Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells3358
Missing cells (%)4.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory712.9 KiB
Average record size in memory73.0 B

Variable types

Text4
Categorical3
Numeric1

Dataset

Description요양기관 개설 현황(요양기관명, 소재지, 종별, 개설일자 등) / 연1회 업데이트 / ※ 과거 기준 자료는 공공데이터포털에서 "공공데이터 제공신청" 하기 바람(최근 3~5개년 자료만 제공 가능)
Author건강보험심사평가원
URLhttps://www.data.go.kr/data/15051057/fileData.do

Alerts

표시과목코드 is highly overall correlated with 표시과목명High correlation
표시과목명 is highly overall correlated with 표시과목코드High correlation
표시과목코드 has 3358 (33.6%) missing valuesMissing
표시과목코드 has 1190 (11.9%) zerosZeros

Reproduction

Analysis started2023-12-13 00:44:02.475849
Analysis finished2023-12-13 00:44:03.963046
Duration1.49 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

요양기관명
Text

Distinct8286
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T09:44:04.180569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length7.202
Min length3

Characters and Unicode

Total characters72020
Distinct characters724
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7492 ?
Unique (%)74.9%

Sample

1st row한강정신건강의학과의원
2nd row엘림이비인후과의원
3rd row로즈여성의원
4th row최시영정신건강의학과의원
5th row하나약국
ValueCountFrequency (%)
약국 46
 
0.4%
의료법인 41
 
0.4%
치과의원 20
 
0.2%
우리약국 16
 
0.2%
의원 16
 
0.2%
중앙약국 16
 
0.2%
하나약국 15
 
0.1%
희망약국 14
 
0.1%
서울치과의원 14
 
0.1%
이사랑치과의원 14
 
0.1%
Other values (8449) 10191
98.0%
2023-12-13T09:44:04.577478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
의 7210
 
10.0%
원 7109
 
9.9%
과 5285
 
7.3%
국 2783
 
3.9%
약 2749
 
3.8%
치 2237
 
3.1%
이 1153
 
1.6%
소 1109
 
1.5%
정 1004
 
1.4%
한 915
 
1.3%
Other values (714) 40466
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70983
98.6%
Space Separator 404
 
0.6%
Decimal Number 284
 
0.4%
Uppercase Letter 120
 
0.2%
Close Punctuation 69
 
0.1%
Open Punctuation 67
 
0.1%
Lowercase Letter 54
 
0.1%
Other Punctuation 26
 
< 0.1%
Dash Punctuation 12
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 7210
 
10.2%
원 7109
 
10.0%
과 5285
 
7.4%
국 2783
 
3.9%
약 2749
 
3.9%
치 2237
 
3.2%
이 1153
 
1.6%
소 1109
 
1.6%
정 1004
 
1.4%
한 915
 
1.3%
Other values (662) 39429
55.5%
Uppercase Letter
ValueCountFrequency (%)
S 15
12.5%
K 11
 
9.2%
C 9
 
7.5%
M 9
 
7.5%
W 8
 
6.7%
N 8
 
6.7%
O 7
 
5.8%
H 6
 
5.0%
J 6
 
5.0%
R 5
 
4.2%
Other values (12) 36
30.0%
Lowercase Letter
ValueCountFrequency (%)
e 33
61.1%
i 5
 
9.3%
n 4
 
7.4%
h 3
 
5.6%
t 2
 
3.7%
c 2
 
3.7%
r 1
 
1.9%
s 1
 
1.9%
w 1
 
1.9%
l 1
 
1.9%
Decimal Number
ValueCountFrequency (%)
3 69
24.3%
5 67
23.6%
6 63
22.2%
2 26
 
9.2%
1 26
 
9.2%
0 14
 
4.9%
8 9
 
3.2%
4 5
 
1.8%
7 5
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 12
46.2%
& 6
23.1%
, 5
19.2%
· 2
 
7.7%
＆ 1
 
3.8%
Space Separator
ValueCountFrequency (%)
404
100.0%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 67
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70978
98.6%
Common 863
 
1.2%
Latin 174
 
0.2%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 7210
 
10.2%
원 7109
 
10.0%
과 5285
 
7.4%
국 2783
 
3.9%
약 2749
 
3.9%
치 2237
 
3.2%
이 1153
 
1.6%
소 1109
 
1.6%
정 1004
 
1.4%
한 915
 
1.3%
Other values (657) 39424
55.5%
Latin
ValueCountFrequency (%)
e 33
19.0%
S 15
 
8.6%
K 11
 
6.3%
C 9
 
5.2%
M 9
 
5.2%
W 8
 
4.6%
N 8
 
4.6%
O 7
 
4.0%
H 6
 
3.4%
J 6
 
3.4%
Other values (23) 62
35.6%
Common
ValueCountFrequency (%)
404
46.8%
) 69
 
8.0%
3 69
 
8.0%
5 67
 
7.8%
( 67
 
7.8%
6 63
 
7.3%
2 26
 
3.0%
1 26
 
3.0%
0 14
 
1.6%
- 12
 
1.4%
Other values (9) 46
 
5.3%
Han
ValueCountFrequency (%)
韓 1
20.0%
美 1
20.0%
人 1
20.0%
林 1
20.0%
天 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70978
98.6%
ASCII 1033
 
1.4%
CJK 5
 
< 0.1%
None 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
의 7210
 
10.2%
원 7109
 
10.0%
과 5285
 
7.4%
국 2783
 
3.9%
약 2749
 
3.9%
치 2237
 
3.2%
이 1153
 
1.6%
소 1109
 
1.6%
정 1004
 
1.4%
한 915
 
1.3%
Other values (657) 39424
55.5%
ASCII
ValueCountFrequency (%)
404
39.1%
) 69
 
6.7%
3 69
 
6.7%
5 67
 
6.5%
( 67
 
6.5%
6 63
 
6.1%
e 33
 
3.2%
2 26
 
2.5%
1 26
 
2.5%
S 15
 
1.5%
Other values (39) 194
18.8%
None
ValueCountFrequency (%)
· 2
50.0%
＆ 1
25.0%
´ 1
25.0%
CJK
ValueCountFrequency (%)
韓 1
20.0%
美 1
20.0%
人 1
20.0%
林 1
20.0%
天 1
20.0%

요양종별
Categorical

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
의원
3986 
약국
2730 
치과의원
2117 
한의원
 
302
보건진료소
 
212
Other values (11)
653 

Length

Max length6
Median length2
Mean length2.6148
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row의원
2nd row의원
3rd row의원
4th row의원
5th row약국

Common Values

ValueCountFrequency (%)
의원 3986
39.9%
약국 2730
27.3%
치과의원 2117
21.2%
한의원 302
 
3.0%
보건진료소 212
 
2.1%
보건지소 161
 
1.6%
병원 161
 
1.6%
요양병원 155
 
1.6%
한방병원 55
 
0.5%
정신병원 32
 
0.3%
Other values (6) 89
 
0.9%

Length

2023-12-13T09:44:04.697048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
의원 3986
39.9%
약국 2730
27.3%
치과의원 2117
21.2%
한의원 302
 
3.0%
보건진료소 212
 
2.1%
보건지소 161
 
1.6%
병원 161
 
1.6%
요양병원 155
 
1.6%
한방병원 55
 
0.5%
정신병원 32
 
0.3%
Other values (6) 89
 
0.9%

시도명
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
서울특별시
2649 
경기도
2117 
부산광역시
652 
대구광역시
547 
경상남도
524 
Other values (12)
3511 

Length

Max length7
Median length5
Mean length4.3263
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도
2nd row서울특별시
3rd row서울특별시
4th row경기도
5th row강원도

Common Values

ValueCountFrequency (%)
서울특별시 2649
26.5%
경기도 2117
21.2%
부산광역시 652
 
6.5%
대구광역시 547
 
5.5%
경상남도 524
 
5.2%
인천광역시 472
 
4.7%
경상북도 464
 
4.6%
전라북도 377
 
3.8%
충청남도 361
 
3.6%
전라남도 328
 
3.3%
Other values (7) 1509
15.1%

Length

2023-12-13T09:44:04.806814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 2649
26.5%
경기도 2117
21.2%
부산광역시 652
 
6.5%
대구광역시 547
 
5.5%
경상남도 524
 
5.2%
인천광역시 472
 
4.7%
경상북도 464
 
4.6%
전라북도 377
 
3.8%
충청남도 361
 
3.6%
전라남도 328
 
3.3%
Other values (7) 1509
15.1%

시군구명
Text

Distinct228
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T09:44:05.042950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.5837
Min length2

Characters and Unicode

Total characters35837
Distinct characters143
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row김포시
2nd row동작구
3rd row강남구
4th row군포시
5th row강릉시
ValueCountFrequency (%)
강남구 331
 
2.9%
서구 331
 
2.9%
중구 300
 
2.6%
북구 277
 
2.4%
남구 237
 
2.0%
성남시 211
 
1.8%
동구 210
 
1.8%
서초구 182
 
1.6%
송파구 179
 
1.5%
수원시 174
 
1.5%
Other values (227) 9131
79.0%
2023-12-13T09:44:05.388392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 6747
18.8%
시 4284
 
12.0%
1563
 
4.4%
남 1112
 
3.1%
서 1084
 
3.0%
산 991
 
2.8%
동 965
 
2.7%
주 939
 
2.6%
군 911
 
2.5%
성 854
 
2.4%
Other values (133) 16387
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34274
95.6%
Space Separator 1563
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 6747
19.7%
시 4284
 
12.5%
남 1112
 
3.2%
서 1084
 
3.2%
산 991
 
2.9%
동 965
 
2.8%
주 939
 
2.7%
군 911
 
2.7%
성 854
 
2.5%
양 787
 
2.3%
Other values (132) 15600
45.5%
Space Separator
ValueCountFrequency (%)
1563
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34274
95.6%
Common 1563
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 6747
19.7%
시 4284
 
12.5%
남 1112
 
3.2%
서 1084
 
3.2%
산 991
 
2.9%
동 965
 
2.8%
주 939
 
2.7%
군 911
 
2.7%
성 854
 
2.5%
양 787
 
2.3%
Other values (132) 15600
45.5%
Common
ValueCountFrequency (%)
1563
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34274
95.6%
ASCII 1563
 
4.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 6747
19.7%
시 4284
 
12.5%
남 1112
 
3.2%
서 1084
 
3.2%
산 991
 
2.9%
동 965
 
2.8%
주 939
 
2.7%
군 911
 
2.7%
성 854
 
2.5%
양 787
 
2.3%
Other values (132) 15600
45.5%
ASCII
ValueCountFrequency (%)
1563
100.0%

도로명주소
Text

Distinct9905
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T09:44:05.655864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length61
Mean length30.8531
Min length14

Characters and Unicode

Total characters308531
Distinct characters721
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9811 ?
Unique (%)98.1%

Sample

1st row경기도 김포시 김포한강4로 113, 304호 (장기동)
2nd row서울특별시 동작구 여의대방로 142, 보라매빌딩 5층 (대방동)
3rd row서울특별시 강남구 논현로115길 72, 2,3층 (논현동)
4th row경기도 군포시 고산로 693, 402호 (산본동, 하나로프라자)
5th row강원도 강릉시 강릉대로 163 (교동)
ValueCountFrequency (%)
서울특별시 2649
 
4.1%
경기도 2117
 
3.3%
2층 1172
 
1.8%
1층 778
 
1.2%
3층 763
 
1.2%
부산광역시 652
 
1.0%
대구광역시 547
 
0.9%
경상남도 524
 
0.8%
4층 474
 
0.7%
인천광역시 472
 
0.7%
Other values (12886) 53760
84.1%
2023-12-13T09:44:06.073772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
53970
 
17.5%
동 10964
 
3.6%
1 9957
 
3.2%
, 9874
 
3.2%
시 9788
 
3.2%
로 9767
 
3.2%
) 8910
 
2.9%
( 8909
 
2.9%
구 7839
 
2.5%
2 7571
 
2.5%
Other values (711) 170982
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 176503
57.2%
Space Separator 53970
 
17.5%
Decimal Number 47847
 
15.5%
Other Punctuation 9971
 
3.2%
Close Punctuation 8910
 
2.9%
Open Punctuation 8909
 
2.9%
Dash Punctuation 1168
 
0.4%
Uppercase Letter 774
 
0.3%
Math Symbol 351
 
0.1%
Lowercase Letter 121
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 10964
 
6.2%
시 9788
 
5.5%
로 9767
 
5.5%
구 7839
 
4.4%
도 5562
 
3.2%
층 4651
 
2.6%
서 4609
 
2.6%
경 3526
 
2.0%
대 3505
 
2.0%
호 3431
 
1.9%
Other values (638) 112861
63.9%
Uppercase Letter
ValueCountFrequency (%)
B 117
15.1%
A 93
 
12.0%
S 54
 
7.0%
C 51
 
6.6%
E 45
 
5.8%
M 42
 
5.4%
T 37
 
4.8%
K 34
 
4.4%
R 33
 
4.3%
I 32
 
4.1%
Other values (16) 236
30.5%
Lowercase Letter
ValueCountFrequency (%)
e 25
20.7%
i 11
 
9.1%
l 8
 
6.6%
t 8
 
6.6%
s 7
 
5.8%
r 7
 
5.8%
a 6
 
5.0%
n 6
 
5.0%
o 6
 
5.0%
w 5
 
4.1%
Other values (11) 32
26.4%
Decimal Number
ValueCountFrequency (%)
1 9957
20.8%
2 7571
15.8%
3 6135
12.8%
0 5613
11.7%
4 4429
9.3%
5 3687
 
7.7%
6 3111
 
6.5%
7 2721
 
5.7%
8 2395
 
5.0%
9 2228
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 9874
99.0%
. 61
 
0.6%
· 21
 
0.2%
/ 7
 
0.1%
@ 4
 
< 0.1%
' 2
 
< 0.1%
& 2
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 4
57.1%
Ⅲ 2
28.6%
Ⅰ 1
 
14.3%
Math Symbol
ValueCountFrequency (%)
~ 349
99.4%
+ 2
 
0.6%
Space Separator
ValueCountFrequency (%)
53970
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8910
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8909
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1168
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 176503
57.2%
Common 131126
42.5%
Latin 902
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 10964
 
6.2%
시 9788
 
5.5%
로 9767
 
5.5%
구 7839
 
4.4%
도 5562
 
3.2%
층 4651
 
2.6%
서 4609
 
2.6%
경 3526
 
2.0%
대 3505
 
2.0%
호 3431
 
1.9%
Other values (638) 112861
63.9%
Latin
ValueCountFrequency (%)
B 117
 
13.0%
A 93
 
10.3%
S 54
 
6.0%
C 51
 
5.7%
E 45
 
5.0%
M 42
 
4.7%
T 37
 
4.1%
K 34
 
3.8%
R 33
 
3.7%
I 32
 
3.5%
Other values (40) 364
40.4%
Common
ValueCountFrequency (%)
53970
41.2%
1 9957
 
7.6%
, 9874
 
7.5%
) 8910
 
6.8%
( 8909
 
6.8%
2 7571
 
5.8%
3 6135
 
4.7%
0 5613
 
4.3%
4 4429
 
3.4%
5 3687
 
2.8%
Other values (13) 12071
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 176503
57.2%
ASCII 132000
42.8%
None 21
 
< 0.1%
Number Forms 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
53970
40.9%
1 9957
 
7.5%
, 9874
 
7.5%
) 8910
 
6.8%
( 8909
 
6.7%
2 7571
 
5.7%
3 6135
 
4.6%
0 5613
 
4.3%
4 4429
 
3.4%
5 3687
 
2.8%
Other values (59) 12945
 
9.8%
Hangul
ValueCountFrequency (%)
동 10964
 
6.2%
시 9788
 
5.5%
로 9767
 
5.5%
구 7839
 
4.4%
도 5562
 
3.2%
층 4651
 
2.6%
서 4609
 
2.6%
경 3526
 
2.0%
대 3505
 
2.0%
호 3431
 
1.9%
Other values (638) 112861
63.9%
None
ValueCountFrequency (%)
· 21
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 4
57.1%
Ⅲ 2
28.6%
Ⅰ 1
 
14.3%

표시과목코드
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct23
Distinct (%)0.3%
Missing3358
Missing (%)33.6%
Infinite0
Infinite (%)0.0%
Mean14.007678
Minimum0
Maximum28
Zeros1190
Zeros (%)11.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T09:44:06.171052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median13
Q327
95-th percentile28
Maximum28
Range28
Interquartile range (IQR)26

Descriptive statistics

Standard deviation11.356767
Coefficient of variation (CV)0.81075296
Kurtosis-1.6861002
Mean14.007678
Median Absolute Deviation (MAD)13
Skewness0.051218383
Sum93039
Variance128.97615
MonotonicityNot monotonic
2023-12-13T09:44:06.254121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
27 2138
21.4%
0 1190
 
11.9%
1 596
 
6.0%
28 357
 
3.6%
13 321
 
3.2%
5 280
 
2.8%
11 245
 
2.5%
12 182
 
1.8%
14 180
 
1.8%
3 162
 
1.6%
Other values (13) 991
 
9.9%
(Missing) 3358
33.6%
ValueCountFrequency (%)
0 1190
11.9%
1 596
6.0%
2 33
 
0.3%
3 162
 
1.6%
4 117
 
1.2%
5 280
 
2.8%
6 67
 
0.7%
7 7
 
0.1%
8 145
 
1.5%
9 140
 
1.4%
ValueCountFrequency (%)
28 357
 
3.6%
27 2138
21.4%
23 126
 
1.3%
21 61
 
0.6%
20 1
 
< 0.1%
18 2
 
< 0.1%
16 18
 
0.2%
15 119
 
1.2%
14 180
 
1.8%
13 321
 
3.2%

표시과목명
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
해당사항없음
3358 
치과
2138 
일반의
1190 
내과
596 
한방
357 
Other values (19)
2361 

Length

Max length12
Median length8
Mean length4.0725
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row정신건강의학과
2nd row이비인후과
3rd row일반의
4th row정신건강의학과
5th row해당사항없음

Common Values

ValueCountFrequency (%)
해당사항없음 3358
33.6%
치과 2138
21.4%
일반의 1190
 
11.9%
내과 596
 
6.0%
한방 357
 
3.6%
이비인후과 321
 
3.2%
정형외과 280
 
2.8%
소아청소년과 245
 
2.5%
안과 182
 
1.8%
피부과 180
 
1.8%
Other values (14) 1153
 
11.5%

Length

2023-12-13T09:44:06.348258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
해당사항없음 3358
33.6%
치과 2138
21.4%
일반의 1190
 
11.9%
내과 596
 
6.0%
한방 357
 
3.6%
이비인후과 321
 
3.2%
정형외과 280
 
2.8%
소아청소년과 245
 
2.5%
안과 182
 
1.8%
피부과 180
 
1.8%
Other values (14) 1153
 
11.5%

개설일자
Text

Distinct5881
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T09:44:06.552573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters100000
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3469 ?
Unique (%)34.7%

Sample

1st row2013-03-18
2nd row2019-08-14
3rd row2008-10-28
4th row1998-02-26
5th row2019-06-18
ValueCountFrequency (%)
1988-01-01 22
 
0.2%
2015-02-02 10
 
0.1%
2017-03-20 9
 
0.1%
2011-01-03 9
 
0.1%
2012-03-02 8
 
0.1%
2018-04-02 8
 
0.1%
1986-07-01 8
 
0.1%
2017-01-02 8
 
0.1%
2019-02-28 8
 
0.1%
2016-04-18 8
 
0.1%
Other values (5871) 9902
99.0%
2023-12-13T09:44:06.839330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 24288
24.3%
- 20000
20.0%
2 16072
16.1%
1 15452
15.5%
9 6294
 
6.3%
8 3471
 
3.5%
3 3266
 
3.3%
7 2853
 
2.9%
4 2840
 
2.8%
5 2750
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80000
80.0%
Dash Punctuation 20000
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24288
30.4%
2 16072
20.1%
1 15452
19.3%
9 6294
 
7.9%
8 3471
 
4.3%
3 3266
 
4.1%
7 2853
 
3.6%
4 2840
 
3.5%
5 2750
 
3.4%
6 2714
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 20000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 100000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 24288
24.3%
- 20000
20.0%
2 16072
16.1%
1 15452
15.5%
9 6294
 
6.3%
8 3471
 
3.5%
3 3266
 
3.3%
7 2853
 
2.9%
4 2840
 
2.8%
5 2750
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24288
24.3%
- 20000
20.0%
2 16072
16.1%
1 15452
15.5%
9 6294
 
6.3%
8 3471
 
3.5%
3 3266
 
3.3%
7 2853
 
2.9%
4 2840
 
2.8%
5 2750
 
2.8%

Interactions

2023-12-13T09:44:03.700537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:44:06.935107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
요양종별시도명표시과목코드표시과목명
요양종별1.0000.3130.6920.868
시도명0.3131.0000.1110.255
표시과목코드0.6920.1111.0001.000
표시과목명0.8680.2551.0001.000
2023-12-13T09:44:07.002454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표시과목명요양종별시도명
표시과목명1.0000.4520.077
요양종별0.4521.0000.105
시도명0.0770.1051.000
2023-12-13T09:44:07.069362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표시과목코드요양종별시도명표시과목명
표시과목코드1.0000.4560.0450.999
요양종별0.4561.0000.1050.452
시도명0.0450.1051.0000.077
표시과목명0.9990.4520.0771.000

Missing values

2023-12-13T09:44:03.802256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:44:03.912412image/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

요양기관명요양종별시도명시군구명도로명주소표시과목코드표시과목명개설일자
29066한강정신건강의학과의원의원경기도김포시경기도 김포시 김포한강4로 113, 304호 (장기동)3정신건강의학과2013-03-18
8847엘림이비인후과의원의원서울특별시동작구서울특별시 동작구 여의대방로 142, 보라매빌딩 5층 (대방동)13이비인후과2019-08-14
10528로즈여성의원의원서울특별시강남구서울특별시 강남구 논현로115길 72, 2,3층 (논현동)0일반의2008-10-28
27633최시영정신건강의학과의원의원경기도군포시경기도 군포시 고산로 693, 402호 (산본동, 하나로프라자)3정신건강의학과1998-02-26
78710하나약국약국강원도강릉시강원도 강릉시 강릉대로 163 (교동)<NA>해당사항없음2019-06-18
62640방학세계로약국약국서울특별시도봉구서울특별시 도봉구 방학로 159 (방학동)<NA>해당사항없음2006-03-03
15956제일내과의원의원대구광역시동구대구광역시 동구 아양로50길 114 (효목동)1내과2000-08-07
44883조은치과의원치과의원부산광역시기장군부산광역시 기장군 정관읍 정관로 579, 10층27치과2014-03-03
78432행복한 정약국약국강원도춘천시강원도 춘천시 영서로2141번길 13 (퇴계동)<NA>해당사항없음2017-03-06
62771동산약국약국서울특별시노원구서울특별시 노원구 동일로 1280, 1층 109호,110호 (중계동, 무지개아파트단지내상가)<NA>해당사항없음2004-02-03
요양기관명요양종별시도명시군구명도로명주소표시과목코드표시과목명개설일자
84882한솔약국약국경상남도남해군경상남도 남해군 남해읍 화전로 103, 주원빌딩<NA>해당사항없음2016-12-23
27020우리중앙의원의원경기도남양주시경기도 남양주시 오남읍 진건오남로522번길 5, 3층0일반의2004-12-27
14797돌고래마취통증의학과의원의원부산광역시금정구부산광역시 금정구 중앙대로 1941, 태일빌딩 4층 (구서동)9마취통증의학과2018-11-30
19432압구정앤성형외과의원의원광주광역시서구광주광역시 서구 상무중앙로 9, 7층 701호 (치평동, 동양빌딩)8성형외과2008-11-01
66763기쁨약국약국부산광역시부산진구부산광역시 부산진구 동평로 201 (부암동)<NA>해당사항없음2019-04-10
21182김주병제통의원의원대전광역시대덕구대전광역시 대덕구 신탄진로 777, 1층 (신탄진동)0일반의1986-06-21
75754우리봄약국약국경기도고양시 일산서구경기도 고양시 일산서구 하이파크3로78번길 1, 107호 (덕이동, 리더스프라자)<NA>해당사항없음2013-04-23
86769수한의원한의원서울특별시강북구서울특별시 강북구 인수봉로 289, 1층 (수유동)28한방2010-04-29
14221화명의원의원부산광역시북구부산광역시 북구 금곡대로 287, 402호 (화명동, 삼한골든뷰)0일반의2001-03-08
28599유성재내과의원의원경기도파주시경기도 파주시 금빛로 24-27 (금촌동, 제일메디칼빌딩 402호)1내과2005-01-29