Overview

Dataset statistics

Number of variables14
Number of observations299
Missing cells126
Missing cells (%)3.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory34.9 KiB
Average record size in memory119.4 B

Variable types

Text4
Categorical8
Numeric2

Dataset

Description한국보훈복지의료공단 인천보훈병원에서 제공하는 통합EMR시스템 내 용법정보(용법코드, 투여경로, 약어약사, 약어의사, 기준일수, 투여횟수, 용법, 용법1, 용법2, 식전 식후, 아침, 점심, 저녁, 자기전)입니다.
URLhttps://www.data.go.kr/data/15117916/fileData.do

Alerts

용법2 is highly overall correlated with 투여경로High correlation
식전 식후 is highly overall correlated with 투여경로 and 4 other fieldsHigh correlation
투여경로 is highly overall correlated with 용법2 and 4 other fieldsHigh correlation
기준일수 is highly overall correlated with 용법High correlation
투여횟수 is highly overall correlated with 용법 and 1 other fieldsHigh correlation
용법 is highly overall correlated with 기준일수 and 1 other fieldsHigh correlation
아침 is highly overall correlated with 투여경로 and 3 other fieldsHigh correlation
점심 is highly overall correlated with 투여경로 and 4 other fieldsHigh correlation
저녁 is highly overall correlated with 투여경로 and 4 other fieldsHigh correlation
자기전 is highly overall correlated with 투여횟수 and 3 other fieldsHigh correlation
기준일수 has 37 (12.4%) missing valuesMissing
투여횟수 has 69 (23.1%) missing valuesMissing
용법1 has 20 (6.7%) missing valuesMissing
용법코드 has unique valuesUnique
약어약사 has unique valuesUnique
약어의사 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:49:27.381730
Analysis finished2023-12-12 03:49:29.642857
Duration2.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

용법코드
Text

UNIQUE 

Distinct299
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-12T12:49:30.104620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.2240803
Min length1

Characters and Unicode

Total characters964
Distinct characters33
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique299 ?
Unique (%)100.0%

Sample

1st rowIDA
2nd rowIDDA
3rd rowIDDP
4th rowIDEA
5th rowIDEP
ValueCountFrequency (%)
ida 1
 
0.3%
boha 1
 
0.3%
bofo 1
 
0.3%
bofn 1
 
0.3%
bofh 1
 
0.3%
bofa 1
 
0.3%
boeb 1
 
0.3%
boch 1
 
0.3%
boca 1
 
0.3%
bobu 1
 
0.3%
Other values (289) 289
96.7%
2023-12-12T12:49:30.894417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
D 100
 
10.4%
O 98
 
10.2%
I 71
 
7.4%
A 71
 
7.4%
B 70
 
7.3%
R 51
 
5.3%
P 47
 
4.9%
H 46
 
4.8%
E 45
 
4.7%
T 36
 
3.7%
Other values (23) 329
34.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 838
86.9%
Decimal Number 126
 
13.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
D 100
11.9%
O 98
11.7%
I 71
 
8.5%
A 71
 
8.5%
B 70
 
8.4%
R 51
 
6.1%
P 47
 
5.6%
H 46
 
5.5%
E 45
 
5.4%
T 36
 
4.3%
Other values (14) 203
24.2%
Decimal Number
ValueCountFrequency (%)
1 36
28.6%
2 32
25.4%
4 15
11.9%
5 10
 
7.9%
6 10
 
7.9%
3 9
 
7.1%
7 7
 
5.6%
8 6
 
4.8%
0 1
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 838
86.9%
Common 126
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
D 100
11.9%
O 98
11.7%
I 71
 
8.5%
A 71
 
8.5%
B 70
 
8.4%
R 51
 
6.1%
P 47
 
5.6%
H 46
 
5.5%
E 45
 
5.4%
T 36
 
4.3%
Other values (14) 203
24.2%
Common
ValueCountFrequency (%)
1 36
28.6%
2 32
25.4%
4 15
11.9%
5 10
 
7.9%
6 10
 
7.9%
3 9
 
7.1%
7 7
 
5.6%
8 6
 
4.8%
0 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 964
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
D 100
 
10.4%
O 98
 
10.2%
I 71
 
7.4%
A 71
 
7.4%
B 70
 
7.3%
R 51
 
5.3%
P 47
 
4.9%
H 46
 
4.8%
E 45
 
4.7%
T 36
 
3.7%
Other values (23) 329
34.1%

투여경로
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2
145 
1
99 
0
55 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
2 145
48.5%
1 99
33.1%
0 55
 
18.4%

Length

2023-12-12T12:49:31.069755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:49:31.189813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 145
48.5%
1 99
33.1%
0 55
 
18.4%

약어약사
Text

UNIQUE 

Distinct299
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-12T12:49:31.671060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.2240803
Min length1

Characters and Unicode

Total characters964
Distinct characters33
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique299 ?
Unique (%)100.0%

Sample

1st rowIDA
2nd rowIDDA
3rd rowIDDP
4th rowIDEA
5th rowIDEP
ValueCountFrequency (%)
ida 1
 
0.3%
boha 1
 
0.3%
bofo 1
 
0.3%
bofn 1
 
0.3%
bofh 1
 
0.3%
bofa 1
 
0.3%
boeb 1
 
0.3%
boch 1
 
0.3%
boca 1
 
0.3%
bobu 1
 
0.3%
Other values (289) 289
96.7%
2023-12-12T12:49:32.322790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
D 100
 
10.4%
O 98
 
10.2%
I 71
 
7.4%
A 71
 
7.4%
B 70
 
7.3%
R 51
 
5.3%
P 47
 
4.9%
H 46
 
4.8%
E 45
 
4.7%
T 36
 
3.7%
Other values (23) 329
34.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 838
86.9%
Decimal Number 126
 
13.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
D 100
11.9%
O 98
11.7%
I 71
 
8.5%
A 71
 
8.5%
B 70
 
8.4%
R 51
 
6.1%
P 47
 
5.6%
H 46
 
5.5%
E 45
 
5.4%
T 36
 
4.3%
Other values (14) 203
24.2%
Decimal Number
ValueCountFrequency (%)
1 36
28.6%
2 32
25.4%
4 15
11.9%
5 10
 
7.9%
6 10
 
7.9%
3 9
 
7.1%
7 7
 
5.6%
8 6
 
4.8%
0 1
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 838
86.9%
Common 126
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
D 100
11.9%
O 98
11.7%
I 71
 
8.5%
A 71
 
8.5%
B 70
 
8.4%
R 51
 
6.1%
P 47
 
5.6%
H 46
 
5.5%
E 45
 
5.4%
T 36
 
4.3%
Other values (14) 203
24.2%
Common
ValueCountFrequency (%)
1 36
28.6%
2 32
25.4%
4 15
11.9%
5 10
 
7.9%
6 10
 
7.9%
3 9
 
7.1%
7 7
 
5.6%
8 6
 
4.8%
0 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 964
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
D 100
 
10.4%
O 98
 
10.2%
I 71
 
7.4%
A 71
 
7.4%
B 70
 
7.3%
R 51
 
5.3%
P 47
 
4.9%
H 46
 
4.8%
E 45
 
4.7%
T 36
 
3.7%
Other values (23) 329
34.1%

약어의사
Text

UNIQUE 

Distinct299
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-12T12:49:32.769471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.2240803
Min length1

Characters and Unicode

Total characters964
Distinct characters36
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique299 ?
Unique (%)100.0%

Sample

1st rowIDA
2nd rowIDDA
3rd rowIDDP
4th rowIDEA
5th rowIDEP
ValueCountFrequency (%)
ida 1
 
0.3%
boha 1
 
0.3%
bofo 1
 
0.3%
bofn 1
 
0.3%
bofh 1
 
0.3%
bofa 1
 
0.3%
boeb 1
 
0.3%
boch 1
 
0.3%
boca 1
 
0.3%
bobu 1
 
0.3%
Other values (289) 289
96.7%
2023-12-12T12:49:33.384073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
D 100
 
10.4%
O 98
 
10.2%
I 71
 
7.4%
B 70
 
7.3%
A 70
 
7.3%
R 51
 
5.3%
P 47
 
4.9%
H 46
 
4.8%
E 45
 
4.7%
1 36
 
3.7%
Other values (26) 330
34.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 835
86.6%
Decimal Number 126
 
13.1%
Lowercase Letter 3
 
0.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
D 100
12.0%
O 98
11.7%
I 71
 
8.5%
B 70
 
8.4%
A 70
 
8.4%
R 51
 
6.1%
P 47
 
5.6%
H 46
 
5.5%
E 45
 
5.4%
T 36
 
4.3%
Other values (14) 201
24.1%
Decimal Number
ValueCountFrequency (%)
1 36
28.6%
2 32
25.4%
4 15
11.9%
6 10
 
7.9%
5 10
 
7.9%
3 9
 
7.1%
7 7
 
5.6%
8 6
 
4.8%
0 1
 
0.8%
Lowercase Letter
ValueCountFrequency (%)
m 1
33.3%
a 1
33.3%
n 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 838
86.9%
Common 126
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
D 100
11.9%
O 98
11.7%
I 71
 
8.5%
B 70
 
8.4%
A 70
 
8.4%
R 51
 
6.1%
P 47
 
5.6%
H 46
 
5.5%
E 45
 
5.4%
T 36
 
4.3%
Other values (17) 204
24.3%
Common
ValueCountFrequency (%)
1 36
28.6%
2 32
25.4%
4 15
11.9%
6 10
 
7.9%
5 10
 
7.9%
3 9
 
7.1%
7 7
 
5.6%
8 6
 
4.8%
0 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 964
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
D 100
 
10.4%
O 98
 
10.2%
I 71
 
7.4%
B 70
 
7.3%
A 70
 
7.3%
R 51
 
5.3%
P 47
 
4.9%
H 46
 
4.8%
E 45
 
4.7%
1 36
 
3.7%
Other values (26) 330
34.2%

기준일수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9
Distinct (%)3.4%
Missing37
Missing (%)12.4%
Infinite0
Infinite (%)0.0%
Mean2.7251908
Minimum1
Maximum84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T12:49:33.520426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile7
Maximum84
Range83
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.4268804
Coefficient of variation (CV)3.0922166
Kurtosis66.832031
Mean2.7251908
Median Absolute Deviation (MAD)0
Skewness7.608427
Sum714
Variance71.012313
MonotonicityNot monotonic
2023-12-12T12:49:33.633057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 233
77.9%
7 11
 
3.7%
28 6
 
2.0%
2 4
 
1.3%
3 2
 
0.7%
14 2
 
0.7%
84 2
 
0.7%
5 1
 
0.3%
21 1
 
0.3%
(Missing) 37
 
12.4%
ValueCountFrequency (%)
1 233
77.9%
2 4
 
1.3%
3 2
 
0.7%
5 1
 
0.3%
7 11
 
3.7%
14 2
 
0.7%
21 1
 
0.3%
28 6
 
2.0%
84 2
 
0.7%
ValueCountFrequency (%)
84 2
 
0.7%
28 6
 
2.0%
21 1
 
0.3%
14 2
 
0.7%
7 11
 
3.7%
5 1
 
0.3%
3 2
 
0.7%
2 4
 
1.3%
1 233
77.9%

투여횟수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9
Distinct (%)3.9%
Missing69
Missing (%)23.1%
Infinite0
Infinite (%)0.0%
Mean2.3652174
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T12:49:33.741792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile6
Maximum12
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.6734789
Coefficient of variation (CV)0.70753703
Kurtosis5.3695371
Mean2.3652174
Median Absolute Deviation (MAD)1
Skewness1.9288644
Sum544
Variance2.8005316
MonotonicityNot monotonic
2023-12-12T12:49:33.864748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 87
29.1%
2 67
22.4%
3 33
 
11.0%
4 20
 
6.7%
5 8
 
2.7%
6 8
 
2.7%
7 4
 
1.3%
8 2
 
0.7%
12 1
 
0.3%
(Missing) 69
23.1%
ValueCountFrequency (%)
1 87
29.1%
2 67
22.4%
3 33
 
11.0%
4 20
 
6.7%
5 8
 
2.7%
6 8
 
2.7%
7 4
 
1.3%
8 2
 
0.7%
12 1
 
0.3%
ValueCountFrequency (%)
12 1
 
0.3%
8 2
 
0.7%
7 4
 
1.3%
6 8
 
2.7%
5 8
 
2.7%
4 20
 
6.7%
3 33
 
11.0%
2 67
22.4%
1 87
29.1%

용법
Categorical

HIGH CORRELATION 

Distinct46
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
74 
1일 1회
45 
1일 2회
42 
1일 1회
20 
1일 3회
18 
Other values (41)
100 

Length

Max length12
Median length7
Mean length5.2307692
Min length3

Unique

Unique23 ?
Unique (%)7.7%

Sample

1st row1일 1회
2nd row1일 1회
3rd row1일 1회
4th row1일 1회
5th row1일 1회

Common Values

ValueCountFrequency (%)
<NA> 74
24.7%
1일 1회 45
15.1%
1일 2회 42
14.0%
1일 1회 20
 
6.7%
1일 3회 18
 
6.0%
1일 2회 17
 
5.7%
1일 4회 10
 
3.3%
1일 3회 9
 
3.0%
1일 4회 8
 
2.7%
1일 5회 4
 
1.3%
Other values (36) 52
17.4%

Length

2023-12-12T12:49:33.995347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1일 195
37.4%
1회 82
15.7%
na 74
 
14.2%
2회 65
 
12.5%
3회 31
 
5.9%
4회 20
 
3.8%
1주 10
 
1.9%
5회 8
 
1.5%
6회 8
 
1.5%
4주 5
 
1.0%
Other values (12) 24
 
4.6%

용법1
Text

MISSING 

Distinct236
Distinct (%)84.6%
Missing20
Missing (%)6.7%
Memory size2.5 KiB
2023-12-12T12:49:34.340281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length20
Mean length10.795699
Min length3

Characters and Unicode

Total characters3012
Distinct characters190
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique209 ?
Unique (%)74.9%

Sample

1st row아침 식전30분에
2nd row점심 식전30분에
3rd row점심 식사직전에
4th row저녁 식전30분에
5th row저녁 식사직전에
ValueCountFrequency (%)
바르세요 78
 
11.0%
얇게 60
 
8.5%
의사지시대로 38
 
5.4%
넣으세요 25
 
3.5%
식전 23
 
3.3%
30분에 18
 
2.5%
눈에 15
 
2.1%
하세요 14
 
2.0%
필요시 12
 
1.7%
매 11
 
1.6%
Other values (186) 412
58.4%
2023-12-12T12:49:35.251122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
480
 
15.9%
에 220
 
7.3%
요 155
 
5.1%
세 144
 
4.8%
시 119
 
4.0%
식 84
 
2.8%
바 80
 
2.7%
르 79
 
2.6%
사 74
 
2.5%
전 72
 
2.4%
Other values (180) 1505
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2302
76.4%
Space Separator 480
 
15.9%
Decimal Number 165
 
5.5%
Other Punctuation 43
 
1.4%
Lowercase Letter 12
 
0.4%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%
Uppercase Letter 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
에 220
 
9.6%
요 155
 
6.7%
세 144
 
6.3%
시 119
 
5.2%
식 84
 
3.6%
바 80
 
3.5%
르 79
 
3.4%
사 74
 
3.2%
전 72
 
3.1%
게 60
 
2.6%
Other values (156) 1215
52.8%
Decimal Number
ValueCountFrequency (%)
3 41
24.8%
1 37
22.4%
0 35
21.2%
2 23
13.9%
4 10
 
6.1%
8 7
 
4.2%
6 5
 
3.0%
5 4
 
2.4%
7 3
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
e 3
25.0%
p 2
16.7%
o 1
 
8.3%
d 1
 
8.3%
i 1
 
8.3%
l 1
 
8.3%
a 1
 
8.3%
t 1
 
8.3%
n 1
 
8.3%
Space Separator
ValueCountFrequency (%)
480
100.0%
Other Punctuation
ValueCountFrequency (%)
, 43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
F 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2302
76.4%
Common 697
 
23.1%
Latin 13
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
에 220
 
9.6%
요 155
 
6.7%
세 144
 
6.3%
시 119
 
5.2%
식 84
 
3.6%
바 80
 
3.5%
르 79
 
3.4%
사 74
 
3.2%
전 72
 
3.1%
게 60
 
2.6%
Other values (156) 1215
52.8%
Common
ValueCountFrequency (%)
480
68.9%
, 43
 
6.2%
3 41
 
5.9%
1 37
 
5.3%
0 35
 
5.0%
2 23
 
3.3%
4 10
 
1.4%
8 7
 
1.0%
6 5
 
0.7%
5 4
 
0.6%
Other values (4) 12
 
1.7%
Latin
ValueCountFrequency (%)
e 3
23.1%
p 2
15.4%
o 1
 
7.7%
d 1
 
7.7%
i 1
 
7.7%
l 1
 
7.7%
a 1
 
7.7%
t 1
 
7.7%
n 1
 
7.7%
F 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2302
76.4%
ASCII 710
 
23.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
480
67.6%
, 43
 
6.1%
3 41
 
5.8%
1 37
 
5.2%
0 35
 
4.9%
2 23
 
3.2%
4 10
 
1.4%
8 7
 
1.0%
6 5
 
0.7%
5 4
 
0.6%
Other values (14) 25
 
3.5%
Hangul
ValueCountFrequency (%)
에 220
 
9.6%
요 155
 
6.7%
세 144
 
6.3%
시 119
 
5.2%
식 84
 
3.6%
바 80
 
3.5%
르 79
 
3.4%
사 74
 
3.2%
전 72
 
3.1%
게 60
 
2.6%
Other values (156) 1215
52.8%

용법2
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
<NA>
146 
복용하세요
96 
주사하세요
45 
관류하세요
 
8
복용 하세요
 
1
Other values (3)
 
3

Length

Max length13
Median length5
Mean length4.5384615
Min length4

Unique

Unique4 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 146
48.8%
복용하세요 96
32.1%
주사하세요 45
 
15.1%
관류하세요 8
 
2.7%
복용 하세요 1
 
0.3%
넣으세요 1
 
0.3%
연속 이틀동안 복용하세요 1
 
0.3%
넣으세요. 1
 
0.3%

Length

2023-12-12T12:49:35.494994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:49:35.644096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 146
48.3%
복용하세요 97
32.1%
주사하세요 45
 
14.9%
관류하세요 8
 
2.6%
넣으세요 2
 
0.7%
복용 1
 
0.3%
하세요 1
 
0.3%
연속 1
 
0.3%
이틀동안 1
 
0.3%

식전 식후
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
S
114 
<NA>
108 
D
14 
V
12 
R
 
7
Other values (13)
44 

Length

Max length4
Median length1
Mean length2.083612
Min length1

Unique

Unique6 ?
Unique (%)2.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
S 114
38.1%
<NA> 108
36.1%
D 14
 
4.7%
V 12
 
4.0%
R 7
 
2.3%
T 7
 
2.3%
B 6
 
2.0%
L 6
 
2.0%
A 6
 
2.0%
N 5
 
1.7%
Other values (8) 14
 
4.7%

Length

2023-12-12T12:49:35.863854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
s 114
38.1%
na 108
36.1%
d 14
 
4.7%
v 12
 
4.0%
r 7
 
2.3%
t 7
 
2.3%
b 6
 
2.0%
l 6
 
2.0%
a 6
 
2.0%
n 5
 
1.7%
Other values (8) 14
 
4.7%

아침
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
0
133 
<NA>
106 
1
60 

Length

Max length4
Median length1
Mean length2.0635452
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 133
44.5%
<NA> 106
35.5%
1 60
20.1%

Length

2023-12-12T12:49:36.027269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:49:36.208253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 133
44.5%
na 106
35.5%
1 60
20.1%

점심
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
0
151 
<NA>
113 
1
35 

Length

Max length4
Median length1
Mean length2.1337793
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 151
50.5%
<NA> 113
37.8%
1 35
 
11.7%

Length

2023-12-12T12:49:36.479935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:49:36.632818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 151
50.5%
na 113
37.8%
1 35
 
11.7%

저녁
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
0
146 
<NA>
107 
1
46 

Length

Max length4
Median length1
Mean length2.0735786
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 146
48.8%
<NA> 107
35.8%
1 46
 
15.4%

Length

2023-12-12T12:49:36.778537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:49:36.923021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 146
48.8%
na 107
35.8%
1 46
 
15.4%

자기전
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
0
157 
<NA>
122 
1
20 

Length

Max length4
Median length1
Mean length2.2240803
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 157
52.5%
<NA> 122
40.8%
1 20
 
6.7%

Length

2023-12-12T12:49:37.127809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:49:37.307869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 157
52.5%
na 122
40.8%
1 20
 
6.7%

Interactions

2023-12-12T12:49:28.805119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:28.572214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:28.923148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:49:28.680805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:49:37.415777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
투여경로기준일수투여횟수용법용법2식전 식후아침점심저녁자기전
투여경로1.0000.2020.1440.7471.0000.9810.5900.4100.4680.291
기준일수0.2021.0000.0001.0000.2300.3950.2730.0000.0000.000
투여횟수0.1440.0001.0001.0000.0000.5450.2200.4350.3310.503
용법0.7471.0001.0001.0000.5650.5190.4380.5630.3980.550
용법21.0000.2300.0000.5651.0000.4900.2710.0620.1600.000
식전 식후0.9810.3950.5450.5190.4901.0000.9940.9060.9330.815
아침0.5900.2730.2200.4380.2710.9941.0000.8070.9030.678
점심0.4100.0000.4350.5630.0620.9060.8071.0000.8800.793
저녁0.4680.0000.3310.3980.1600.9330.9030.8801.0000.738
자기전0.2910.0000.5030.5500.0000.8150.6780.7930.7381.000
2023-12-12T12:49:37.589248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용법2식전 식후투여경로점심저녁자기전용법아침
용법21.0000.2710.9870.0680.1890.0000.2600.324
식전 식후0.2711.0000.9480.7330.7660.7420.1590.896
투여경로0.9870.9481.0000.6430.7190.4690.4370.857
점심0.0680.7330.6431.0000.6850.5830.4080.598
저녁0.1890.7660.7190.6851.0000.5280.3080.717
자기전0.0000.7420.4690.5830.5281.0000.4300.474
용법0.2600.1590.4370.4080.3080.4301.0000.314
아침0.3240.8960.8570.5980.7170.4740.3141.000
2023-12-12T12:49:37.767795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일수투여횟수투여경로용법용법2식전 식후아침점심저녁자기전
기준일수1.000-0.1480.1540.9050.1570.2230.1810.0000.0000.000
투여횟수-0.1481.0000.0900.9110.0000.2550.2310.4580.3480.530
투여경로0.1540.0901.0000.4370.9870.9480.8570.6430.7190.469
용법0.9050.9110.4371.0000.2600.1590.3140.4080.3080.430
용법20.1570.0000.9870.2601.0000.2710.3240.0680.1890.000
식전 식후0.2230.2550.9480.1590.2711.0000.8960.7330.7660.742
아침0.1810.2310.8570.3140.3240.8961.0000.5980.7170.474
점심0.0000.4580.6430.4080.0680.7330.5981.0000.6850.583
저녁0.0000.3480.7190.3080.1890.7660.7170.6851.0000.528
자기전0.0000.5300.4690.4300.0000.7420.4740.5830.5281.000

Missing values

2023-12-12T12:49:29.091853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:49:29.307241image/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.
2023-12-12T12:49:29.506570image/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

용법코드투여경로약어약사약어의사기준일수투여횟수용법용법1용법2식전 식후아침점심저녁자기전
0IDA0IDAIDA111일 1회아침 식전30분에주사하세요<NA><NA><NA><NA><NA>
1IDDA0IDDAIDDA111일 1회점심 식전30분에주사하세요<NA><NA><NA><NA><NA>
2IDDP0IDDPIDDP111일 1회점심 식사직전에주사하세요<NA><NA><NA><NA><NA>
3IDEA0IDEAIDEA111일 1회저녁 식전30분에주사하세요<NA><NA><NA><NA><NA>
4IDEP0IDEPIDEP111일 1회저녁 식사직전에주사하세요<NA><NA><NA><NA><NA>
5IDP0IDPIDP111일 1회아침 식사직전에주사하세요<NA><NA><NA><NA><NA>
6IDR0IDRIDR111일 1회의사지시대로주사하세요<NA><NA><NA><NA><NA>
7IQ240IQ24IQ24111일 1회24시간마다주사하세요<NA><NA><NA><NA><NA>
8IRR10IRR1IRR1111일 1회<NA>관류하세요<NA>0000
9IBA0IBAIBA121일 2회아침,저녁 식전30분에주사하세요<NA><NA><NA><NA><NA>
용법코드투여경로약어약사약어의사기준일수투여횟수용법용법1용법2식전 식후아침점심저녁자기전
289OPT2OPTOPT<NA><NA><NA>의사지시대로 등에 바르세요<NA><NA><NA><NA><NA><NA>
290ORT2ORTORT<NA><NA><NA>의사지시대로 항문에 바르세요<NA><NA><NA><NA><NA><NA>
291OS2OSOS<NA><NA><NA>의사지시대로 머리에 바르세요<NA><NA><NA><NA><NA><NA>
292OT2OTOT<NA><NA><NA>의사지시대로 몸통에 바르세요<NA><NA><NA><NA><NA><NA>
293OU2OUOU<NA><NA><NA>양쪽눈에 넣으세요<NA><NA><NA><NA><NA><NA>
294VT22VT2VT2<NA><NA><NA>1일2회 질속에 넣으세요<NA><NA><NA><NA><NA><NA>
295W2SP2W2SPW2SP<NA><NA><NA>배,가슴 등 편편한 곳에 3일간 붙이세요<NA>S0000
296WPRN2WPRNWPRN<NA><NA><NA>필요시 샴푸하세요<NA>S0000
297XX2XXXX<NA><NA><NA>환자불출(Fee not applied)<NA><NA><NA><NA><NA><NA>
298YY2YYYY<NA><NA><NA>이미 사용된 약입니다<NA><NA><NA><NA><NA><NA>