Overview

Dataset statistics

Number of variables8
Number of observations507
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory33.3 KiB
Average record size in memory67.3 B

Variable types

Numeric3
Categorical1
Text4

Dataset

Description보건복지부_전국 산후조리원 시도, 시군구, 산후조리원 이름, 산후조리원 주소 등 정보를 제공합니다. 산후조리원, 출산, 산후조리 등 정보를 제공합니다.
Author보건복지부
URLhttps://www.data.go.kr/data/15004303/fileData.do

Alerts

번호 is highly overall correlated with 시도High correlation
일반실 is highly overall correlated with 특실High correlation
특실 is highly overall correlated with 일반실High correlation
시도 is highly overall correlated with 번호High correlation
번호 has unique valuesUnique
특실 has 141 (27.8%) zerosZeros

Reproduction

Analysis started2023-12-12 21:30:03.127005
Analysis finished2023-12-12 21:30:04.612976
Duration1.49 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct507
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean254
Minimum1
Maximum507
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-13T06:30:04.679564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile26.3
Q1127.5
median254
Q3380.5
95-th percentile481.7
Maximum507
Range506
Interquartile range (IQR)253

Descriptive statistics

Standard deviation146.50256
Coefficient of variation (CV)0.57678173
Kurtosis-1.2
Mean254
Median Absolute Deviation (MAD)127
Skewness0
Sum128778
Variance21463
MonotonicityStrictly increasing
2023-12-13T06:30:04.807994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
335 1
 
0.2%
348 1
 
0.2%
347 1
 
0.2%
346 1
 
0.2%
345 1
 
0.2%
344 1
 
0.2%
343 1
 
0.2%
342 1
 
0.2%
341 1
 
0.2%
Other values (497) 497
98.0%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
507 1
0.2%
506 1
0.2%
505 1
0.2%
504 1
0.2%
503 1
0.2%
502 1
0.2%
501 1
0.2%
500 1
0.2%
499 1
0.2%
498 1
0.2%

시도
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
경기
156 
서울
125 
인천
28 
부산
28 
경남
27 
Other values (12)
143 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기 156
30.8%
서울 125
24.7%
인천 28
 
5.5%
부산 28
 
5.5%
경남 27
 
5.3%
대구 24
 
4.7%
강원 16
 
3.2%
충남 16
 
3.2%
전북 14
 
2.8%
경북 13
 
2.6%
Other values (7) 60
 
11.8%

Length

2023-12-13T06:30:04.930006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 156
30.8%
서울 125
24.7%
인천 28
 
5.5%
부산 28
 
5.5%
경남 27
 
5.3%
대구 24
 
4.7%
강원 16
 
3.2%
충남 16
 
3.2%
전북 14
 
2.8%
경북 13
 
2.6%
Other values (7) 60
 
11.8%

시군구
Text

Distinct126
Distinct (%)24.9%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-13T06:30:05.223394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.8560158
Min length2

Characters and Unicode

Total characters1955
Distinct characters111
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)4.7%

Sample

1st row종로구
2nd row종로구
3rd row중구
4th row중구
5th row성동구
ValueCountFrequency (%)
성남시 20
 
3.3%
서구 17
 
2.8%
강남구 17
 
2.8%
수원시 16
 
2.6%
용인시 16
 
2.6%
창원시 14
 
2.3%
북구 13
 
2.1%
분당구 13
 
2.1%
화성시 11
 
1.8%
강동구 11
 
1.8%
Other values (125) 459
75.6%
2023-12-13T06:30:05.689090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 346
17.7%
시 276
 
14.1%
100
 
5.1%
원 60
 
3.1%
남 58
 
3.0%
서 57
 
2.9%
주 52
 
2.7%
양 49
 
2.5%
동 48
 
2.5%
성 48
 
2.5%
Other values (101) 861
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1845
94.4%
Space Separator 100
 
5.1%
Close Punctuation 5
 
0.3%
Open Punctuation 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 346
18.8%
시 276
 
15.0%
원 60
 
3.3%
남 58
 
3.1%
서 57
 
3.1%
주 52
 
2.8%
양 49
 
2.7%
동 48
 
2.6%
성 48
 
2.6%
수 43
 
2.3%
Other values (98) 808
43.8%
Space Separator
ValueCountFrequency (%)
100
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1845
94.4%
Common 110
 
5.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 346
18.8%
시 276
 
15.0%
원 60
 
3.3%
남 58
 
3.1%
서 57
 
3.1%
주 52
 
2.8%
양 49
 
2.7%
동 48
 
2.6%
성 48
 
2.6%
수 43
 
2.3%
Other values (98) 808
43.8%
Common
ValueCountFrequency (%)
100
90.9%
) 5
 
4.5%
( 5
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1845
94.4%
ASCII 110
 
5.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 346
18.8%
시 276
 
15.0%
원 60
 
3.3%
남 58
 
3.1%
서 57
 
3.1%
주 52
 
2.8%
양 49
 
2.7%
동 48
 
2.6%
성 48
 
2.6%
수 43
 
2.3%
Other values (98) 808
43.8%
ASCII
ValueCountFrequency (%)
100
90.9%
) 5
 
4.5%
( 5
 
4.5%

산후조리원
Text

Distinct479
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-13T06:30:05.955525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length8.5700197
Min length1

Characters and Unicode

Total characters4345
Distinct characters318
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique458 ?
Unique (%)90.3%

Sample

1st row첫단추(창경궁점)
2nd row올리비움
3rd row더드림 산후조리원
4th row와이케이 동그라미 레피리움 산후조리원
5th row㈜와이케이 동그라미 산후조리원 행당점
ValueCountFrequency (%)
산후조리원 86
 
13.2%
미래여성산후조리원 5
 
0.8%
동그라미 5
 
0.8%
레피리움 5
 
0.8%
미래산후조리원 4
 
0.6%
2호점 4
 
0.6%
마미캠프 3
 
0.5%
이자르산후조리원 3
 
0.5%
미즈맘산후조리원 3
 
0.5%
2관 2
 
0.3%
Other values (498) 531
81.6%
2023-12-13T06:30:06.343512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 460
 
10.6%
원 435
 
10.0%
산 408
 
9.4%
조 399
 
9.2%
후 395
 
9.1%
144
 
3.3%
미 79
 
1.8%
아 65
 
1.5%
이 58
 
1.3%
라 49
 
1.1%
Other values (308) 1853
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4065
93.6%
Space Separator 144
 
3.3%
Close Punctuation 33
 
0.8%
Open Punctuation 32
 
0.7%
Other Symbol 30
 
0.7%
Uppercase Letter 24
 
0.6%
Decimal Number 13
 
0.3%
Lowercase Letter 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 460
 
11.3%
원 435
 
10.7%
산 408
 
10.0%
조 399
 
9.8%
후 395
 
9.7%
미 79
 
1.9%
아 65
 
1.6%
이 58
 
1.4%
라 49
 
1.2%
스 45
 
1.1%
Other values (284) 1672
41.1%
Uppercase Letter
ValueCountFrequency (%)
Y 4
16.7%
M 4
16.7%
K 3
12.5%
B 2
8.3%
H 2
8.3%
J 2
8.3%
S 1
 
4.2%
G 1
 
4.2%
T 1
 
4.2%
V 1
 
4.2%
Other values (3) 3
12.5%
Decimal Number
ValueCountFrequency (%)
2 7
53.8%
1 5
38.5%
3 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
h 1
50.0%
e 1
50.0%
Space Separator
ValueCountFrequency (%)
144
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 30
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4095
94.2%
Common 224
 
5.2%
Latin 26
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 460
 
11.2%
원 435
 
10.6%
산 408
 
10.0%
조 399
 
9.7%
후 395
 
9.6%
미 79
 
1.9%
아 65
 
1.6%
이 58
 
1.4%
라 49
 
1.2%
스 45
 
1.1%
Other values (285) 1702
41.6%
Latin
ValueCountFrequency (%)
Y 4
15.4%
M 4
15.4%
K 3
11.5%
B 2
 
7.7%
H 2
 
7.7%
J 2
 
7.7%
h 1
 
3.8%
e 1
 
3.8%
S 1
 
3.8%
G 1
 
3.8%
Other values (5) 5
19.2%
Common
ValueCountFrequency (%)
144
64.3%
) 33
 
14.7%
( 32
 
14.3%
2 7
 
3.1%
1 5
 
2.2%
3 1
 
0.4%
& 1
 
0.4%
- 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4065
93.6%
ASCII 250
 
5.8%
None 30
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 460
 
11.3%
원 435
 
10.7%
산 408
 
10.0%
조 399
 
9.8%
후 395
 
9.7%
미 79
 
1.9%
아 65
 
1.6%
이 58
 
1.4%
라 49
 
1.2%
스 45
 
1.1%
Other values (284) 1672
41.1%
ASCII
ValueCountFrequency (%)
144
57.6%
) 33
 
13.2%
( 32
 
12.8%
2 7
 
2.8%
1 5
 
2.0%
Y 4
 
1.6%
M 4
 
1.6%
K 3
 
1.2%
B 2
 
0.8%
H 2
 
0.8%
Other values (13) 14
 
5.6%
None
ValueCountFrequency (%)
㈜ 30
100.0%

주소
Text

Distinct504
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-13T06:30:06.688968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length38
Mean length24.175542
Min length12

Characters and Unicode

Total characters12257
Distinct characters357
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique501 ?
Unique (%)98.8%

Sample

1st row서울특별시 종로구 원남동 28-7 창경빌딩 2~4층
2nd row서울특별시 종로구 통일로 16길 4-1
3rd row서울특별시 서울시 중구 다산로36길 11 6,7층
4th row서울특별시 서울시 중구 중림로31, 이화빌딩 1층
5th row서울특별시 성동구 고산자로 6길 40 6층
ValueCountFrequency (%)
경기도 140
 
5.6%
서울특별시 118
 
4.7%
경상남도 27
 
1.1%
부산광역시 26
 
1.0%
대구광역시 24
 
1.0%
성남시 20
 
0.8%
4층 18
 
0.7%
서구 17
 
0.7%
강남구 17
 
0.7%
수원시 16
 
0.6%
Other values (1259) 2068
83.0%
2023-12-13T06:30:07.166334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2014
 
16.4%
시 498
 
4.1%
로 490
 
4.0%
1 397
 
3.2%
구 379
 
3.1%
동 347
 
2.8%
도 268
 
2.2%
2 267
 
2.2%
) 249
 
2.0%
( 248
 
2.0%
Other values (347) 7100
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7359
60.0%
Decimal Number 2066
 
16.9%
Space Separator 2014
 
16.4%
Close Punctuation 249
 
2.0%
Open Punctuation 248
 
2.0%
Other Punctuation 191
 
1.6%
Dash Punctuation 76
 
0.6%
Math Symbol 39
 
0.3%
Uppercase Letter 14
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 498
 
6.8%
로 490
 
6.7%
구 379
 
5.2%
동 347
 
4.7%
도 268
 
3.6%
서 210
 
2.9%
경 206
 
2.8%
층 206
 
2.8%
대 161
 
2.2%
기 155
 
2.1%
Other values (322) 4439
60.3%
Decimal Number
ValueCountFrequency (%)
1 397
19.2%
2 267
12.9%
3 218
10.6%
4 214
10.4%
6 202
9.8%
5 188
9.1%
7 163
7.9%
0 149
 
7.2%
8 144
 
7.0%
9 124
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
B 5
35.7%
S 2
 
14.3%
M 2
 
14.3%
C 2
 
14.3%
F 1
 
7.1%
Y 1
 
7.1%
A 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 179
93.7%
. 12
 
6.3%
Space Separator
ValueCountFrequency (%)
2014
100.0%
Close Punctuation
ValueCountFrequency (%)
) 249
100.0%
Open Punctuation
ValueCountFrequency (%)
( 248
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%
Math Symbol
ValueCountFrequency (%)
~ 39
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7359
60.0%
Common 4883
39.8%
Latin 15
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 498
 
6.8%
로 490
 
6.7%
구 379
 
5.2%
동 347
 
4.7%
도 268
 
3.6%
서 210
 
2.9%
경 206
 
2.8%
층 206
 
2.8%
대 161
 
2.2%
기 155
 
2.1%
Other values (322) 4439
60.3%
Common
ValueCountFrequency (%)
2014
41.2%
1 397
 
8.1%
2 267
 
5.5%
) 249
 
5.1%
( 248
 
5.1%
3 218
 
4.5%
4 214
 
4.4%
6 202
 
4.1%
5 188
 
3.9%
, 179
 
3.7%
Other values (7) 707
 
14.5%
Latin
ValueCountFrequency (%)
B 5
33.3%
S 2
 
13.3%
M 2
 
13.3%
C 2
 
13.3%
F 1
 
6.7%
Y 1
 
6.7%
c 1
 
6.7%
A 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7359
60.0%
ASCII 4898
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2014
41.1%
1 397
 
8.1%
2 267
 
5.5%
) 249
 
5.1%
( 248
 
5.1%
3 218
 
4.5%
4 214
 
4.4%
6 202
 
4.1%
5 188
 
3.8%
, 179
 
3.7%
Other values (15) 722
 
14.7%
Hangul
ValueCountFrequency (%)
시 498
 
6.8%
로 490
 
6.7%
구 379
 
5.2%
동 347
 
4.7%
도 268
 
3.6%
서 210
 
2.9%
경 206
 
2.8%
층 206
 
2.8%
대 161
 
2.2%
기 155
 
2.1%
Other values (322) 4439
60.3%

전화번호
Text

Distinct504
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-13T06:30:07.406320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.881657
Min length9

Characters and Unicode

Total characters6024
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

Unique501 ?
Unique (%)98.8%

Sample

1st row02-763-5400
2nd row02-738-3335
3rd row02-2231-6375
4th row02-6012-1010
5th row02-6409-1003
ValueCountFrequency (%)
02-3453-4628 2
 
0.4%
031-853-2030 2
 
0.4%
042-488-3565 2
 
0.4%
055-365-0202 1
 
0.2%
031-896-3333 1
 
0.2%
031-631-9170 1
 
0.2%
031-636-0671 1
 
0.2%
031-853-9115 1
 
0.2%
031-879-8434 1
 
0.2%
031-836-3001 1
 
0.2%
Other values (494) 494
97.4%
2023-12-13T06:30:07.774117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1092
18.1%
- 1010
16.8%
3 659
10.9%
2 602
10.0%
5 557
9.2%
1 528
8.8%
7 372
 
6.2%
6 358
 
5.9%
4 327
 
5.4%
8 302
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5014
83.2%
Dash Punctuation 1010
 
16.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1092
21.8%
3 659
13.1%
2 602
12.0%
5 557
11.1%
1 528
10.5%
7 372
 
7.4%
6 358
 
7.1%
4 327
 
6.5%
8 302
 
6.0%
9 217
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 1010
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6024
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1092
18.1%
- 1010
16.8%
3 659
10.9%
2 602
10.0%
5 557
9.2%
1 528
8.8%
7 372
 
6.2%
6 358
 
5.9%
4 327
 
5.4%
8 302
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6024
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1092
18.1%
- 1010
16.8%
3 659
10.9%
2 602
10.0%
5 557
9.2%
1 528
8.8%
7 372
 
6.2%
6 358
 
5.9%
4 327
 
5.4%
8 302
 
5.0%

일반실
Real number (ℝ)

HIGH CORRELATION 

Distinct102
Distinct (%)20.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean265.23669
Minimum0
Maximum1300
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-13T06:30:07.905384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile150
Q1200
median250
Q3290
95-th percentile450
Maximum1300
Range1300
Interquartile range (IQR)90

Descriptive statistics

Standard deviation115.00778
Coefficient of variation (CV)0.43360435
Kurtosis22.7803
Mean265.23669
Median Absolute Deviation (MAD)50
Skewness3.4313681
Sum134475
Variance13226.79
MonotonicityNot monotonic
2023-12-13T06:30:08.034074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
250 30
 
5.9%
200 30
 
5.9%
220 28
 
5.5%
240 27
 
5.3%
230 27
 
5.3%
260 26
 
5.1%
270 26
 
5.1%
280 25
 
4.9%
180 22
 
4.3%
300 21
 
4.1%
Other values (92) 245
48.3%
ValueCountFrequency (%)
0 1
 
0.2%
55 1
 
0.2%
59 1
 
0.2%
60 1
 
0.2%
69 1
 
0.2%
70 1
 
0.2%
90 1
 
0.2%
100 2
0.4%
110 3
0.6%
116 1
 
0.2%
ValueCountFrequency (%)
1300 1
0.2%
1200 1
0.2%
800 1
0.2%
700 1
0.2%
690 1
0.2%
680 2
0.4%
630 1
0.2%
600 1
0.2%
590 1
0.2%
580 1
0.2%

특실
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct110
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean257.55621
Minimum0
Maximum2600
Zeros141
Zeros (%)27.8%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-13T06:30:08.162675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median250
Q3330
95-th percentile550
Maximum2600
Range2600
Interquartile range (IQR)330

Descriptive statistics

Standard deviation287.52492
Coefficient of variation (CV)1.1163579
Kurtosis21.965503
Mean257.55621
Median Absolute Deviation (MAD)100
Skewness3.7690093
Sum130581
Variance82670.579
MonotonicityNot monotonic
2023-12-13T06:30:08.314464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 141
27.8%
250 25
 
4.9%
260 24
 
4.7%
280 17
 
3.4%
230 16
 
3.2%
320 15
 
3.0%
290 13
 
2.6%
300 13
 
2.6%
350 12
 
2.4%
380 12
 
2.4%
Other values (100) 219
43.2%
ValueCountFrequency (%)
0 141
27.8%
65 1
 
0.2%
79 1
 
0.2%
109 1
 
0.2%
120 1
 
0.2%
125 1
 
0.2%
130 3
 
0.6%
150 2
 
0.4%
154 1
 
0.2%
160 4
 
0.8%
ValueCountFrequency (%)
2600 1
0.2%
2300 1
0.2%
2000 2
0.4%
1800 1
0.2%
1700 1
0.2%
1500 2
0.4%
1300 1
0.2%
1200 2
0.4%
1150 1
0.2%
900 1
0.2%

Interactions

2023-12-13T06:30:04.149587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:03.676117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:03.922845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:04.224665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:03.756008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:03.997144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:04.301455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:03.844769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:30:04.072615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:30:08.405320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호시도일반실특실
번호1.0000.9340.4300.398
시도0.9341.0000.4130.000
일반실0.4300.4131.0000.843
특실0.3980.0000.8431.000
2023-12-13T06:30:08.509322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호일반실특실시도
번호1.000-0.446-0.2700.727
일반실-0.4461.0000.5620.185
특실-0.2700.5621.0000.000
시도0.7270.1850.0001.000

Missing values

2023-12-13T06:30:04.405716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:30:04.554816image/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

번호시도시군구산후조리원주소전화번호일반실특실
01서울종로구첫단추(창경궁점)서울특별시 종로구 원남동 28-7 창경빌딩 2~4층02-763-5400410460
12서울종로구올리비움서울특별시 종로구 통일로 16길 4-102-738-33354702000
23서울중구더드림 산후조리원서울특별시 서울시 중구 다산로36길 11 6,7층02-2231-6375280330
34서울중구와이케이 동그라미 레피리움 산후조리원서울특별시 서울시 중구 중림로31, 이화빌딩 1층02-6012-1010450450
45서울성동구㈜와이케이 동그라미 산후조리원 행당점서울특별시 성동구 고산자로 6길 40 6층02-6409-10034500
56서울광진구광진아기맘미소서울특별시 광진구 뚝섬로 503, 3층(자양동)02-447-00653000
67서울광진구르베르쏘서울특별시 광진구 구의로 28 2층(구의동)02-457-60202200
78서울광진구(주)궁 구의점서울특별시 광진구 자양로 192 1~5층(구의동)02-453-0640480580
89서울동대문구린아미에산후조리원서울특별시 동대문구 장한로 119 (장안동,삼성쉐르빌2층)02-2246-20012500
910서울동대문구삼육서울병원부설산후조리원서울특별시 동대문구 망우로 82, B1,1,2층 (휘경동)2210-3366230286
번호시도시군구산후조리원주소전화번호일반실특실
497498경남통영시통영자모산후조리원경상남도 통영시 무전대로 4, 301055-646-3537200220
498499제주제주시프린세스산후조리원제주특별자치도 제주시 서광로 220. 4층 서광빌딩(삼도1동)064-722-2277200210
499500제주제주시예나산후조리원제주특별자치도 제주시 남광로 83 (용담2동)064-748-0088200210
500501제주제주시에덴산후조리원제주특별자치도 제주시 도령로 11(노형동)064-748-1828180190
501502제주제주시프라임산후조리원제주특별자치도 제주시 오남로82 (오라2동)064-702-1155230260
502503제주제주시엔젤산후조리원제주특별자치도 제주시과원로70 3층9연동)064-741-5335250250
503504제주제주시맘편한산후조리원제주특별자치도 제주시1100로3283영화빌딩2층(노형)064-711-30801800
504505제주제주시드림포레산후조리원제주특별자치도 제주시 서사로 136, 2층064-759-78382600
505506제주서귀포시서귀포공공산후조리원제주특별자치도 서귀포시 중앙로 125064-762-30051540
506507제주서귀포시제주서귀포의료원 부설 산후조리원제주특별자치도 서귀포시 장수로 47064-730-36541900