Overview

Dataset statistics

Number of variables11
Number of observations1684
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory149.8 KiB
Average record size in memory91.1 B

Variable types

Numeric2
Categorical6
Text3

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기 has constant value ""Constant
순번 is highly overall correlated with 시군명High correlation
우편번호 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
병원구분 is highly imbalanced (50.6%)Imbalance
순번 has unique valuesUnique

Reproduction

Analysis started2024-03-13 23:43:56.065102
Analysis finished2024-03-13 23:43:57.014968
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1684
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean842.5
Minimum1
Maximum1684
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2024-03-14T08:43:57.070314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile85.15
Q1421.75
median842.5
Q31263.25
95-th percentile1599.85
Maximum1684
Range1683
Interquartile range (IQR)841.5

Descriptive statistics

Standard deviation486.27324
Coefficient of variation (CV)0.57717892
Kurtosis-1.2
Mean842.5
Median Absolute Deviation (MAD)421
Skewness0
Sum1418770
Variance236461.67
MonotonicityStrictly increasing
2024-03-14T08:43:57.515039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1108 1
 
0.1%
1132 1
 
0.1%
1131 1
 
0.1%
1130 1
 
0.1%
1129 1
 
0.1%
1128 1
 
0.1%
1127 1
 
0.1%
1126 1
 
0.1%
1125 1
 
0.1%
Other values (1674) 1674
99.4%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1684 1
0.1%
1683 1
0.1%
1682 1
0.1%
1681 1
0.1%
1680 1
0.1%
1679 1
0.1%
1678 1
0.1%
1677 1
0.1%
1676 1
0.1%
1675 1
0.1%

시군명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
전주시
699 
익산시
251 
군산시
230 
정읍시
108 
남원시
82 
Other values (9)
314 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 699
41.5%
익산시 251
 
14.9%
군산시 230
 
13.7%
정읍시 108
 
6.4%
남원시 82
 
4.9%
김제시 80
 
4.8%
완주군 58
 
3.4%
고창군 46
 
2.7%
부안군 43
 
2.6%
순창군 20
 
1.2%
Other values (4) 67
 
4.0%

Length

2024-03-14T08:43:57.640279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 699
41.5%
익산시 251
 
14.9%
군산시 230
 
13.7%
정읍시 108
 
6.4%
남원시 82
 
4.9%
김제시 80
 
4.8%
완주군 58
 
3.4%
고창군 46
 
2.7%
부안군 43
 
2.6%
순창군 20
 
1.2%
Other values (4) 67
 
4.0%

병원명
Text

Distinct1480
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
2024-03-14T08:43:57.810524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length7.4174584
Min length3

Characters and Unicode

Total characters12491
Distinct characters399
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1342 ?
Unique (%)79.7%

Sample

1st row우리가정의원
2nd row상아치과의원
3rd row즐거운치과의원
4th row하종영내과의원
5th row제일산부인과의원
ValueCountFrequency (%)
현대의원 7
 
0.4%
제일치과의원 5
 
0.3%
현대마취통증의학과의원 5
 
0.3%
우리가정의학과의원 5
 
0.3%
중앙의원 5
 
0.3%
하나의원 5
 
0.3%
세종치과의원 4
 
0.2%
이사랑치과의원 4
 
0.2%
현대치과의원 4
 
0.2%
아름다운치과의원 4
 
0.2%
Other values (1470) 1636
97.1%
2024-03-14T08:43:58.109417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
의 1787
 
14.3%
원 1707
 
13.7%
과 1357
 
10.9%
치 518
 
4.1%
정 253
 
2.0%
이 217
 
1.7%
내 193
 
1.5%
인 177
 
1.4%
학 174
 
1.4%
소 165
 
1.3%
Other values (389) 5943
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12428
99.5%
Decimal Number 27
 
0.2%
Close Punctuation 10
 
0.1%
Open Punctuation 10
 
0.1%
Uppercase Letter 6
 
< 0.1%
Other Punctuation 4
 
< 0.1%
Lowercase Letter 4
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 1787
 
14.4%
원 1707
 
13.7%
과 1357
 
10.9%
치 518
 
4.2%
정 253
 
2.0%
이 217
 
1.7%
내 193
 
1.6%
인 177
 
1.4%
학 174
 
1.4%
소 165
 
1.3%
Other values (370) 5880
47.3%
Decimal Number
ValueCountFrequency (%)
0 16
59.3%
1 4
 
14.8%
2 4
 
14.8%
3 1
 
3.7%
6 1
 
3.7%
5 1
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
M 1
16.7%
F 1
16.7%
E 1
16.7%
D 1
16.7%
L 1
16.7%
S 1
16.7%
Other Punctuation
ValueCountFrequency (%)
& 3
75.0%
. 1
 
25.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
75.0%
r 1
 
25.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12428
99.5%
Common 53
 
0.4%
Latin 10
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 1787
 
14.4%
원 1707
 
13.7%
과 1357
 
10.9%
치 518
 
4.2%
정 253
 
2.0%
이 217
 
1.7%
내 193
 
1.6%
인 177
 
1.4%
학 174
 
1.4%
소 165
 
1.3%
Other values (370) 5880
47.3%
Common
ValueCountFrequency (%)
0 16
30.2%
) 10
18.9%
( 10
18.9%
1 4
 
7.5%
2 4
 
7.5%
& 3
 
5.7%
- 2
 
3.8%
. 1
 
1.9%
3 1
 
1.9%
6 1
 
1.9%
Latin
ValueCountFrequency (%)
e 3
30.0%
M 1
 
10.0%
F 1
 
10.0%
E 1
 
10.0%
D 1
 
10.0%
r 1
 
10.0%
L 1
 
10.0%
S 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12428
99.5%
ASCII 63
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
의 1787
 
14.4%
원 1707
 
13.7%
과 1357
 
10.9%
치 518
 
4.2%
정 253
 
2.0%
이 217
 
1.7%
내 193
 
1.6%
인 177
 
1.4%
학 174
 
1.4%
소 165
 
1.3%
Other values (370) 5880
47.3%
ASCII
ValueCountFrequency (%)
0 16
25.4%
) 10
15.9%
( 10
15.9%
1 4
 
6.3%
2 4
 
6.3%
& 3
 
4.8%
e 3
 
4.8%
- 2
 
3.2%
M 1
 
1.6%
F 1
 
1.6%
Other values (9) 9
14.3%

병원구분
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
의원
1029 
치과의원
510 
병원
 
74
산부인과
 
56
종합병원
 
11
Other values (2)
 
4

Length

Max length4
Median length2
Mean length2.6900238
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row의원
2nd row치과의원
3rd row치과의원
4th row의원
5th row산부인과

Common Values

ValueCountFrequency (%)
의원 1029
61.1%
치과의원 510
30.3%
병원 74
 
4.4%
산부인과 56
 
3.3%
종합병원 11
 
0.7%
상급종합 2
 
0.1%
치과병원 2
 
0.1%

Length

2024-03-14T08:43:58.220413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T08:43:58.314614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의원 1029
61.1%
치과의원 510
30.3%
병원 74
 
4.4%
산부인과 56
 
3.3%
종합병원 11
 
0.7%
상급종합 2
 
0.1%
치과병원 2
 
0.1%

도로명주소
Text

Distinct1466
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
2024-03-14T08:43:58.604935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length29
Mean length18.471496
Min length9

Characters and Unicode

Total characters31106
Distinct characters255
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1284 ?
Unique (%)76.2%

Sample

1st row익산시 동천로7길 29
2nd row익산시 고봉로14길 4 (영등동)
3rd row익산시 동서로 229 (남중동)
4th row익산시 동서로 229
5th row익산시 동서로 231 (남중동)
ValueCountFrequency (%)
전주시 699
 
9.6%
완산구 415
 
5.7%
덕진구 284
 
3.9%
익산시 251
 
3.5%
군산시 230
 
3.2%
정읍시 108
 
1.5%
남원시 82
 
1.1%
중앙로 81
 
1.1%
김제시 80
 
1.1%
백제대로 67
 
0.9%
Other values (1192) 4957
68.3%
2024-03-14T08:43:58.994590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5570
 
17.9%
로 1506
 
4.8%
시 1486
 
4.8%
1 1219
 
3.9%
( 1177
 
3.8%
) 1177
 
3.8%
산 1148
 
3.7%
동 1091
 
3.5%
2 821
 
2.6%
주 812
 
2.6%
Other values (245) 15099
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17871
57.5%
Space Separator 5570
 
17.9%
Decimal Number 5115
 
16.4%
Open Punctuation 1177
 
3.8%
Close Punctuation 1177
 
3.8%
Dash Punctuation 176
 
0.6%
Other Punctuation 18
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 1506
 
8.4%
시 1486
 
8.3%
산 1148
 
6.4%
동 1091
 
6.1%
주 812
 
4.5%
구 739
 
4.1%
전 732
 
4.1%
완 481
 
2.7%
군 467
 
2.6%
읍 458
 
2.6%
Other values (227) 8951
50.1%
Decimal Number
ValueCountFrequency (%)
1 1219
23.8%
2 821
16.1%
3 562
11.0%
4 477
 
9.3%
6 399
 
7.8%
5 372
 
7.3%
0 363
 
7.1%
7 308
 
6.0%
8 304
 
5.9%
9 290
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 15
83.3%
. 3
 
16.7%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
5570
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1177
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1177
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 176
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17871
57.5%
Common 13233
42.5%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 1506
 
8.4%
시 1486
 
8.3%
산 1148
 
6.4%
동 1091
 
6.1%
주 812
 
4.5%
구 739
 
4.1%
전 732
 
4.1%
완 481
 
2.7%
군 467
 
2.6%
읍 458
 
2.6%
Other values (227) 8951
50.1%
Common
ValueCountFrequency (%)
5570
42.1%
1 1219
 
9.2%
( 1177
 
8.9%
) 1177
 
8.9%
2 821
 
6.2%
3 562
 
4.2%
4 477
 
3.6%
6 399
 
3.0%
5 372
 
2.8%
0 363
 
2.7%
Other values (6) 1096
 
8.3%
Latin
ValueCountFrequency (%)
k 1
50.0%
s 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17871
57.5%
ASCII 13235
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5570
42.1%
1 1219
 
9.2%
( 1177
 
8.9%
) 1177
 
8.9%
2 821
 
6.2%
3 562
 
4.2%
4 477
 
3.6%
6 399
 
3.0%
5 372
 
2.8%
0 363
 
2.7%
Other values (8) 1098
 
8.3%
Hangul
ValueCountFrequency (%)
로 1506
 
8.4%
시 1486
 
8.3%
산 1148
 
6.4%
동 1091
 
6.1%
주 812
 
4.5%
구 739
 
4.1%
전 732
 
4.1%
완 481
 
2.7%
군 467
 
2.6%
읍 458
 
2.6%
Other values (227) 8951
50.1%

전화번호
Text

Distinct1676
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
2024-03-14T08:43:59.204551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length12
Mean length12.067102
Min length12

Characters and Unicode

Total characters20321
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1668 ?
Unique (%)99.0%

Sample

1st row063-843-1600
2nd row063-841-7281
3rd row063-852-3400
4th row063-842-0890
5th row063-840-7500
ValueCountFrequency (%)
063-635-3020 2
 
0.1%
063-837-5555 2
 
0.1%
063-545-8383 2
 
0.1%
063-532-1414 2
 
0.1%
063-283-6672 2
 
0.1%
063-464-5550 2
 
0.1%
063-259-8900 2
 
0.1%
063-222-7891 2
 
0.1%
063-582-0202 1
 
0.1%
063-581-0733 1
 
0.1%
Other values (1666) 1666
98.9%
2024-03-14T08:43:59.528907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 3390
16.7%
0 2849
14.0%
3 2848
14.0%
6 2579
12.7%
2 2139
10.5%
5 1628
8.0%
8 1288
 
6.3%
7 1187
 
5.8%
4 1074
 
5.3%
1 887
 
4.4%
Other values (4) 452
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16906
83.2%
Dash Punctuation 3390
 
16.7%
Other Punctuation 14
 
0.1%
Math Symbol 11
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2849
16.9%
3 2848
16.8%
6 2579
15.3%
2 2139
12.7%
5 1628
9.6%
8 1288
7.6%
7 1187
7.0%
4 1074
 
6.4%
1 887
 
5.2%
9 427
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 13
92.9%
/ 1
 
7.1%
Dash Punctuation
ValueCountFrequency (%)
- 3390
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20321
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 3390
16.7%
0 2849
14.0%
3 2848
14.0%
6 2579
12.7%
2 2139
10.5%
5 1628
8.0%
8 1288
 
6.3%
7 1187
 
5.8%
4 1074
 
5.3%
1 887
 
4.4%
Other values (4) 452
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20321
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 3390
16.7%
0 2849
14.0%
3 2848
14.0%
6 2579
12.7%
2 2139
10.5%
5 1628
8.0%
8 1288
 
6.3%
7 1187
 
5.8%
4 1074
 
5.3%
1 887
 
4.4%
Other values (4) 452
 
2.2%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct459
Distinct (%)27.3%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean55011.734
Minimum54001
Maximum56468
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.9 KiB
2024-03-14T08:43:59.749696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54001
5-th percentile54082.1
Q154593
median54956
Q355311
95-th percentile56307
Maximum56468
Range2467
Interquartile range (IQR)718

Descriptive statistics

Standard deviation639.17533
Coefficient of variation (CV)0.011618891
Kurtosis-0.30653714
Mean55011.734
Median Absolute Deviation (MAD)360
Skewness0.56826969
Sum92584748
Variance408545.11
MonotonicityNot monotonic
2024-03-14T08:43:59.899433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
56163 24
 
1.4%
55018 21
 
1.2%
54893 20
 
1.2%
54545 19
 
1.1%
56162 19
 
1.1%
54946 19
 
1.1%
54593 19
 
1.1%
55038 17
 
1.0%
55122 16
 
1.0%
54091 16
 
1.0%
Other values (449) 1493
88.7%
ValueCountFrequency (%)
54001 3
0.2%
54005 1
 
0.1%
54011 3
0.2%
54013 6
0.4%
54021 4
0.2%
54022 7
0.4%
54023 1
 
0.1%
54024 1
 
0.1%
54025 6
0.4%
54026 2
 
0.1%
ValueCountFrequency (%)
56468 4
 
0.2%
56455 3
 
0.2%
56448 1
 
0.1%
56438 2
 
0.1%
56437 1
 
0.1%
56436 3
 
0.2%
56433 10
0.6%
56432 13
0.8%
56416 1
 
0.1%
56415 3
 
0.2%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
보건의료과
1684 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
보건의료과 1684
100.0%

Length

2024-03-14T08:44:00.013764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T08:44:00.093162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보건의료과 1684
100.0%

공개여부
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
공개
1684 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공개 1684
100.0%

Length

2024-03-14T08:44:00.170676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T08:44:00.250939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 1684
100.0%

작성일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
2015.1
1684 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015.1
2nd row2015.1
3rd row2015.1
4th row2015.1
5th row2015.1

Common Values

ValueCountFrequency (%)
2015.1 1684
100.0%

Length

2024-03-14T08:44:00.343463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T08:44:00.420838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015.1 1684
100.0%

갱신주기
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.3 KiB
1년
1684 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1년
2nd row1년
3rd row1년
4th row1년
5th row1년

Common Values

ValueCountFrequency (%)
1년 1684
100.0%

Length

2024-03-14T08:44:00.498600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T08:44:00.572810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 1684
100.0%

Interactions

2024-03-14T08:43:56.682970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:43:56.535357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:43:56.754815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:43:56.612326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T08:44:00.623391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명병원구분우편번호
순번1.0000.8810.0720.928
시군명0.8811.0000.0000.984
병원구분0.0720.0001.0000.000
우편번호0.9280.9840.0001.000
2024-03-14T08:44:00.699084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명병원구분
시군명1.0000.000
병원구분0.0001.000
2024-03-14T08:44:00.768841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번우편번호시군명병원구분
순번1.0000.3230.6180.036
우편번호0.3231.0000.9250.000
시군명0.6180.9251.0000.000
병원구분0.0360.0000.0001.000

Missing values

2024-03-14T08:43:56.856333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T08:43:56.968807image/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

순번시군명병원명병원구분도로명주소전화번호우편번호자료출처공개여부작성일갱신주기
01익산시우리가정의원의원익산시 동천로7길 29063-843-160054610보건의료과공개2015.11년
12익산시상아치과의원치과의원익산시 고봉로14길 4 (영등동)063-841-728154628보건의료과공개2015.11년
23익산시즐거운치과의원치과의원익산시 동서로 229 (남중동)063-852-340054633보건의료과공개2015.11년
34익산시하종영내과의원의원익산시 동서로 229063-842-089054633보건의료과공개2015.11년
45익산시제일산부인과의원산부인과익산시 동서로 231 (남중동)063-840-750054633보건의료과공개2015.11년
56익산시새소망정형외과의원의원익산시 동서로 222 (남중동)063-851-980054619보건의료과공개2015.11년
67익산시굿모닝치과의원치과의원익산시 고현로 111 (모현동1가)063-851-287754659보건의료과공개2015.11년
78익산시으뜸정형외과의원의원익산시 고현로 112 (모현동1가)063-841-751154661보건의료과공개2015.11년
89익산시김래형치과의원치과의원익산시 고현로 101063-853-281354659보건의료과공개2015.11년
910익산시이진아소아청소년과의원의원익산시 고현로7길 4063-842-475854659보건의료과공개2015.11년
순번시군명병원명병원구분도로명주소전화번호우편번호자료출처공개여부작성일갱신주기
16741675전주시삼성가정의학과의원의원전주시 완산구 난전들로 266 (삼천동1가)063-285-600155132보건의료과공개2015.11년
16751676전주시굿모닝치과의원치과의원전주시 완산구 난전들로 266 (삼천동1가)063-227-287655132보건의료과공개2015.11년
16761677전주시큰나무의원의원전주시 완산구 기린대로 170 (중노송동)063-286-758255005보건의료과공개2015.11년
16771678전주시선치과의원치과의원전주시 완산구 기린대로 170 (중노송동)063-285-227555005보건의료과공개2015.11년
16781679전주시평화성모가정의학과의원의원전주시 완산구 모악로 4679 (평화동2가)063-221-7255~655135보건의료과공개2015.11년
16791680전주시유로진남성의원의원전주시 완산구 백제대로 400 (서신동)063-277-333854940보건의료과공개2015.11년
16801681전주시예스의원의원전주시 완산구 백제대로 400063-255-750254940보건의료과공개2015.11년
16811682전주시문이비인후과의원의원전주시 완산구 당산로 49063-253-399354948보건의료과공개2015.11년
16821683전주시이로운치과의원치과의원전주시 완산구 당산로 49063-274-287454948보건의료과공개2015.11년
16831684전주시정치과의원치과의원전주시 완산구 백제대로 110 (효자동1가)063-222-287555093보건의료과공개2015.11년