Overview

Dataset statistics

Number of variables12
Number of observations1437
Missing cells103
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory139.1 KiB
Average record size in memory99.1 B

Variable types

Categorical4
Text5
Numeric3

Dataset

Description산재보험 지정 의료기관 현황
Author근로복지공단
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=RDSRAHFRGEQ40VTLAAC828503679&infSeq=1

Alerts

시군명 is highly overall correlated with 우편번호 and 3 other fieldsHigh correlation
관할지사 is highly overall correlated with 우편번호 and 3 other fieldsHigh correlation
우편번호 is highly overall correlated with WGS84위도 and 2 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 우편번호 and 2 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
진폐의료기관구분 is highly imbalanced (99.2%)Imbalance
재활인증기관구분 is highly imbalanced (84.2%)Imbalance
도로명주소 has 23 (1.6%) missing valuesMissing
팩스번호 has 42 (2.9%) missing valuesMissing

Reproduction

Analysis started2023-12-10 22:32:21.789608
Analysis finished2023-12-10 22:32:24.364426
Duration2.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size11.4 KiB
수원시
140 
성남시
114 
부천시
111 
안산시
98 
고양시
 
86
Other values (26)
888 

Length

Max length4
Median length3
Mean length3.1009047
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row화성시
2nd row의정부시
3rd row의정부시
4th row남양주시
5th row안양시

Common Values

ValueCountFrequency (%)
수원시 140
 
9.7%
성남시 114
 
7.9%
부천시 111
 
7.7%
안산시 98
 
6.8%
고양시 86
 
6.0%
용인시 83
 
5.8%
남양주시 70
 
4.9%
시흥시 69
 
4.8%
화성시 69
 
4.8%
평택시 63
 
4.4%
Other values (21) 534
37.2%

Length

2023-12-11T07:32:24.417629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 140
 
9.7%
성남시 114
 
7.9%
부천시 111
 
7.7%
안산시 98
 
6.8%
고양시 86
 
6.0%
용인시 83
 
5.8%
남양주시 70
 
4.9%
시흥시 69
 
4.8%
화성시 69
 
4.8%
평택시 63
 
4.4%
Other values (21) 534
37.2%

기관명
Text

Distinct1370
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size11.4 KiB
2023-12-11T07:32:24.587549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length7.8983994
Min length3

Characters and Unicode

Total characters11350
Distinct characters444
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1329 ?
Unique (%)92.5%

Sample

1st row삼성정형외과의원
2nd row진의원
3rd row참서울의원
4th row다산한의원
5th row본병원
ValueCountFrequency (%)
의료법인 22
 
1.4%
바른정형외과의원 6
 
0.4%
한의원 6
 
0.4%
현대정형외과의원 6
 
0.4%
연세정형외과의원 5
 
0.3%
정형외과 5
 
0.3%
서울정형외과의원 5
 
0.3%
삼성정형외과의원 5
 
0.3%
서울의원 4
 
0.3%
거북이한의원 4
 
0.3%
Other values (1451) 1506
95.7%
2023-12-11T07:32:24.905388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 1363
 
12.0%
의 1015
 
8.9%
과 564
 
5.0%
병 539
 
4.7%
한 434
 
3.8%
외 406
 
3.6%
정 383
 
3.4%
형 339
 
3.0%
료 178
 
1.6%
양 174
 
1.5%
Other values (434) 5955
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10992
96.8%
Space Separator 138
 
1.2%
Decimal Number 82
 
0.7%
Open Punctuation 52
 
0.5%
Close Punctuation 52
 
0.5%
Uppercase Letter 27
 
0.2%
Other Punctuation 5
 
< 0.1%
Dash Punctuation 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 1363
 
12.4%
의 1015
 
9.2%
과 564
 
5.1%
병 539
 
4.9%
한 434
 
3.9%
외 406
 
3.7%
정 383
 
3.5%
형 339
 
3.1%
료 178
 
1.6%
양 174
 
1.6%
Other values (400) 5597
50.9%
Uppercase Letter
ValueCountFrequency (%)
S 7
25.9%
C 3
11.1%
R 3
11.1%
U 2
 
7.4%
J 2
 
7.4%
K 2
 
7.4%
W 2
 
7.4%
E 1
 
3.7%
O 1
 
3.7%
Y 1
 
3.7%
Other values (3) 3
11.1%
Decimal Number
ValueCountFrequency (%)
2 17
20.7%
1 16
19.5%
5 14
17.1%
3 14
17.1%
6 13
15.9%
0 4
 
4.9%
8 3
 
3.7%
4 1
 
1.2%
Open Punctuation
ValueCountFrequency (%)
( 49
94.2%
（ 2
 
3.8%
[ 1
 
1.9%
Close Punctuation
ValueCountFrequency (%)
) 49
94.2%
） 2
 
3.8%
] 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 2
40.0%
. 2
40.0%
: 1
20.0%
Space Separator
ValueCountFrequency (%)
137
99.3%
　 1
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10992
96.8%
Common 330
 
2.9%
Latin 28
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 1363
 
12.4%
의 1015
 
9.2%
과 564
 
5.1%
병 539
 
4.9%
한 434
 
3.9%
외 406
 
3.7%
정 383
 
3.5%
형 339
 
3.1%
료 178
 
1.6%
양 174
 
1.6%
Other values (400) 5597
50.9%
Common
ValueCountFrequency (%)
137
41.5%
( 49
 
14.8%
) 49
 
14.8%
2 17
 
5.2%
1 16
 
4.8%
5 14
 
4.2%
3 14
 
4.2%
6 13
 
3.9%
0 4
 
1.2%
8 3
 
0.9%
Other values (10) 14
 
4.2%
Latin
ValueCountFrequency (%)
S 7
25.0%
C 3
10.7%
R 3
10.7%
U 2
 
7.1%
J 2
 
7.1%
K 2
 
7.1%
W 2
 
7.1%
E 1
 
3.6%
e 1
 
3.6%
O 1
 
3.6%
Other values (4) 4
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10992
96.8%
ASCII 353
 
3.1%
None 5
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 1363
 
12.4%
의 1015
 
9.2%
과 564
 
5.1%
병 539
 
4.9%
한 434
 
3.9%
외 406
 
3.7%
정 383
 
3.5%
형 339
 
3.1%
료 178
 
1.6%
양 174
 
1.6%
Other values (400) 5597
50.9%
ASCII
ValueCountFrequency (%)
137
38.8%
( 49
 
13.9%
) 49
 
13.9%
2 17
 
4.8%
1 16
 
4.5%
5 14
 
4.0%
3 14
 
4.0%
6 13
 
3.7%
S 7
 
2.0%
0 4
 
1.1%
Other values (21) 33
 
9.3%
None
ValueCountFrequency (%)
） 2
40.0%
（ 2
40.0%
　 1
20.0%

관할지사
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size11.4 KiB
성남지사
184 
안산지사
167 
부천지사
164 
수원지사
141 
고양지사
130 
Other values (7)
651 

Length

Max length5
Median length4
Mean length4.1607516
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row화성지사
2nd row의정부지사
3rd row의정부지사
4th row남양주지사
5th row안양지사

Common Values

ValueCountFrequency (%)
성남지사 184
12.8%
안산지사 167
11.6%
부천지사 164
11.4%
수원지사 141
9.8%
고양지사 130
9.0%
안양지사 125
8.7%
용인지사 121
8.4%
의정부지사 118
8.2%
남양주지사 113
7.9%
평택지사 100
7.0%
Other values (2) 74
5.1%

Length

2023-12-11T07:32:25.016322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성남지사 184
12.8%
안산지사 167
11.6%
부천지사 164
11.4%
수원지사 141
9.8%
고양지사 130
9.0%
안양지사 125
8.7%
용인지사 121
8.4%
의정부지사 118
8.2%
남양주지사 113
7.9%
평택지사 100
7.0%
Other values (2) 74
5.1%

도로명주소
Text

MISSING 

Distinct1345
Distinct (%)95.1%
Missing23
Missing (%)1.6%
Memory size11.4 KiB
2023-12-11T07:32:25.279503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length18.382603
Min length13

Characters and Unicode

Total characters25993
Distinct characters286
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1279 ?
Unique (%)90.5%

Sample

1st row경기도 화성시 봉담읍 삼천병마로 1316
2nd row경기도 의정부시 청사로 37
3rd row경기도 의정부시 금신로 368
4th row경기도 남양주시 늘을2로14번길 5
5th row경기도 안양시 만안구 안양로314번길 15
ValueCountFrequency (%)
경기도 1414
 
22.1%
수원시 140
 
2.2%
성남시 114
 
1.8%
부천시 110
 
1.7%
안산시 96
 
1.5%
용인시 81
 
1.3%
고양시 81
 
1.3%
화성시 69
 
1.1%
시흥시 68
 
1.1%
남양주시 67
 
1.0%
Other values (1455) 4171
65.1%
2023-12-11T07:32:25.677508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4997
19.2%
시 1501
 
5.8%
경 1493
 
5.7%
기 1464
 
5.6%
도 1442
 
5.5%
로 1364
 
5.2%
1 889
 
3.4%
2 641
 
2.5%
구 630
 
2.4%
3 496
 
1.9%
Other values (276) 11076
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16406
63.1%
Space Separator 4997
 
19.2%
Decimal Number 4457
 
17.1%
Dash Punctuation 131
 
0.5%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1501
 
9.1%
경 1493
 
9.1%
기 1464
 
8.9%
도 1442
 
8.8%
로 1364
 
8.3%
구 630
 
3.8%
안 328
 
2.0%
양 326
 
2.0%
남 310
 
1.9%
길 301
 
1.8%
Other values (263) 7247
44.2%
Decimal Number
ValueCountFrequency (%)
1 889
19.9%
2 641
14.4%
3 496
11.1%
4 406
9.1%
5 401
9.0%
6 356
8.0%
7 335
 
7.5%
0 322
 
7.2%
8 312
 
7.0%
9 299
 
6.7%
Space Separator
ValueCountFrequency (%)
4997
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 131
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16406
63.1%
Common 9587
36.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1501
 
9.1%
경 1493
 
9.1%
기 1464
 
8.9%
도 1442
 
8.8%
로 1364
 
8.3%
구 630
 
3.8%
안 328
 
2.0%
양 326
 
2.0%
남 310
 
1.9%
길 301
 
1.8%
Other values (263) 7247
44.2%
Common
ValueCountFrequency (%)
4997
52.1%
1 889
 
9.3%
2 641
 
6.7%
3 496
 
5.2%
4 406
 
4.2%
5 401
 
4.2%
6 356
 
3.7%
7 335
 
3.5%
0 322
 
3.4%
8 312
 
3.3%
Other values (3) 432
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16406
63.1%
ASCII 9587
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4997
52.1%
1 889
 
9.3%
2 641
 
6.7%
3 496
 
5.2%
4 406
 
4.2%
5 401
 
4.2%
6 356
 
3.7%
7 335
 
3.5%
0 322
 
3.4%
8 312
 
3.3%
Other values (3) 432
 
4.5%
Hangul
ValueCountFrequency (%)
시 1501
 
9.1%
경 1493
 
9.1%
기 1464
 
8.9%
도 1442
 
8.8%
로 1364
 
8.3%
구 630
 
3.8%
안 328
 
2.0%
양 326
 
2.0%
남 310
 
1.9%
길 301
 
1.8%
Other values (263) 7247
44.2%

지번주소
Text

Distinct1429
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size11.4 KiB
2023-12-11T07:32:25.979877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length50
Mean length28.031315
Min length15

Characters and Unicode

Total characters40281
Distinct characters459
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1421 ?
Unique (%)98.9%

Sample

1st row경기도 화성시 봉담읍 동화리 424-3번지 삼성정형외과의원 (서울의원)
2nd row경기도 의정부시 금오동 473-3번지 신세계프라자 501호
3rd row경기도 의정부시 금오동 463-2번지
4th row경기도 남양주시 호평동 641-1번지 샤르망메디칼프라자 12층
5th row경기도 안양시 만안구 안양동 668-35번지 1,3-8층
ValueCountFrequency (%)
경기도 1434
 
17.2%
수원시 141
 
1.7%
2층 128
 
1.5%
성남시 114
 
1.4%
3층 113
 
1.4%
부천시 112
 
1.3%
안산시 98
 
1.2%
고양시 86
 
1.0%
용인시 83
 
1.0%
남양주시 70
 
0.8%
Other values (2833) 5976
71.5%
2023-12-11T07:32:26.517303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6919
 
17.2%
지 1523
 
3.8%
시 1514
 
3.8%
1 1494
 
3.7%
기 1488
 
3.7%
도 1475
 
3.7%
경 1463
 
3.6%
동 1426
 
3.5%
번 1415
 
3.5%
2 1145
 
2.8%
Other values (449) 20419
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23238
57.7%
Decimal Number 8326
 
20.7%
Space Separator 6919
 
17.2%
Dash Punctuation 1132
 
2.8%
Other Punctuation 317
 
0.8%
Uppercase Letter 177
 
0.4%
Math Symbol 90
 
0.2%
Open Punctuation 28
 
0.1%
Close Punctuation 28
 
0.1%
Lowercase Letter 25
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 1523
 
6.6%
시 1514
 
6.5%
기 1488
 
6.4%
도 1475
 
6.3%
경 1463
 
6.3%
동 1426
 
6.1%
번 1415
 
6.1%
구 643
 
2.8%
층 612
 
2.6%
원 448
 
1.9%
Other values (389) 11231
48.3%
Uppercase Letter
ValueCountFrequency (%)
B 22
12.4%
A 19
 
10.7%
C 15
 
8.5%
S 13
 
7.3%
L 12
 
6.8%
T 11
 
6.2%
I 10
 
5.6%
Y 9
 
5.1%
G 7
 
4.0%
E 7
 
4.0%
Other values (14) 52
29.4%
Lowercase Letter
ValueCountFrequency (%)
e 5
20.0%
n 3
12.0%
r 3
12.0%
c 2
 
8.0%
s 1
 
4.0%
m 1
 
4.0%
i 1
 
4.0%
k 1
 
4.0%
a 1
 
4.0%
p 1
 
4.0%
Other values (6) 6
24.0%
Decimal Number
ValueCountFrequency (%)
1 1494
17.9%
2 1145
13.8%
3 1050
12.6%
4 879
10.6%
0 867
10.4%
5 784
9.4%
6 609
7.3%
7 573
 
6.9%
8 476
 
5.7%
9 449
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 309
97.5%
. 6
 
1.9%
/ 1
 
0.3%
& 1
 
0.3%
Space Separator
ValueCountFrequency (%)
6919
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1132
100.0%
Math Symbol
ValueCountFrequency (%)
~ 90
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23237
57.7%
Common 16841
41.8%
Latin 202
 
0.5%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 1523
 
6.6%
시 1514
 
6.5%
기 1488
 
6.4%
도 1475
 
6.3%
경 1463
 
6.3%
동 1426
 
6.1%
번 1415
 
6.1%
구 643
 
2.8%
층 612
 
2.6%
원 448
 
1.9%
Other values (388) 11230
48.3%
Latin
ValueCountFrequency (%)
B 22
 
10.9%
A 19
 
9.4%
C 15
 
7.4%
S 13
 
6.4%
L 12
 
5.9%
T 11
 
5.4%
I 10
 
5.0%
Y 9
 
4.5%
G 7
 
3.5%
E 7
 
3.5%
Other values (30) 77
38.1%
Common
ValueCountFrequency (%)
6919
41.1%
1 1494
 
8.9%
2 1145
 
6.8%
- 1132
 
6.7%
3 1050
 
6.2%
4 879
 
5.2%
0 867
 
5.1%
5 784
 
4.7%
6 609
 
3.6%
7 573
 
3.4%
Other values (10) 1389
 
8.2%
Han
ValueCountFrequency (%)
家 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23237
57.7%
ASCII 17043
42.3%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6919
40.6%
1 1494
 
8.8%
2 1145
 
6.7%
- 1132
 
6.6%
3 1050
 
6.2%
4 879
 
5.2%
0 867
 
5.1%
5 784
 
4.6%
6 609
 
3.6%
7 573
 
3.4%
Other values (50) 1591
 
9.3%
Hangul
ValueCountFrequency (%)
지 1523
 
6.6%
시 1514
 
6.5%
기 1488
 
6.4%
도 1475
 
6.3%
경 1463
 
6.3%
동 1426
 
6.1%
번 1415
 
6.1%
구 643
 
2.8%
층 612
 
2.6%
원 448
 
1.9%
Other values (388) 11230
48.3%
CJK
ValueCountFrequency (%)
家 1
100.0%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct930
Distinct (%)65.0%
Missing7
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean14257.746
Minimum10011
Maximum18611
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.8 KiB
2023-12-11T07:32:26.641973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10011
5-th percentile10342.45
Q112041.25
median14436.5
Q316430
95-th percentile18143.55
Maximum18611
Range8600
Interquartile range (IQR)4388.75

Descriptive statistics

Standard deviation2464.8207
Coefficient of variation (CV)0.1728759
Kurtosis-1.1176987
Mean14257.746
Median Absolute Deviation (MAD)2157.5
Skewness-0.016398152
Sum20388577
Variance6075341.2
MonotonicityNot monotonic
2023-12-11T07:32:26.756077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10071 9
 
0.6%
11813 8
 
0.6%
15865 7
 
0.5%
17936 6
 
0.4%
11492 6
 
0.4%
10113 6
 
0.4%
15360 6
 
0.4%
13506 6
 
0.4%
10381 6
 
0.4%
14948 6
 
0.4%
Other values (920) 1364
94.9%
(Missing) 7
 
0.5%
ValueCountFrequency (%)
10011 2
 
0.1%
10018 2
 
0.1%
10029 2
 
0.1%
10039 1
 
0.1%
10040 1
 
0.1%
10059 1
 
0.1%
10062 2
 
0.1%
10066 1
 
0.1%
10071 9
0.6%
10073 2
 
0.1%
ValueCountFrequency (%)
18611 2
0.1%
18606 1
 
0.1%
18603 1
 
0.1%
18600 2
0.1%
18598 1
 
0.1%
18593 3
0.2%
18592 1
 
0.1%
18591 1
 
0.1%
18577 1
 
0.1%
18568 1
 
0.1%

전화번호
Text

Distinct1418
Distinct (%)99.4%
Missing11
Missing (%)0.8%
Memory size11.4 KiB
2023-12-11T07:32:26.981318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.959327
Min length6

Characters and Unicode

Total characters17054
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1410 ?
Unique (%)98.9%

Sample

1st row031-298-7119
2nd row0318531266~7
3rd row031-852-9933
4th row031-559-8101
5th row031-441-2900
ValueCountFrequency (%)
032-327-6116 2
 
0.1%
031-691-7510 2
 
0.1%
031-954-1400 2
 
0.1%
031-697-8220 2
 
0.1%
031-982-7675 2
 
0.1%
031-999-2222 2
 
0.1%
031-732-0880 2
 
0.1%
031-221-2222 2
 
0.1%
02-381-0033 1
 
0.1%
031-857-1788 1
 
0.1%
Other values (1408) 1408
98.7%
2023-12-11T07:32:27.356868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2779
16.3%
0 2625
15.4%
1 2321
13.6%
3 2217
13.0%
7 1278
7.5%
2 1249
7.3%
5 1233
7.2%
8 1085
 
6.4%
9 816
 
4.8%
6 785
 
4.6%
Other values (2) 666
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14273
83.7%
Dash Punctuation 2779
 
16.3%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2625
18.4%
1 2321
16.3%
3 2217
15.5%
7 1278
9.0%
2 1249
8.8%
5 1233
8.6%
8 1085
7.6%
9 816
 
5.7%
6 785
 
5.5%
4 664
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 2779
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17054
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 2779
16.3%
0 2625
15.4%
1 2321
13.6%
3 2217
13.0%
7 1278
7.5%
2 1249
7.3%
5 1233
7.2%
8 1085
 
6.4%
9 816
 
4.8%
6 785
 
4.6%
Other values (2) 666
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17054
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2779
16.3%
0 2625
15.4%
1 2321
13.6%
3 2217
13.0%
7 1278
7.5%
2 1249
7.3%
5 1233
7.2%
8 1085
 
6.4%
9 816
 
4.8%
6 785
 
4.6%
Other values (2) 666
 
3.9%

팩스번호
Text

MISSING 

Distinct1383
Distinct (%)99.1%
Missing42
Missing (%)2.9%
Memory size11.4 KiB
2023-12-11T07:32:27.628418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.087455
Min length9

Characters and Unicode

Total characters16862
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

Unique1371 ?
Unique (%)98.3%

Sample

1st row031-298-2116
2nd row031-853-1269
3rd row031-852-9339
4th row031-559-8103
5th row031-468-7599
ValueCountFrequency (%)
031-759-7756 2
 
0.1%
032-325-9876 2
 
0.1%
031-294-0872 2
 
0.1%
031-999-2200 2
 
0.1%
031-221-9788 2
 
0.1%
031-697-8221 2
 
0.1%
031-691-7514 2
 
0.1%
031-954-1331 2
 
0.1%
031-989-9575 2
 
0.1%
031-732-0696 2
 
0.1%
Other values (1373) 1375
98.6%
2023-12-11T07:32:28.008898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2784
16.5%
0 2427
14.4%
3 2230
13.2%
1 2094
12.4%
2 1244
7.4%
7 1240
7.4%
8 1109
 
6.6%
5 1106
 
6.6%
6 922
 
5.5%
9 876
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14078
83.5%
Dash Punctuation 2784
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2427
17.2%
3 2230
15.8%
1 2094
14.9%
2 1244
8.8%
7 1240
8.8%
8 1109
7.9%
5 1106
7.9%
6 922
 
6.5%
9 876
 
6.2%
4 830
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 2784
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16862
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 2784
16.5%
0 2427
14.4%
3 2230
13.2%
1 2094
12.4%
2 1244
7.4%
7 1240
7.4%
8 1109
 
6.6%
5 1106
 
6.6%
6 922
 
5.5%
9 876
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16862
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2784
16.5%
0 2427
14.4%
3 2230
13.2%
1 2094
12.4%
2 1244
7.4%
7 1240
7.4%
8 1109
 
6.6%
5 1106
 
6.6%
6 922
 
5.5%
9 876
 
5.2%

진폐의료기관구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.4 KiB
비해당
1436 
해당
 
1

Length

Max length3
Median length3
Mean length2.9993041
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
비해당 1436
99.9%
해당 1
 
0.1%

Length

2023-12-11T07:32:28.138998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:32:28.245652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비해당 1436
99.9%
해당 1
 
0.1%

재활인증기관구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.4 KiB
비해당
1404 
해당
 
33

Length

Max length3
Median length3
Mean length2.9770355
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
비해당 1404
97.7%
해당 33
 
2.3%

Length

2023-12-11T07:32:28.355003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:32:28.721821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비해당 1404
97.7%
해당 33
 
2.3%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct1358
Distinct (%)95.2%
Missing10
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean37.438659
Minimum36.964405
Maximum38.090328
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.8 KiB
2023-12-11T07:32:28.879243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.964405
5-th percentile37.082041
Q137.291135
median37.412578
Q337.610632
95-th percentile37.759336
Maximum38.090328
Range1.1259226
Interquartile range (IQR)0.31949737

Descriptive statistics

Standard deviation0.21015997
Coefficient of variation (CV)0.0056134482
Kurtosis-0.38909772
Mean37.438659
Median Absolute Deviation (MAD)0.13854395
Skewness0.12439108
Sum53424.967
Variance0.044167214
MonotonicityNot monotonic
2023-12-11T07:32:29.009220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5981310767 3
 
0.2%
37.7448652943 3
 
0.2%
37.3277507121 3
 
0.2%
37.6762134714 3
 
0.2%
37.3604244685 2
 
0.1%
37.7530805063 2
 
0.1%
37.4195110154 2
 
0.1%
37.6772490952 2
 
0.1%
37.1492924517 2
 
0.1%
37.2671475731 2
 
0.1%
Other values (1348) 1403
97.6%
(Missing) 10
 
0.7%
ValueCountFrequency (%)
36.9644052069 1
0.1%
36.9648154983 1
0.1%
36.9787555958 1
0.1%
36.9790863294 2
0.1%
36.982523563 1
0.1%
36.9840497212 1
0.1%
36.9876822644 1
0.1%
36.9881523917 2
0.1%
36.9882692644 1
0.1%
36.9886189131 1
0.1%
ValueCountFrequency (%)
38.0903278355 1
0.1%
38.0253738214 1
0.1%
38.0244204892 1
0.1%
38.0235512237 1
0.1%
38.0174251575 1
0.1%
37.9998349286 1
0.1%
37.9577778808 1
0.1%
37.9198109083 1
0.1%
37.9088541736 1
0.1%
37.9068599484 1
0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct1358
Distinct (%)95.2%
Missing10
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean126.99515
Minimum126.58256
Maximum127.69137
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.8 KiB
2023-12-11T07:32:29.134336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.58256
5-th percentile126.73209
Q1126.81736
median127.01576
Q3127.12853
95-th percentile127.29725
Maximum127.69137
Range1.1088189
Interquartile range (IQR)0.31116875

Descriptive statistics

Standard deviation0.19356381
Coefficient of variation (CV)0.0015241828
Kurtosis0.28539181
Mean126.99515
Median Absolute Deviation (MAD)0.143639
Skewness0.49592159
Sum181222.07
Variance0.03746695
MonotonicityNot monotonic
2023-12-11T07:32:29.283857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1437133448 3
 
0.2%
127.0952364642 3
 
0.2%
126.8023400296 3
 
0.2%
126.7482756739 3
 
0.2%
126.9299909178 2
 
0.1%
127.0709328423 2
 
0.1%
127.2870710855 2
 
0.1%
126.7467229713 2
 
0.1%
127.073973741 2
 
0.1%
127.0805627445 2
 
0.1%
Other values (1348) 1403
97.6%
(Missing) 10
 
0.7%
ValueCountFrequency (%)
126.5825555862 1
0.1%
126.5870994059 2
0.1%
126.5877251202 1
0.1%
126.5989605649 1
0.1%
126.6001738151 1
0.1%
126.6191440503 1
0.1%
126.6227959716 1
0.1%
126.6228753128 1
0.1%
126.6232141562 1
0.1%
126.6235711257 2
0.1%
ValueCountFrequency (%)
127.6913745235 1
0.1%
127.6381504115 1
0.1%
127.6372797797 1
0.1%
127.6372098392 1
0.1%
127.6350809464 1
0.1%
127.6339605205 1
0.1%
127.6330504751 1
0.1%
127.6329239251 1
0.1%
127.6292555301 1
0.1%
127.6267042219 1
0.1%

Interactions

2023-12-11T07:32:23.732442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:23.028118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:23.419858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:23.825166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:23.149180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:23.541572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:23.922916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:23.288685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:23.640761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:32:29.378160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명관할지사우편번호진폐의료기관구분재활인증기관구분WGS84위도WGS84경도
시군명1.0001.0000.9920.0410.0000.9720.953
관할지사1.0001.0000.9440.0000.0000.8550.806
우편번호0.9920.9441.0000.0000.1000.9210.871
진폐의료기관구분0.0410.0000.0001.0000.0000.1340.000
재활인증기관구분0.0000.0000.1000.0001.0000.0000.000
WGS84위도0.9720.8550.9210.1340.0001.0000.687
WGS84경도0.9530.8060.8710.0000.0000.6871.000
2023-12-11T07:32:29.498113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
재활인증기관구분진폐의료기관구분시군명관할지사
재활인증기관구분1.0000.0000.0000.000
진폐의료기관구분0.0001.0000.0340.000
시군명0.0000.0341.0000.992
관할지사0.0000.0000.9921.000
2023-12-11T07:32:29.597057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호WGS84위도WGS84경도시군명관할지사진폐의료기관구분재활인증기관구분
우편번호1.000-0.9210.0990.9260.7900.0000.076
WGS84위도-0.9211.000-0.1360.8160.5850.1030.000
WGS84경도0.099-0.1361.0000.7410.5070.0000.000
시군명0.9260.8160.7411.0000.9920.0340.000
관할지사0.7900.5850.5070.9921.0000.0000.000
진폐의료기관구분0.0000.1030.0000.0340.0001.0000.000
재활인증기관구분0.0760.0000.0000.0000.0000.0001.000

Missing values

2023-12-11T07:32:24.053284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:32:24.194875image/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.
2023-12-11T07:32:24.303171image/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

시군명기관명관할지사도로명주소지번주소우편번호전화번호팩스번호진폐의료기관구분재활인증기관구분WGS84위도WGS84경도
0화성시삼성정형외과의원화성지사경기도 화성시 봉담읍 삼천병마로 1316경기도 화성시 봉담읍 동화리 424-3번지 삼성정형외과의원 (서울의원)18303031-298-7119031-298-2116비해당비해당37.222246126.951908
1의정부시진의원의정부지사경기도 의정부시 청사로 37경기도 의정부시 금오동 473-3번지 신세계프라자 501호117570318531266~7031-853-1269비해당비해당37.751517127.069852
2의정부시참서울의원의정부지사경기도 의정부시 금신로 368경기도 의정부시 금오동 463-2번지11751031-852-9933031-852-9339비해당비해당37.747978127.058544
3남양주시다산한의원남양주지사경기도 남양주시 늘을2로14번길 5경기도 남양주시 호평동 641-1번지 샤르망메디칼프라자 12층12150031-559-8101031-559-8103비해당비해당37.654114127.24457
4안양시본병원안양지사경기도 안양시 만안구 안양로314번길 15경기도 안양시 만안구 안양동 668-35번지 1,3-8층13992031-441-2900031-468-7599비해당비해당37.40069126.921031
5성남시참서울의원성남지사경기도 성남시 수정구 산성대로 207경기도 성남시 수정구 신흥동 6947번지 에드모스빌딩 4층13345031-734-3500031-734-3503비해당비해당37.438059127.140777
6안양시원천의료재단 중화연합의원안양지사경기도 안양시 만안구 관악대로 12경기도 안양시 만안구 안양동 380-2번지14032031-469-0365031-469-0364비해당비해당37.394624126.926648
7안산시박진영병원안산지사경기도 안산시 단원구 광덕대로 181경기도 안산시 단원구 고잔동 706-5번지 BYC빌딩 2층15461031-405-2200031-475-0009비해당비해당37.312808126.829269
8안산시에스정형외과의원안산지사경기도 안산시 단원구 예술대학로 17경기도 안산시 단원구 고잔동 534-3번지 안산중앙노블레스 4층15360031-482-7588031-482-7587비해당비해당37.318672126.836497
9수원시이건강치과의원수원지사경기도 수원시 팔달구 권광로 197경기도 수원시 팔달구 인계동 1038-3번지 301호16489031-222-0027031-222-0072비해당비해당37.265229127.032799
시군명기관명관할지사도로명주소지번주소우편번호전화번호팩스번호진폐의료기관구분재활인증기관구분WGS84위도WGS84경도
1427화성시의료법인은혜와감사의료재단(향남스마트병원)화성지사경기도 화성시 향남읍 상신하길로298번길 11경기도 화성시 향남읍 하길리 1471-4번지 지비앤티타워18611031-371-8050031-352-7582비해당비해당37.114774126.911059
1428안산시탑정형외과의원안산지사경기도 안산시 단원구 고잔로 88경기도 안산시 단원구 고잔동 534-2번지 지스타프라자 401호15360031-418-2772031-418-7163비해당비해당37.31875126.836011
1429시흥시참사랑 신경외과의원안산지사경기도 시흥시 시흥대로1074번길 5경기도 시흥시 은행동 288-1번지 스페이스타워 3층14921031-435-7582031-435-7580비해당비해당37.431978126.793541
1430성남시티플러스치과의원성남지사경기도 성남시 수정구 성남대로 1228경기도 성남시 수정구 수진동 2997번지 해광빌딩 6층13316031-723-7522<NA>비해당비해당37.439516127.128177
1431화성시새봄병원화성지사경기도 화성시 꽃내음1길 5-4경기도 화성시 새솔동 78-1번지 봄프라자(401~415호) 3,4층 304~310호18244031-357-8100031-357-2761비해당비해당37.284993126.816836
1432광명시서울경희한의원안양지사경기도 광명시 오리로 856경기도 광명시 철산동 413번지 한복빌딩 4층1424002-2060-369502-2060-3635비해당비해당37.474723126.867261
1433성남시(학교법인)동국대학교한의과대학분당한방병원성남지사경기도 성남시 분당구 불정로 268경기도 성남시 분당구 수내동 87-2번지13601031-710-3790031-710-3780비해당비해당37.36727127.127981
1434여주시구인재활의학과의원용인지사경기도 여주시 대신면 여양로 1421경기도 여주시 대신면 율촌리 269-7번지 구인재활의학과의원12610031-882-7636031-882-7709비해당비해당37.375384127.590121
1435광주시사상참경희한의원성남지사경기도 광주시 초월읍 경충대로 922경기도 광주시 초월읍 산이리 95-54번지12799031-798-8770031-798-8772비해당비해당37.36474127.312082
1436구리시이종환한의원남양주지사경기도 구리시 경춘로 253경기도 구리시 인창동 676-7번지 다우스퀘어 7층 3호11922031-565-5775031-565-5885비해당비해당37.602239127.143037