Overview

Dataset statistics

Number of variables9
Number of observations1266
Missing cells26
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory92.9 KiB
Average record size in memory75.1 B

Variable types

Categorical3
Text3
Numeric3

Dataset

Description병원평가정보(질병-만성폐쇄성폐질환) 현황
Author건강보험심사평가원
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=6JIDC14KLPHQPUTE83T521407615&infSeq=1

Alerts

평가내역 has constant value ""Constant
소재지우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
평가등급 is highly imbalanced (61.8%)Imbalance
소재지도로명주소 has 17 (1.3%) missing valuesMissing
소재지지번주소 has unique valuesUnique

Reproduction

Analysis started2023-12-10 22:49:51.492113
Analysis finished2023-12-10 22:49:53.511175
Duration2.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
수원시
121 
성남시
107 
부천시
92 
고양시
82 
용인시
 
78
Other values (26)
786 

Length

Max length4
Median length3
Mean length3.1034755
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시흥시
2nd row시흥시
3rd row포천시
4th row시흥시
5th row의정부시

Common Values

ValueCountFrequency (%)
수원시 121
 
9.6%
성남시 107
 
8.5%
부천시 92
 
7.3%
고양시 82
 
6.5%
용인시 78
 
6.2%
남양주시 62
 
4.9%
의정부시 59
 
4.7%
안산시 56
 
4.4%
화성시 56
 
4.4%
평택시 53
 
4.2%
Other values (21) 500
39.5%

Length

2023-12-11T07:49:53.587908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 121
 
9.6%
성남시 107
 
8.5%
부천시 92
 
7.3%
고양시 82
 
6.5%
용인시 78
 
6.2%
남양주시 62
 
4.9%
의정부시 59
 
4.7%
안산시 56
 
4.4%
화성시 56
 
4.4%
평택시 53
 
4.2%
Other values (21) 500
39.5%

기관명
Text

Distinct1100
Distinct (%)86.9%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
2023-12-11T07:49:53.874107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length7.371248
Min length3

Characters and Unicode

Total characters9332
Distinct characters370
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1016 ?
Unique (%)80.3%

Sample

1st row의료법인 남촌의료재단 시화병원
2nd row의료법인 녹향의료재단 신천연합병원
3rd row의료법인일심의료재단우리병원
4th row이연정내과의원
5th row이재균내과의원
ValueCountFrequency (%)
의료법인 14
 
1.1%
서울내과의원 9
 
0.7%
연세내과의원 9
 
0.7%
우리내과의원 8
 
0.6%
속편한내과의원 8
 
0.6%
김내과의원 7
 
0.5%
서울삼성내과의원 5
 
0.4%
우리의원 5
 
0.4%
서울가정의학과의원 4
 
0.3%
현내과의원 4
 
0.3%
Other values (1129) 1255
94.5%
2023-12-11T07:49:54.336523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 1312
 
14.1%
의 1239
 
13.3%
과 760
 
8.1%
내 591
 
6.3%
병 191
 
2.0%
성 166
 
1.8%
인 129
 
1.4%
한 127
 
1.4%
이 125
 
1.3%
정 124
 
1.3%
Other values (360) 4568
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9189
98.5%
Space Separator 62
 
0.7%
Decimal Number 51
 
0.5%
Uppercase Letter 13
 
0.1%
Close Punctuation 6
 
0.1%
Open Punctuation 5
 
0.1%
Lowercase Letter 4
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 1312
 
14.3%
의 1239
 
13.5%
과 760
 
8.3%
내 591
 
6.4%
병 191
 
2.1%
성 166
 
1.8%
인 129
 
1.4%
한 127
 
1.4%
이 125
 
1.4%
정 124
 
1.3%
Other values (341) 4425
48.2%
Uppercase Letter
ValueCountFrequency (%)
S 3
23.1%
O 3
23.1%
K 3
23.1%
D 2
15.4%
W 1
 
7.7%
T 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
3 13
25.5%
6 12
23.5%
5 12
23.5%
2 7
13.7%
1 7
13.7%
Lowercase Letter
ValueCountFrequency (%)
r 2
50.0%
e 1
25.0%
h 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
· 1
50.0%
Space Separator
ValueCountFrequency (%)
62
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9189
98.5%
Common 126
 
1.4%
Latin 17
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 1312
 
14.3%
의 1239
 
13.5%
과 760
 
8.3%
내 591
 
6.4%
병 191
 
2.1%
성 166
 
1.8%
인 129
 
1.4%
한 127
 
1.4%
이 125
 
1.4%
정 124
 
1.3%
Other values (341) 4425
48.2%
Common
ValueCountFrequency (%)
62
49.2%
3 13
 
10.3%
6 12
 
9.5%
5 12
 
9.5%
2 7
 
5.6%
1 7
 
5.6%
) 6
 
4.8%
( 5
 
4.0%
. 1
 
0.8%
· 1
 
0.8%
Latin
ValueCountFrequency (%)
S 3
17.6%
O 3
17.6%
K 3
17.6%
r 2
11.8%
D 2
11.8%
W 1
 
5.9%
e 1
 
5.9%
h 1
 
5.9%
T 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9189
98.5%
ASCII 142
 
1.5%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 1312
 
14.3%
의 1239
 
13.5%
과 760
 
8.3%
내 591
 
6.4%
병 191
 
2.1%
성 166
 
1.8%
인 129
 
1.4%
한 127
 
1.4%
이 125
 
1.4%
정 124
 
1.3%
Other values (341) 4425
48.2%
ASCII
ValueCountFrequency (%)
62
43.7%
3 13
 
9.2%
6 12
 
8.5%
5 12
 
8.5%
2 7
 
4.9%
1 7
 
4.9%
) 6
 
4.2%
( 5
 
3.5%
S 3
 
2.1%
O 3
 
2.1%
Other values (8) 12
 
8.5%
None
ValueCountFrequency (%)
· 1
100.0%

평가내역
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
만성폐쇄성폐질환
1266 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
만성폐쇄성폐질환 1266
100.0%

Length

2023-12-11T07:49:54.495329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:49:54.610077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
만성폐쇄성폐질환 1266
100.0%

평가등급
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
등급제외
1056 
1등급
 
79
2등급
 
60
3등급
 
41
4등급
 
15

Length

Max length4
Median length4
Mean length3.8341232
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2등급
2nd row2등급
3rd row2등급
4th row2등급
5th row2등급

Common Values

ValueCountFrequency (%)
등급제외 1056
83.4%
1등급 79
 
6.2%
2등급 60
 
4.7%
3등급 41
 
3.2%
4등급 15
 
1.2%
5등급 15
 
1.2%

Length

2023-12-11T07:49:54.987722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:49:55.126791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
등급제외 1056
83.4%
1등급 79
 
6.2%
2등급 60
 
4.7%
3등급 41
 
3.2%
4등급 15
 
1.2%
5등급 15
 
1.2%

소재지도로명주소
Text

MISSING 

Distinct1224
Distinct (%)98.0%
Missing17
Missing (%)1.3%
Memory size10.0 KiB
2023-12-11T07:49:55.442256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length18.325861
Min length13

Characters and Unicode

Total characters22889
Distinct characters283
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

Unique1200 ?
Unique (%)96.1%

Sample

1st row경기도 시흥시 군자천로 381
2nd row경기도 포천시 소흘읍 호국로 661
3rd row경기도 시흥시 비둘기공원1길 25
4th row경기도 의정부시 의정로 191
5th row경기도 구리시 동구릉로 65
ValueCountFrequency (%)
경기도 1249
 
21.9%
수원시 120
 
2.1%
성남시 107
 
1.9%
부천시 90
 
1.6%
고양시 79
 
1.4%
용인시 77
 
1.4%
남양주시 61
 
1.1%
의정부시 59
 
1.0%
화성시 56
 
1.0%
안산시 56
 
1.0%
Other values (1396) 3739
65.7%
2023-12-11T07:49:55.887762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4444
19.4%
경 1312
 
5.7%
기 1287
 
5.6%
시 1276
 
5.6%
도 1275
 
5.6%
로 1207
 
5.3%
1 775
 
3.4%
구 537
 
2.3%
2 518
 
2.3%
3 455
 
2.0%
Other values (273) 9803
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14506
63.4%
Space Separator 4444
 
19.4%
Decimal Number 3824
 
16.7%
Dash Punctuation 115
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 1312
 
9.0%
기 1287
 
8.9%
시 1276
 
8.8%
도 1275
 
8.8%
로 1207
 
8.3%
구 537
 
3.7%
양 335
 
2.3%
길 267
 
1.8%
남 266
 
1.8%
안 253
 
1.7%
Other values (261) 6491
44.7%
Decimal Number
ValueCountFrequency (%)
1 775
20.3%
2 518
13.5%
3 455
11.9%
5 325
8.5%
4 323
8.4%
6 307
 
8.0%
7 302
 
7.9%
0 294
 
7.7%
8 276
 
7.2%
9 249
 
6.5%
Space Separator
ValueCountFrequency (%)
4444
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 115
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14506
63.4%
Common 8383
36.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 1312
 
9.0%
기 1287
 
8.9%
시 1276
 
8.8%
도 1275
 
8.8%
로 1207
 
8.3%
구 537
 
3.7%
양 335
 
2.3%
길 267
 
1.8%
남 266
 
1.8%
안 253
 
1.7%
Other values (261) 6491
44.7%
Common
ValueCountFrequency (%)
4444
53.0%
1 775
 
9.2%
2 518
 
6.2%
3 455
 
5.4%
5 325
 
3.9%
4 323
 
3.9%
6 307
 
3.7%
7 302
 
3.6%
0 294
 
3.5%
8 276
 
3.3%
Other values (2) 364
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14506
63.4%
ASCII 8383
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4444
53.0%
1 775
 
9.2%
2 518
 
6.2%
3 455
 
5.4%
5 325
 
3.9%
4 323
 
3.9%
6 307
 
3.7%
7 302
 
3.6%
0 294
 
3.5%
8 276
 
3.3%
Other values (2) 364
 
4.3%
Hangul
ValueCountFrequency (%)
경 1312
 
9.0%
기 1287
 
8.9%
시 1276
 
8.8%
도 1275
 
8.8%
로 1207
 
8.3%
구 537
 
3.7%
양 335
 
2.3%
길 267
 
1.8%
남 266
 
1.8%
안 253
 
1.7%
Other values (261) 6491
44.7%

소재지지번주소
Text

UNIQUE 

Distinct1266
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size10.0 KiB
2023-12-11T07:49:56.203806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length87
Median length51
Mean length28.958136
Min length14

Characters and Unicode

Total characters36661
Distinct characters429
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1266 ?
Unique (%)100.0%

Sample

1st row경기도 시흥시 정왕동 1842-3번지 시화병원
2nd row경기도 시흥시 대야동 469-3번지 복지로 61, 2층
3rd row경기도 포천시 소흘읍 송우리 116-11번지 661호
4th row경기도 시흥시 대야동 541-15번지 우곡프라자 202호
5th row경기도 의정부시 가능동 672-41번지
ValueCountFrequency (%)
경기도 1266
 
16.8%
2층 190
 
2.5%
수원시 121
 
1.6%
성남시 107
 
1.4%
3층 102
 
1.4%
부천시 92
 
1.2%
고양시 82
 
1.1%
용인시 78
 
1.0%
4층 65
 
0.9%
남양주시 62
 
0.8%
Other values (2639) 5375
71.3%
2023-12-11T07:49:56.694986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6274
 
17.1%
지 1380
 
3.8%
1 1333
 
3.6%
기 1313
 
3.6%
도 1291
 
3.5%
시 1290
 
3.5%
경 1287
 
3.5%
번 1265
 
3.5%
동 1219
 
3.3%
2 1207
 
3.3%
Other values (419) 18802
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20952
57.2%
Decimal Number 7895
 
21.5%
Space Separator 6274
 
17.1%
Dash Punctuation 966
 
2.6%
Other Punctuation 298
 
0.8%
Math Symbol 115
 
0.3%
Uppercase Letter 110
 
0.3%
Close Punctuation 23
 
0.1%
Open Punctuation 23
 
0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 1380
 
6.6%
기 1313
 
6.3%
도 1291
 
6.2%
시 1290
 
6.2%
경 1287
 
6.1%
번 1265
 
6.0%
동 1219
 
5.8%
층 576
 
2.7%
구 542
 
2.6%
호 521
 
2.5%
Other values (373) 10268
49.0%
Uppercase Letter
ValueCountFrequency (%)
A 18
16.4%
C 13
11.8%
B 11
 
10.0%
S 7
 
6.4%
W 6
 
5.5%
D 5
 
4.5%
R 5
 
4.5%
L 5
 
4.5%
E 5
 
4.5%
T 5
 
4.5%
Other values (14) 30
27.3%
Decimal Number
ValueCountFrequency (%)
1 1333
16.9%
2 1207
15.3%
3 1021
12.9%
0 1010
12.8%
4 845
10.7%
5 653
8.3%
6 519
 
6.6%
7 461
 
5.8%
8 448
 
5.7%
9 398
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 280
94.0%
. 14
 
4.7%
& 2
 
0.7%
/ 2
 
0.7%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅲ 1
50.0%
Space Separator
ValueCountFrequency (%)
6274
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 966
100.0%
Math Symbol
ValueCountFrequency (%)
~ 115
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20952
57.2%
Common 15594
42.5%
Latin 115
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 1380
 
6.6%
기 1313
 
6.3%
도 1291
 
6.2%
시 1290
 
6.2%
경 1287
 
6.1%
번 1265
 
6.0%
동 1219
 
5.8%
층 576
 
2.7%
구 542
 
2.6%
호 521
 
2.5%
Other values (373) 10268
49.0%
Latin
ValueCountFrequency (%)
A 18
15.7%
C 13
 
11.3%
B 11
 
9.6%
S 7
 
6.1%
W 6
 
5.2%
D 5
 
4.3%
R 5
 
4.3%
L 5
 
4.3%
E 5
 
4.3%
T 5
 
4.3%
Other values (17) 35
30.4%
Common
ValueCountFrequency (%)
6274
40.2%
1 1333
 
8.5%
2 1207
 
7.7%
3 1021
 
6.5%
0 1010
 
6.5%
- 966
 
6.2%
4 845
 
5.4%
5 653
 
4.2%
6 519
 
3.3%
7 461
 
3.0%
Other values (9) 1305
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20952
57.2%
ASCII 15707
42.8%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6274
39.9%
1 1333
 
8.5%
2 1207
 
7.7%
3 1021
 
6.5%
0 1010
 
6.4%
- 966
 
6.2%
4 845
 
5.4%
5 653
 
4.2%
6 519
 
3.3%
7 461
 
2.9%
Other values (34) 1418
 
9.0%
Hangul
ValueCountFrequency (%)
지 1380
 
6.6%
기 1313
 
6.3%
도 1291
 
6.2%
시 1290
 
6.2%
경 1287
 
6.1%
번 1265
 
6.0%
동 1219
 
5.8%
층 576
 
2.7%
구 542
 
2.6%
호 521
 
2.5%
Other values (373) 10268
49.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅲ 1
50.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct918
Distinct (%)72.6%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean14155.65
Minimum10011
Maximum18611
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.3 KiB
2023-12-11T07:49:56.875873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10011
5-th percentile10336.4
Q112011
median14092
Q316436
95-th percentile18136
Maximum18611
Range8600
Interquartile range (IQR)4425

Descriptive statistics

Standard deviation2497.1941
Coefficient of variation (CV)0.17640971
Kurtosis-1.1841306
Mean14155.65
Median Absolute Deviation (MAD)2224
Skewness0.055205942
Sum17906897
Variance6235978.4
MonotonicityNot monotonic
2023-12-11T07:49:57.030733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15865 7
 
0.6%
13618 6
 
0.5%
14072 5
 
0.4%
10924 5
 
0.4%
10905 5
 
0.4%
12084 4
 
0.3%
17936 4
 
0.3%
11940 4
 
0.3%
13599 4
 
0.3%
16393 4
 
0.3%
Other values (908) 1217
96.1%
ValueCountFrequency (%)
10011 1
 
0.1%
10018 3
0.2%
10040 1
 
0.1%
10059 1
 
0.1%
10060 1
 
0.1%
10067 1
 
0.1%
10068 1
 
0.1%
10070 1
 
0.1%
10071 2
0.2%
10073 1
 
0.1%
ValueCountFrequency (%)
18611 2
0.2%
18600 1
 
0.1%
18598 1
 
0.1%
18594 1
 
0.1%
18593 4
0.3%
18592 1
 
0.1%
18591 1
 
0.1%
18568 2
0.2%
18567 2
0.2%
18550 2
0.2%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct1237
Distinct (%)98.0%
Missing4
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean37.449103
Minimum36.960955
Maximum38.100617
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.3 KiB
2023-12-11T07:49:57.212077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.960955
5-th percentile37.080747
Q137.293352
median37.431006
Q337.634004
95-th percentile37.818492
Maximum38.100617
Range1.1396613
Interquartile range (IQR)0.34065189

Descriptive statistics

Standard deviation0.21883966
Coefficient of variation (CV)0.0058436558
Kurtosis-0.35456415
Mean37.449103
Median Absolute Deviation (MAD)0.15547796
Skewness0.17031428
Sum47260.767
Variance0.047890799
MonotonicityNot monotonic
2023-12-11T07:49:57.378636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.3734813717 3
 
0.2%
37.2538663614 2
 
0.2%
37.6449290397 2
 
0.2%
37.7445955606 2
 
0.2%
37.7263677442 2
 
0.2%
37.4365775346 2
 
0.2%
37.3366662115 2
 
0.2%
37.6344413468 2
 
0.2%
37.2505690045 2
 
0.2%
37.4282853438 2
 
0.2%
Other values (1227) 1241
98.0%
(Missing) 4
 
0.3%
ValueCountFrequency (%)
36.9609553206 1
0.1%
36.9611007482 1
0.1%
36.9614956154 1
0.1%
36.9632453036 1
0.1%
36.9772202616 1
0.1%
36.9790863294 1
0.1%
36.9840497212 1
0.1%
36.9861754028 1
0.1%
36.9881523917 1
0.1%
36.9882692644 1
0.1%
ValueCountFrequency (%)
38.1006166517 1
0.1%
38.0991918519 1
0.1%
38.0910739209 1
0.1%
38.0903278355 1
0.1%
38.0256395132 1
0.1%
38.0243987043 1
0.1%
38.0235512237 1
0.1%
37.9998349286 1
0.1%
37.9592303481 1
0.1%
37.9583733138 1
0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct1237
Distinct (%)98.0%
Missing4
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean127.01987
Minimum126.58256
Maximum127.75346
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.3 KiB
2023-12-11T07:49:57.526786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.58256
5-th percentile126.74585
Q1126.84097
median127.03605
Q3127.13626
95-th percentile127.44655
Maximum127.75346
Range1.1709027
Interquartile range (IQR)0.29529409

Descriptive statistics

Standard deviation0.20585562
Coefficient of variation (CV)0.0016206568
Kurtosis0.4496104
Mean127.01987
Median Absolute Deviation (MAD)0.13308144
Skewness0.61913813
Sum160299.08
Variance0.042376537
MonotonicityNot monotonic
2023-12-11T07:49:57.688477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1196937543 3
 
0.2%
127.0744906955 2
 
0.2%
126.666513227 2
 
0.2%
127.0980642187 2
 
0.2%
127.0545873719 2
 
0.2%
126.8016249551 2
 
0.2%
126.7284520798 2
 
0.2%
127.2111574561 2
 
0.2%
127.0229215756 2
 
0.2%
126.9925450502 2
 
0.2%
Other values (1227) 1241
98.0%
(Missing) 4
 
0.3%
ValueCountFrequency (%)
126.5825555862 1
0.1%
126.5986406181 1
0.1%
126.6001738151 1
0.1%
126.601732979 1
0.1%
126.623439457 1
0.1%
126.6261996286 1
0.1%
126.6272018156 1
0.1%
126.6273248993 1
0.1%
126.6275192643 1
0.1%
126.6329200073 1
0.1%
ValueCountFrequency (%)
127.7534583305 1
0.1%
127.6691950314 1
0.1%
127.6686207363 1
0.1%
127.6439730063 1
0.1%
127.6386455655 1
0.1%
127.6372797797 1
0.1%
127.6372350256 1
0.1%
127.6367504612 1
0.1%
127.6363312817 1
0.1%
127.6358927578 1
0.1%

Interactions

2023-12-11T07:49:52.876237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:52.289903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:52.573371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:52.965362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:52.374565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:52.664957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:53.064513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:52.479322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:52.769676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:49:57.780559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명평가등급소재지우편번호WGS84위도WGS84경도
시군명1.0000.1860.9910.9690.940
평가등급0.1861.0000.0000.1190.049
소재지우편번호0.9910.0001.0000.9130.862
WGS84위도0.9690.1190.9131.0000.617
WGS84경도0.9400.0490.8620.6171.000
2023-12-11T07:49:57.873268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평가등급시군명
평가등급1.0000.082
시군명0.0821.000
2023-12-11T07:49:57.953866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명평가등급
소재지우편번호1.000-0.9120.1320.9210.000
WGS84위도-0.9121.000-0.1650.8020.063
WGS84경도0.132-0.1651.0000.6970.026
시군명0.9210.8020.6971.0000.082
평가등급0.0000.0630.0260.0821.000

Missing values

2023-12-11T07:49:53.211890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:49:53.340835image/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.
2023-12-11T07:49:53.443543image/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

시군명기관명평가내역평가등급소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0시흥시의료법인 남촌의료재단 시화병원만성폐쇄성폐질환2등급경기도 시흥시 군자천로 381경기도 시흥시 정왕동 1842-3번지 시화병원1503437.349909126.73701
1시흥시의료법인 녹향의료재단 신천연합병원만성폐쇄성폐질환2등급<NA>경기도 시흥시 대야동 469-3번지 복지로 61, 2층1490537.444527126.789376
2포천시의료법인일심의료재단우리병원만성폐쇄성폐질환2등급경기도 포천시 소흘읍 호국로 661경기도 포천시 소흘읍 송우리 116-11번지 661호1117437.827488127.148136
3시흥시이연정내과의원만성폐쇄성폐질환2등급경기도 시흥시 비둘기공원1길 25경기도 시흥시 대야동 541-15번지 우곡프라자 202호1491237.441492126.791292
4의정부시이재균내과의원만성폐쇄성폐질환2등급경기도 의정부시 의정로 191경기도 의정부시 가능동 672-41번지1167537.749922127.034173
5구리시재단법인원진녹색병원만성폐쇄성폐질환2등급경기도 구리시 동구릉로 65경기도 구리시 인창동 527-44번지1191937.605925127.133888
6군포시천내과의원만성폐쇄성폐질환2등급경기도 군포시 군포로 494경기도 군포시 당동 898번지 당동빌딩 205호1585637.350454126.944835
7평택시평택중앙내과의원만성폐쇄성폐질환2등급경기도 평택시 중앙로 29경기도 평택시 통복동 84-3번지1789436.995274127.08641
8안성시하나로연합의원만성폐쇄성폐질환2등급경기도 안성시 중앙로 370경기도 안성시 석정동 22-1번지 하평플리스 4층1758137.007621127.267903
9파주시황효주내과의원만성폐쇄성폐질환2등급<NA>경기도 파주시 문산읍 문산리 17-25번지 2층 청도훼미리코아1082437.855776126.786662
시군명기관명평가내역평가등급소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
1256군포시연세속시원의원만성폐쇄성폐질환등급제외경기도 군포시 번영로 502경기도 군포시 금정동 874-1번지 역사상가 301,307,311,313,314,315,316,405호1586237.357611126.933411
1257부천시연세수내과의원만성폐쇄성폐질환등급제외경기도 부천시 옥길로 111경기도 부천시 옥길동 726-5번지 드림탑프라자 501호,502호,503호1478437.467116126.821843
1258고양시연세신일의원만성폐쇄성폐질환등급제외경기도 고양시 덕양구 호국로 788경기도 고양시 덕양구 성사동 698-15번지 2층1046437.656363126.836281
1259고양시연세엘내과의원만성폐쇄성폐질환등급제외경기도 고양시 덕양구 동세로 63경기도 고양시 덕양구 삼송동 337-3번지 3,4층1058837.648133126.884315
1260오산시연세원내과의원만성폐쇄성폐질환등급제외경기도 오산시 내삼미로 93경기도 오산시 수청동 620-1번지 백현프라자 3층1811437.170536127.065789
1261수원시연세이비인후과의원만성폐쇄성폐질환등급제외경기도 수원시 장안구 파장로 82경기도 수원시 장안구 파장동 580-8번지1634937.306588126.992066
1262성남시연세제일내과의원만성폐쇄성폐질환등급제외경기도 성남시 중원구 성남대로1148번길 2경기도 성남시 중원구 성남동 3492번지 소평빌딩 5층1336537.432273127.129513
1263수원시연세진내과의원만성폐쇄성폐질환등급제외경기도 수원시 영통구 광교호수공원로 277경기도 수원시 영통구 원천동 589번지 중흥 S-클래스 B2층 24~27호1651737.282784127.05752
1264양평군연세푸르른내과의원만성폐쇄성폐질환등급제외경기도 양평군 양평읍 역전길 24경기도 양평군 양평읍 양근리 376-4번지 오성프라자 402호1255637.492245127.491052
1265평택시연세한빛외과의원만성폐쇄성폐질환등급제외경기도 평택시 서정역로36번길 24-10경기도 평택시 이충동 460번지1777937.05706127.057023