.8%
2023-12-12T11:11:52.993412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 55
21.1%
사 49
18.8%
부 22
 
8.4%
서 12
 
4.6%
산 11
 
4.2%
울 10
 
3.8%
주 8
 
3.1%
역 6
 
2.3%
본 6
 
2.3%
북 4
 
1.5%
Other values (46) 78
29.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 261
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 55
21.1%
사 49
18.8%
부 22
 
8.4%
서 12
 
4.6%
산 11
 
4.2%
울 10
 
3.8%
주 8
 
3.1%
역 6
 
2.3%
본 6
 
2.3%
북 4
 
1.5%
Other values (46) 78
29.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 261
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 55
21.1%
사 49
18.8%
부 22
 
8.4%
서 12
 
4.6%
산 11
 
4.2%
울 10
 
3.8%
주 8
 
3.1%
역 6
 
2.3%
본 6
 
2.3%
북 4
 
1.5%
Other values (46) 78
29.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 261
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 55
21.1%
사 49
18.8%
부 22
 
8.4%
서 12
 
4.6%
산 11
 
4.2%
울 10
 
3.8%
주 8
 
3.1%
역 6
 
2.3%
본 6
 
2.3%
북 4
 
1.5%
Other values (46) 78
29.9%

상급종합
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)66.7%
Missing25
Missing (%)45.5%
Infinite0
Infinite (%)0.0%
Mean36.933333
Minimum19
Maximum108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T11:11:53.133364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile20.45
Q126.25
median29
Q337.75
95-th percentile91.85
Maximum108
Range89
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation22.129608
Coefficient of variation (CV)0.59917711
Kurtosis5.3494196
Mean36.933333
Median Absolute Deviation (MAD)4.5
Skewness2.4090863
Sum1108
Variance489.71954
MonotonicityNot monotonic
2023-12-12T11:11:53.271636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
29 4
 
7.3%
26 3
 
5.5%
27 2
 
3.6%
28 2
 
3.6%
38 2
 
3.6%
21 2
 
3.6%
31 2
 
3.6%
32 1
 
1.8%
30 1
 
1.8%
108 1
 
1.8%
Other values (10) 10
 
18.2%
(Missing) 25
45.5%
ValueCountFrequency (%)
19 1
 
1.8%
20 1
 
1.8%
21 2
3.6%
22 1
 
1.8%
26 3
5.5%
27 2
3.6%
28 2
3.6%
29 4
7.3%
30 1
 
1.8%
31 2
3.6%
ValueCountFrequency (%)
108 1
1.8%
104 1
1.8%
77 1
1.8%
61 1
1.8%
40 1
1.8%
39 1
1.8%
38 2
3.6%
37 1
1.8%
35 1
1.8%
32 1
1.8%

종합병원
Real number (ℝ)

MISSING 

Distinct38
Distinct (%)71.7%
Missing2
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean63.716981
Minimum22
Maximum158
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T11:11:53.417341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile34
Q148
median56
Q371
95-th percentile110
Maximum158
Range136
Interquartile range (IQR)23

Descriptive statistics

Standard deviation26.091096
Coefficient of variation (CV)0.40948418
Kurtosis2.7291696
Mean63.716981
Median Absolute Deviation (MAD)11
Skewness1.4306525
Sum3377
Variance680.74528
MonotonicityNot monotonic
2023-12-12T11:11:53.571468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
54 4
 
7.3%
60 3
 
5.5%
56 3
 
5.5%
46 3
 
5.5%
49 3
 
5.5%
38 2
 
3.6%
86 2
 
3.6%
51 2
 
3.6%
68 2
 
3.6%
65 1
 
1.8%
Other values (28) 28
50.9%
(Missing) 2
 
3.6%
ValueCountFrequency (%)
22 1
 
1.8%
27 1
 
1.8%
28 1
 
1.8%
38 2
3.6%
40 1
 
1.8%
41 1
 
1.8%
42 1
 
1.8%
43 1
 
1.8%
45 1
 
1.8%
46 3
5.5%
ValueCountFrequency (%)
158 1
1.8%
132 1
1.8%
119 1
1.8%
104 1
1.8%
101 1
1.8%
95 1
1.8%
92 1
1.8%
90 1
1.8%
88 1
1.8%
86 2
3.6%

병원
Real number (ℝ)

Distinct33
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.272727
Minimum29
Maximum203
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T11:11:53.763720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum29
5-th percentile48.5
Q162.5
median69
Q383
95-th percentile117.2
Maximum203
Range174
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation25.919715
Coefficient of variation (CV)0.3398294
Kurtosis9.7903592
Mean76.272727
Median Absolute Deviation (MAD)8
Skewness2.3825077
Sum4195
Variance671.83165
MonotonicityNot monotonic
2023-12-12T11:11:53.911887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
69 5
 
9.1%
61 5
 
9.1%
64 4
 
7.3%
66 3
 
5.5%
74 3
 
5.5%
92 2
 
3.6%
75 2
 
3.6%
59 2
 
3.6%
58 2
 
3.6%
67 2
 
3.6%
Other values (23) 25
45.5%
ValueCountFrequency (%)
29 1
 
1.8%
39 1
 
1.8%
45 1
 
1.8%
50 1
 
1.8%
57 1
 
1.8%
58 2
 
3.6%
59 2
 
3.6%
61 5
9.1%
64 4
7.3%
66 3
5.5%
ValueCountFrequency (%)
203 1
1.8%
123 1
1.8%
120 1
1.8%
116 1
1.8%
115 1
1.8%
110 1
1.8%
105 1
1.8%
94 1
1.8%
93 1
1.8%
92 2
3.6%

의원
Real number (ℝ)

Distinct31
Distinct (%)56.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.418182
Minimum46
Maximum122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T11:11:54.063769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile51.4
Q162
median67
Q373
95-th percentile84.6
Maximum122
Range76
Interquartile range (IQR)11

Descriptive statistics

Standard deviation11.926769
Coefficient of variation (CV)0.17432163
Kurtosis6.625453
Mean68.418182
Median Absolute Deviation (MAD)6
Skewness1.6473038
Sum3763
Variance142.24781
MonotonicityNot monotonic
2023-12-12T11:11:54.214461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
66 4
 
7.3%
76 3
 
5.5%
68 3
 
5.5%
70 3
 
5.5%
59 3
 
5.5%
62 3
 
5.5%
65 3
 
5.5%
73 3
 
5.5%
69 2
 
3.6%
63 2
 
3.6%
Other values (21) 26
47.3%
ValueCountFrequency (%)
46 1
 
1.8%
49 1
 
1.8%
50 1
 
1.8%
52 1
 
1.8%
53 1
 
1.8%
57 2
3.6%
58 1
 
1.8%
59 3
5.5%
60 1
 
1.8%
62 3
5.5%
ValueCountFrequency (%)
122 1
 
1.8%
93 1
 
1.8%
86 1
 
1.8%
84 1
 
1.8%
82 1
 
1.8%
80 2
3.6%
78 1
 
1.8%
77 1
 
1.8%
76 3
5.5%
75 1
 
1.8%

치과
Real number (ℝ)

MISSING 

Distinct37
Distinct (%)69.8%
Missing2
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean37.603774
Minimum1
Maximum228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T11:11:54.414124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.4
Q123
median32
Q343
95-th percentile81
Maximum228
Range227
Interquartile range (IQR)20

Descriptive statistics

Standard deviation33.610518
Coefficient of variation (CV)0.89380705
Kurtosis19.620213
Mean37.603774
Median Absolute Deviation (MAD)11
Skewness3.7251731
Sum1993
Variance1129.6669
MonotonicityNot monotonic
2023-12-12T11:11:54.935318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
39 4
 
7.3%
24 3
 
5.5%
32 3
 
5.5%
43 2
 
3.6%
25 2
 
3.6%
14 2
 
3.6%
27 2
 
3.6%
40 2
 
3.6%
2 2
 
3.6%
33 2
 
3.6%
Other values (27) 29
52.7%
ValueCountFrequency (%)
1 1
1.8%
2 2
3.6%
6 1
1.8%
8 1
1.8%
10 2
3.6%
14 2
3.6%
15 1
1.8%
19 1
1.8%
21 2
3.6%
23 1
1.8%
ValueCountFrequency (%)
228 1
1.8%
100 1
1.8%
84 1
1.8%
79 1
1.8%
69 1
1.8%
65 1
1.8%
60 1
1.8%
55 1
1.8%
51 1
1.8%
50 1
1.8%

한방
Real number (ℝ)

MISSING 

Distinct39
Distinct (%)81.2%
Missing7
Missing (%)12.7%
Infinite0
Infinite (%)0.0%
Mean69.083333
Minimum14
Maximum204
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T11:11:55.085690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile29.05
Q140.75
median56.5
Q387.25
95-th percentile160.65
Maximum204
Range190
Interquartile range (IQR)46.5

Descriptive statistics

Standard deviation41.142634
Coefficient of variation (CV)0.59555079
Kurtosis2.1193344
Mean69.083333
Median Absolute Deviation (MAD)19.5
Skewness1.4636991
Sum3316
Variance1692.7163
MonotonicityNot monotonic
2023-12-12T11:11:55.270529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
31 4
 
7.3%
50 3
 
5.5%
51 2
 
3.6%
37 2
 
3.6%
48 2
 
3.6%
40 2
 
3.6%
96 1
 
1.8%
54 1
 
1.8%
70 1
 
1.8%
28 1
 
1.8%
Other values (29) 29
52.7%
(Missing) 7
 
12.7%
ValueCountFrequency (%)
14 1
 
1.8%
20 1
 
1.8%
28 1
 
1.8%
31 4
7.3%
33 1
 
1.8%
37 2
3.6%
40 2
3.6%
41 1
 
1.8%
44 1
 
1.8%
45 1
 
1.8%
ValueCountFrequency (%)
204 1
1.8%
171 1
1.8%
168 1
1.8%
147 1
1.8%
133 1
1.8%
112 1
1.8%
105 1
1.8%
100 1
1.8%
99 1
1.8%
96 1
1.8%

Interactions

2023-12-12T11:11:51.505504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:47.992981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:48.980288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:49.686751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:50.359496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:50.937778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:51.598837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:48.442005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:49.084795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:49.782137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:50.450956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:51.031448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:51.694388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:48.565049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:49.199827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:49.916638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:50.559752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:51.132272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:51.779478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:48.651080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:49.352048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:50.034337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:50.665656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:51.226717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:51.867060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:48.763243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:49.472597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:50.151166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:50.774465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:51.312677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:51.956802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:48.879860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:49.583187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:50.239913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:50.850100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:11:51.394135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:11:55.402034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지사명상급종합종합병원병원의원치과한방
지사명1.0001.0001.0001.0001.0001.0001.000
상급종합1.0001.0000.0000.5090.3690.0000.000
종합병원1.0000.0001.0000.5950.0000.0000.000
병원1.0000.5090.5951.0000.4180.0000.000
의원1.0000.3690.0000.4181.0000.0000.484
치과1.0000.0000.0000.0000.0001.0000.061
한방1.0000.0000.0000.0000.4840.0611.000
2023-12-12T11:11:55.529729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상급종합종합병원병원의원치과한방
상급종합1.0000.1960.3310.1530.0570.125
종합병원0.1961.0000.2570.2420.122-0.048
병원0.3310.2571.0000.470-0.1170.171
의원0.1530.2420.4701.000-0.1120.311
치과0.0570.122-0.117-0.1121.0000.100
한방0.125-0.0480.1710.3110.1001.000

Missing values

2023-12-12T11:11:52.087216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:11:52.217347image/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.
2023-12-12T11:11:52.320933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

지사명상급종합종합병원병원의원치과한방
0서울지역본부2238646943204
1서울강남지사28272949271
2서울서초지사31<NA>39682131
3서울동부지사293871605560
4서울성동지사31<NA>457069168
5서울서부지사356059596082
6서울남부지사215666782487
7서울북부지사214658624662
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