Overview

Dataset statistics

Number of variables14
Number of observations35
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory127.8 B

Variable types

Text1
Categorical1
Numeric12

Dataset

Description대전보훈병원에서 개방하는 응급환자 진료과별 통계 데이터로 진료과별 (1월~12월)이 포함된 공공데이터입니다.
URLhttps://www.data.go.kr/data/15067504/fileData.do

Alerts

1월 is highly overall correlated with 2월 and 10 other fieldsHigh correlation
2월 is highly overall correlated with 1월 and 10 other fieldsHigh correlation
3월 is highly overall correlated with 1월 and 10 other fieldsHigh correlation
4월 is highly overall correlated with 1월 and 10 other fieldsHigh correlation
5월 is highly overall correlated with 1월 and 10 other fieldsHigh correlation
6월 is highly overall correlated with 1월 and 10 other fieldsHigh correlation
7월 is highly overall correlated with 1월 and 10 other fieldsHigh correlation
8월 is highly overall correlated with 1월 and 10 other fieldsHigh correlation
9월 is highly overall correlated with 1월 and 10 other fieldsHigh correlation
10월 is highly overall correlated with 1월 and 10 other fieldsHigh correlation
11월 is highly overall correlated with 1월 and 10 other fieldsHigh correlation
12월 is highly overall correlated with 1월 and 10 other fieldsHigh correlation
1월 has 12 (34.3%) zerosZeros
2월 has 15 (42.9%) zerosZeros
3월 has 11 (31.4%) zerosZeros
4월 has 10 (28.6%) zerosZeros
5월 has 8 (22.9%) zerosZeros
6월 has 10 (28.6%) zerosZeros
7월 has 7 (20.0%) zerosZeros
8월 has 6 (17.1%) zerosZeros
9월 has 10 (28.6%) zerosZeros
10월 has 9 (25.7%) zerosZeros
11월 has 7 (20.0%) zerosZeros
12월 has 8 (22.9%) zerosZeros

Reproduction

Analysis started2023-12-12 16:07:50.437915
Analysis finished2023-12-12 16:08:03.030122
Duration12.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

Distinct19
Distinct (%)54.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-13T01:08:03.145204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.2571429
Min length2

Characters and Unicode

Total characters149
Distinct characters40
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

Unique3 ?
Unique (%)8.6%

Sample

1st row가정의학과
2nd row가정의학과
3rd row내과
4th row내과
5th row내분비내과
ValueCountFrequency (%)
가정의학과 2
 
5.7%
내과 2
 
5.7%
혈액종양내과 2
 
5.7%
정형외과 2
 
5.7%
이비인후과 2
 
5.7%
응급실 2
 
5.7%
외과 2
 
5.7%
심장내과 2
 
5.7%
신장내과 2
 
5.7%
신경외과 2
 
5.7%
Other values (9) 15
42.9%
2023-12-13T01:08:03.421522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 33
22.1%
내 18
 
12.1%
외 6
 
4.0%
비 6
 
4.0%
신 6
 
4.0%
의 4
 
2.7%
학 4
 
2.7%
장 4
 
2.7%
정 4
 
2.7%
기 4
 
2.7%
Other values (30) 60
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 149
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 33
22.1%
내 18
 
12.1%
외 6
 
4.0%
비 6
 
4.0%
신 6
 
4.0%
의 4
 
2.7%
학 4
 
2.7%
장 4
 
2.7%
정 4
 
2.7%
기 4
 
2.7%
Other values (30) 60
40.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 149
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 33
22.1%
내 18
 
12.1%
외 6
 
4.0%
비 6
 
4.0%
신 6
 
4.0%
의 4
 
2.7%
학 4
 
2.7%
장 4
 
2.7%
정 4
 
2.7%
기 4
 
2.7%
Other values (30) 60
40.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 149
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 33
22.1%
내 18
 
12.1%
외 6
 
4.0%
비 6
 
4.0%
신 6
 
4.0%
의 4
 
2.7%
학 4
 
2.7%
장 4
 
2.7%
정 4
 
2.7%
기 4
 
2.7%
Other values (30) 60
40.3%

국사비
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
사비
18 
국비
17 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row국비
2nd row사비
3rd row국비
4th row사비
5th row국비

Common Values

ValueCountFrequency (%)
사비 18
51.4%
국비 17
48.6%

Length

2023-12-13T01:08:03.530095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:08:03.619849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사비 18
51.4%
국비 17
48.6%

1월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.142857
Minimum0
Maximum166
Zeros12
Zeros (%)34.3%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T01:08:03.692505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34.5
95-th percentile39.4
Maximum166
Range166
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation32.002889
Coefficient of variation (CV)3.1552144
Kurtosis18.743876
Mean10.142857
Median Absolute Deviation (MAD)1
Skewness4.2969406
Sum355
Variance1024.1849
MonotonicityNot monotonic
2023-12-13T01:08:03.780986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 12
34.3%
1 8
22.9%
3 2
 
5.7%
7 2
 
5.7%
4 2
 
5.7%
2 2
 
5.7%
10 1
 
2.9%
5 1
 
2.9%
101 1
 
2.9%
166 1
 
2.9%
Other values (3) 3
 
8.6%
ValueCountFrequency (%)
0 12
34.3%
1 8
22.9%
2 2
 
5.7%
3 2
 
5.7%
4 2
 
5.7%
5 1
 
2.9%
7 2
 
5.7%
8 1
 
2.9%
10 1
 
2.9%
12 1
 
2.9%
ValueCountFrequency (%)
166 1
2.9%
101 1
2.9%
13 1
2.9%
12 1
2.9%
10 1
2.9%
8 1
2.9%
7 2
5.7%
5 1
2.9%
4 2
5.7%
3 2
5.7%

2월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)34.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.9714286
Minimum0
Maximum173
Zeros15
Zeros (%)42.9%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T01:08:03.867133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35
95-th percentile37.5
Maximum173
Range173
Interquartile range (IQR)5

Descriptive statistics

Standard deviation32.73466
Coefficient of variation (CV)3.2828456
Kurtosis20.065267
Mean9.9714286
Median Absolute Deviation (MAD)1
Skewness4.4206663
Sum349
Variance1071.558
MonotonicityNot monotonic
2023-12-13T01:08:03.953159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 15
42.9%
1 6
 
17.1%
2 3
 
8.6%
5 2
 
5.7%
9 2
 
5.7%
12 1
 
2.9%
6 1
 
2.9%
97 1
 
2.9%
173 1
 
2.9%
4 1
 
2.9%
Other values (2) 2
 
5.7%
ValueCountFrequency (%)
0 15
42.9%
1 6
 
17.1%
2 3
 
8.6%
4 1
 
2.9%
5 2
 
5.7%
6 1
 
2.9%
7 1
 
2.9%
9 2
 
5.7%
10 1
 
2.9%
12 1
 
2.9%
ValueCountFrequency (%)
173 1
 
2.9%
97 1
 
2.9%
12 1
 
2.9%
10 1
 
2.9%
9 2
5.7%
7 1
 
2.9%
6 1
 
2.9%
5 2
5.7%
4 1
 
2.9%
2 3
8.6%

3월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.4857143
Minimum0
Maximum170
Zeros11
Zeros (%)31.4%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T01:08:04.055389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35.5
95-th percentile29.1
Maximum170
Range170
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation30.714407
Coefficient of variation (CV)3.2379646
Kurtosis23.670096
Mean9.4857143
Median Absolute Deviation (MAD)1
Skewness4.751534
Sum332
Variance943.37479
MonotonicityNot monotonic
2023-12-13T01:08:04.146143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 11
31.4%
1 8
22.9%
2 4
 
11.4%
9 4
 
11.4%
5 2
 
5.7%
7 2
 
5.7%
6 1
 
2.9%
76 1
 
2.9%
170 1
 
2.9%
4 1
 
2.9%
ValueCountFrequency (%)
0 11
31.4%
1 8
22.9%
2 4
 
11.4%
4 1
 
2.9%
5 2
 
5.7%
6 1
 
2.9%
7 2
 
5.7%
9 4
 
11.4%
76 1
 
2.9%
170 1
 
2.9%
ValueCountFrequency (%)
170 1
 
2.9%
76 1
 
2.9%
9 4
 
11.4%
7 2
 
5.7%
6 1
 
2.9%
5 2
 
5.7%
4 1
 
2.9%
2 4
 
11.4%
1 8
22.9%
0 11
31.4%

4월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.342857
Minimum0
Maximum170
Zeros10
Zeros (%)28.6%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T01:08:04.254339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35
95-th percentile35.8
Maximum170
Range170
Interquartile range (IQR)5

Descriptive statistics

Standard deviation31.092786
Coefficient of variation (CV)3.0062086
Kurtosis22.110693
Mean10.342857
Median Absolute Deviation (MAD)1
Skewness4.5840733
Sum362
Variance966.76134
MonotonicityNot monotonic
2023-12-13T01:08:04.348459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 10
28.6%
1 8
22.9%
4 3
 
8.6%
2 2
 
5.7%
3 2
 
5.7%
5 2
 
5.7%
9 2
 
5.7%
12 1
 
2.9%
14 1
 
2.9%
10 1
 
2.9%
Other values (3) 3
 
8.6%
ValueCountFrequency (%)
0 10
28.6%
1 8
22.9%
2 2
 
5.7%
3 2
 
5.7%
4 3
 
8.6%
5 2
 
5.7%
9 2
 
5.7%
10 1
 
2.9%
12 1
 
2.9%
14 1
 
2.9%
ValueCountFrequency (%)
170 1
 
2.9%
82 1
 
2.9%
16 1
 
2.9%
14 1
 
2.9%
12 1
 
2.9%
10 1
 
2.9%
9 2
5.7%
5 2
5.7%
4 3
8.6%
3 2
5.7%

5월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.485714
Minimum0
Maximum181
Zeros8
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T01:08:04.460852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q36
95-th percentile29.5
Maximum181
Range181
Interquartile range (IQR)5

Descriptive statistics

Standard deviation31.487973
Coefficient of variation (CV)3.0029402
Kurtosis27.132738
Mean10.485714
Median Absolute Deviation (MAD)2
Skewness5.0641227
Sum367
Variance991.49244
MonotonicityNot monotonic
2023-12-13T01:08:04.566807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 8
22.9%
3 7
20.0%
1 4
11.4%
2 4
11.4%
5 3
 
8.6%
15 1
 
2.9%
16 1
 
2.9%
8 1
 
2.9%
7 1
 
2.9%
61 1
 
2.9%
Other values (4) 4
11.4%
ValueCountFrequency (%)
0 8
22.9%
1 4
11.4%
2 4
11.4%
3 7
20.0%
5 3
 
8.6%
7 1
 
2.9%
8 1
 
2.9%
9 1
 
2.9%
10 1
 
2.9%
12 1
 
2.9%
ValueCountFrequency (%)
181 1
 
2.9%
61 1
 
2.9%
16 1
 
2.9%
15 1
 
2.9%
12 1
 
2.9%
10 1
 
2.9%
9 1
 
2.9%
8 1
 
2.9%
7 1
 
2.9%
5 3
8.6%

6월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)34.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10
Minimum0
Maximum185
Zeros10
Zeros (%)28.6%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T01:08:04.656790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q34.5
95-th percentile31.9
Maximum185
Range185
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation32.624422
Coefficient of variation (CV)3.2624422
Kurtosis26.150616
Mean10
Median Absolute Deviation (MAD)2
Skewness4.9830147
Sum350
Variance1064.3529
MonotonicityNot monotonic
2023-12-13T01:08:04.745596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 10
28.6%
1 5
14.3%
3 5
14.3%
2 4
 
11.4%
4 2
 
5.7%
5 2
 
5.7%
8 2
 
5.7%
69 1
 
2.9%
185 1
 
2.9%
7 1
 
2.9%
Other values (2) 2
 
5.7%
ValueCountFrequency (%)
0 10
28.6%
1 5
14.3%
2 4
 
11.4%
3 5
14.3%
4 2
 
5.7%
5 2
 
5.7%
7 1
 
2.9%
8 2
 
5.7%
11 1
 
2.9%
16 1
 
2.9%
ValueCountFrequency (%)
185 1
 
2.9%
69 1
 
2.9%
16 1
 
2.9%
11 1
 
2.9%
8 2
 
5.7%
7 1
 
2.9%
5 2
 
5.7%
4 2
 
5.7%
3 5
14.3%
2 4
11.4%

7월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.428571
Minimum0
Maximum238
Zeros7
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T01:08:04.838752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q36
95-th percentile33.7
Maximum238
Range238
Interquartile range (IQR)5

Descriptive statistics

Standard deviation41.284726
Coefficient of variation (CV)3.3217595
Kurtosis28.181448
Mean12.428571
Median Absolute Deviation (MAD)2
Skewness5.1814009
Sum435
Variance1704.4286
MonotonicityNot monotonic
2023-12-13T01:08:04.921557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2 9
25.7%
0 7
20.0%
1 5
14.3%
3 3
 
8.6%
12 2
 
5.7%
5 2
 
5.7%
14 1
 
2.9%
10 1
 
2.9%
9 1
 
2.9%
75 1
 
2.9%
Other values (3) 3
 
8.6%
ValueCountFrequency (%)
0 7
20.0%
1 5
14.3%
2 9
25.7%
3 3
 
8.6%
5 2
 
5.7%
7 1
 
2.9%
9 1
 
2.9%
10 1
 
2.9%
12 2
 
5.7%
14 1
 
2.9%
ValueCountFrequency (%)
238 1
 
2.9%
75 1
 
2.9%
16 1
 
2.9%
14 1
 
2.9%
12 2
5.7%
10 1
 
2.9%
9 1
 
2.9%
7 1
 
2.9%
5 2
5.7%
3 3
8.6%

8월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.6
Minimum0
Maximum245
Zeros6
Zeros (%)17.1%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T01:08:05.007457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q35.5
95-th percentile41.7
Maximum245
Range245
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation43.860206
Coefficient of variation (CV)3.2250151
Kurtosis24.543532
Mean13.6
Median Absolute Deviation (MAD)2
Skewness4.8379726
Sum476
Variance1923.7176
MonotonicityNot monotonic
2023-12-13T01:08:05.096235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 6
17.1%
3 5
14.3%
1 5
14.3%
2 5
14.3%
5 3
8.6%
4 2
 
5.7%
6 2
 
5.7%
10 2
 
5.7%
13 1
 
2.9%
15 1
 
2.9%
Other values (3) 3
8.6%
ValueCountFrequency (%)
0 6
17.1%
1 5
14.3%
2 5
14.3%
3 5
14.3%
4 2
 
5.7%
5 3
8.6%
6 2
 
5.7%
10 2
 
5.7%
13 1
 
2.9%
14 1
 
2.9%
ValueCountFrequency (%)
245 1
 
2.9%
104 1
 
2.9%
15 1
 
2.9%
14 1
 
2.9%
13 1
 
2.9%
10 2
 
5.7%
6 2
 
5.7%
5 3
8.6%
4 2
 
5.7%
3 5
14.3%

9월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.057143
Minimum0
Maximum249
Zeros10
Zeros (%)28.6%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T01:08:05.184762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q39
95-th percentile44.9
Maximum249
Range249
Interquartile range (IQR)9

Descriptive statistics

Standard deviation44.460123
Coefficient of variation (CV)3.1628136
Kurtosis24.64896
Mean14.057143
Median Absolute Deviation (MAD)3
Skewness4.8345284
Sum492
Variance1976.7025
MonotonicityNot monotonic
2023-12-13T01:08:05.276166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 10
28.6%
3 6
17.1%
1 4
 
11.4%
2 3
 
8.6%
10 2
 
5.7%
13 2
 
5.7%
7 1
 
2.9%
8 1
 
2.9%
4 1
 
2.9%
103 1
 
2.9%
Other values (4) 4
 
11.4%
ValueCountFrequency (%)
0 10
28.6%
1 4
 
11.4%
2 3
 
8.6%
3 6
17.1%
4 1
 
2.9%
7 1
 
2.9%
8 1
 
2.9%
10 2
 
5.7%
11 1
 
2.9%
13 2
 
5.7%
ValueCountFrequency (%)
249 1
2.9%
103 1
2.9%
20 1
2.9%
16 1
2.9%
13 2
5.7%
11 1
2.9%
10 2
5.7%
8 1
2.9%
7 1
2.9%
4 1
2.9%

10월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.942857
Minimum0
Maximum186
Zeros9
Zeros (%)25.7%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T01:08:05.364158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q36.5
95-th percentile38.4
Maximum186
Range186
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation34.05095
Coefficient of variation (CV)2.8511561
Kurtosis21.809648
Mean11.942857
Median Absolute Deviation (MAD)3
Skewness4.5665062
Sum418
Variance1159.4672
MonotonicityNot monotonic
2023-12-13T01:08:05.467485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 9
25.7%
2 6
17.1%
3 4
11.4%
5 4
11.4%
6 3
 
8.6%
9 2
 
5.7%
14 1
 
2.9%
7 1
 
2.9%
93 1
 
2.9%
186 1
 
2.9%
Other values (3) 3
 
8.6%
ValueCountFrequency (%)
0 9
25.7%
2 6
17.1%
3 4
11.4%
5 4
11.4%
6 3
 
8.6%
7 1
 
2.9%
9 2
 
5.7%
10 1
 
2.9%
13 1
 
2.9%
14 1
 
2.9%
ValueCountFrequency (%)
186 1
 
2.9%
93 1
 
2.9%
15 1
 
2.9%
14 1
 
2.9%
13 1
 
2.9%
10 1
 
2.9%
9 2
5.7%
7 1
 
2.9%
6 3
8.6%
5 4
11.4%

11월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.971429
Minimum0
Maximum179
Zeros7
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T01:08:05.570595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q37.5
95-th percentile40.3
Maximum179
Range179
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation33.306496
Coefficient of variation (CV)2.7821656
Kurtosis20.410825
Mean11.971429
Median Absolute Deviation (MAD)3
Skewness4.4306836
Sum419
Variance1109.3227
MonotonicityNot monotonic
2023-12-13T01:08:05.663720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 7
20.0%
1 5
14.3%
2 5
14.3%
5 4
11.4%
11 3
8.6%
6 3
8.6%
10 1
 
2.9%
3 1
 
2.9%
4 1
 
2.9%
97 1
 
2.9%
Other values (4) 4
11.4%
ValueCountFrequency (%)
0 7
20.0%
1 5
14.3%
2 5
14.3%
3 1
 
2.9%
4 1
 
2.9%
5 4
11.4%
6 3
8.6%
9 1
 
2.9%
10 1
 
2.9%
11 3
8.6%
ValueCountFrequency (%)
179 1
 
2.9%
97 1
 
2.9%
16 1
 
2.9%
15 1
 
2.9%
11 3
8.6%
10 1
 
2.9%
9 1
 
2.9%
6 3
8.6%
5 4
11.4%
4 1
 
2.9%

12월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.514286
Minimum0
Maximum183
Zeros8
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-13T01:08:05.754689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q36
95-th percentile42.4
Maximum183
Range183
Interquartile range (IQR)5

Descriptive statistics

Standard deviation33.988209
Coefficient of variation (CV)2.9518295
Kurtosis20.869092
Mean11.514286
Median Absolute Deviation (MAD)3
Skewness4.483334
Sum403
Variance1155.1983
MonotonicityNot monotonic
2023-12-13T01:08:05.846434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 8
22.9%
1 5
14.3%
4 3
 
8.6%
3 3
 
8.6%
5 3
 
8.6%
2 3
 
8.6%
6 2
 
5.7%
9 2
 
5.7%
8 1
 
2.9%
7 1
 
2.9%
Other values (4) 4
11.4%
ValueCountFrequency (%)
0 8
22.9%
1 5
14.3%
2 3
 
8.6%
3 3
 
8.6%
4 3
 
8.6%
5 3
 
8.6%
6 2
 
5.7%
7 1
 
2.9%
8 1
 
2.9%
9 2
 
5.7%
ValueCountFrequency (%)
183 1
 
2.9%
97 1
 
2.9%
19 1
 
2.9%
12 1
 
2.9%
9 2
5.7%
8 1
 
2.9%
7 1
 
2.9%
6 2
5.7%
5 3
8.6%
4 3
8.6%

Interactions

2023-12-13T01:08:01.553260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:50.855749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:51.985085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:53.179735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:54.057053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:54.979777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:55.841811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:56.686938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:57.766674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:58.636004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:59.490068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:00.504631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:01.633749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:50.953714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:52.070823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:53.250846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:54.149026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:55.046856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:55.909331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:56.764777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:57.831748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:58.708959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:59.579010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:00.582583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:01.721087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:51.043057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:52.171842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:53.320899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:54.228765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:55.118535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:55.981222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:56.844661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:57.907294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:58.776505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:59.673684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:00.672684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:01.795183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:51.132915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:52.269226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:53.393332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:54.301853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:55.192579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:56.050980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:56.918582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:57.980921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:58.847481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:59.751184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:00.772390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:01.864025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:51.222172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:52.361477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:53.465601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:54.385644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:55.266504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:56.121537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:56.995816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:58.048676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:58.915900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:59.831663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:00.875944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:01.955651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:51.310129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:52.442661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:53.541266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:54.458676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:55.335626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:56.191320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:57.063175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:58.115330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:58.985039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:59.915938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:00.969221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:02.039505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:51.408529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:52.524339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:53.612946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:54.533225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:55.408001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:56.263652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:57.128401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:58.183887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:59.052313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:00.011429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:01.068927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:02.119395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:51.488683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:52.602918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:53.681155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:54.596869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:55.471304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:56.325594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:57.186350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:58.254918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:59.117179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:00.090744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:01.149212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:02.193548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:51.584380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:52.671099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:53.748730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:54.667066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:55.552731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:56.389798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:57.485710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:58.329989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:59.180236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:00.174528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:01.239461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:02.596929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:51.701692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:52.972488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:53.816608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:54.735634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:55.620259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:56.460020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:57.552423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:58.406312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:59.243546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:00.251369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:01.316194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:02.666330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:51.813555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:53.038386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:53.886552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:54.818713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:55.696428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:56.533594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:57.632381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:58.487636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:59.328940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:00.335748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:01.400398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:02.737383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:51.904370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:53.107624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:53.965996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:54.899933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:55.767655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:56.606327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:57.700025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:58.569867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:07:59.410526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:00.421919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:08:01.482553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:08:05.927447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분국사비1월2월3월4월5월6월7월8월9월10월11월12월
구분1.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
국사비0.0001.0000.0060.0060.0060.0060.0060.0060.0060.0060.0060.0060.0060.000
1월0.0000.0061.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2월0.0000.0061.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
3월0.0000.0061.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
4월0.0000.0061.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
5월0.0000.0061.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
6월0.0000.0061.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
7월0.0000.0061.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
8월0.0000.0061.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
9월0.0000.0061.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
10월0.0000.0061.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
11월0.0000.0061.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
12월0.0000.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-13T01:08:06.051568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1월2월3월4월5월6월7월8월9월10월11월12월국사비
1월1.0000.7940.7150.7830.8120.7600.7530.6860.7590.7470.7220.7000.000
2월0.7941.0000.6510.6670.8140.8360.7480.6330.7120.7950.6790.6920.000
3월0.7150.6511.0000.8350.7740.8240.7860.7450.8540.7740.8740.8100.000
4월0.7830.6670.8351.0000.7920.8040.7720.8010.8650.8280.9120.8050.000
5월0.8120.8140.7740.7921.0000.7980.8450.7270.7780.7760.7930.7590.000
6월0.7600.8360.8240.8040.7981.0000.8290.7750.8680.8920.8800.8380.000
7월0.7530.7480.7860.7720.8450.8291.0000.7970.8400.8340.8440.8580.000
8월0.6860.6330.7450.8010.7270.7750.7971.0000.8370.8220.8210.8340.000
9월0.7590.7120.8540.8650.7780.8680.8400.8371.0000.8720.8780.8940.000
10월0.7470.7950.7740.8280.7760.8920.8340.8220.8721.0000.8460.8540.000
11월0.7220.6790.8740.9120.7930.8800.8440.8210.8780.8461.0000.8810.000
12월0.7000.6920.8100.8050.7590.8380.8580.8340.8940.8540.8811.0000.000
국사비0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-13T01:08:02.840116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:08:02.980322image/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

구분국사비1월2월3월4월5월6월7월8월9월10월11월12월
0가정의학과국비000011000000
1가정의학과사비011003233314
2내과국비352133212221
3내과사비022052323524
4내분비내과국비100110141300
5내분비내과사비120031120211
6류마티스내과국비000101212523
7류마티스내과사비001110020211
8비뇨의학과국비001100200021
9비뇨의학과사비000020100000
구분국사비1월2월3월4월5월6월7월8월9월10월11월12월
25응급실사비166173170170181185238245249186179183
26이비인후과국비000000110000
27이비인후과사비000000000001
28정형외과국비8479107731310115
29정형외과사비12771691612616131612
30피부과국비000000000010
31혈액종양내과국비7102458333666
32혈액종양내과사비139991211161420151519
33호흡기내과국비104553353399
34호흡기내과사비109423210112114