Overview

Dataset statistics

Number of variables9
Number of observations25
Missing cells3
Missing cells (%)1.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory81.3 B

Variable types

Text4
Numeric4
Categorical1

Dataset

Description응급의료센터 현황_인허가
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=2V907117JYW4JNDSN2WK159326&infSeq=1

Alerts

영업상태명 has constant value ""Constant
소재지우편번호 is highly overall correlated with WGS84위도High correlation
WGS84위도 is highly overall correlated with 소재지우편번호High correlation
소재지도로명주소 has 2 (8.0%) missing valuesMissing
소재지우편번호 has 1 (4.0%) missing valuesMissing
사업장명 has unique valuesUnique
소재지지번주소 has unique valuesUnique
WGS84위도 has unique valuesUnique
WGS84경도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 22:14:49.400817
Analysis finished2023-12-10 22:14:51.867938
Duration2.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

Distinct14
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-11T07:14:51.968970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.12
Min length3

Characters and Unicode

Total characters78
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)24.0%

Sample

1st row고양시
2nd row고양시
3rd row고양시
4th row고양시
5th row광명시
ValueCountFrequency (%)
고양시 4
16.0%
성남시 3
12.0%
군포시 2
8.0%
남양주시 2
8.0%
수원시 2
8.0%
안산시 2
8.0%
안양시 2
8.0%
용인시 2
8.0%
광명시 1
 
4.0%
구리시 1
 
4.0%
Other values (4) 4
16.0%
2023-12-11T07:14:52.230625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 25
32.1%
양 8
 
10.3%
남 5
 
6.4%
고 4
 
5.1%
안 4
 
5.1%
성 3
 
3.8%
포 3
 
3.8%
주 3
 
3.8%
산 2
 
2.6%
부 2
 
2.6%
Other values (14) 19
24.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 78
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 25
32.1%
양 8
 
10.3%
남 5
 
6.4%
고 4
 
5.1%
안 4
 
5.1%
성 3
 
3.8%
포 3
 
3.8%
주 3
 
3.8%
산 2
 
2.6%
부 2
 
2.6%
Other values (14) 19
24.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 78
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 25
32.1%
양 8
 
10.3%
남 5
 
6.4%
고 4
 
5.1%
안 4
 
5.1%
성 3
 
3.8%
포 3
 
3.8%
주 3
 
3.8%
산 2
 
2.6%
부 2
 
2.6%
Other values (14) 19
24.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 78
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 25
32.1%
양 8
 
10.3%
남 5
 
6.4%
고 4
 
5.1%
안 4
 
5.1%
성 3
 
3.8%
포 3
 
3.8%
주 3
 
3.8%
산 2
 
2.6%
부 2
 
2.6%
Other values (14) 19
24.4%

사업장명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-11T07:14:52.417006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length10.16
Min length4

Characters and Unicode

Total characters254
Distinct characters77
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

Unique25 ?
Unique (%)100.0%

Sample

1st row동국대학교 일산불교병원
2nd row의료법인 명지의료재단 명지병원
3rd row인제대학교 일산백병원
4th row국민건강보험공단 일산병원
5th row의료법인 광명성애병원
ValueCountFrequency (%)
의료법인 3
 
7.0%
가톨릭대학교 2
 
4.7%
동국대학교 1
 
2.3%
고대안산병원 1
 
2.3%
포천중문의과대학교 1
 
2.3%
분당차병원 1
 
2.3%
성빈센트병원 1
 
2.3%
아주대학교병원 1
 
2.3%
대아의료재단 1
 
2.3%
한도병원 1
 
2.3%
Other values (30) 30
69.8%
2023-12-11T07:14:52.733584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 28
 
11.0%
병 25
 
9.8%
18
 
7.1%
대 13
 
5.1%
의 12
 
4.7%
학 11
 
4.3%
교 11
 
4.3%
료 8
 
3.1%
단 5
 
2.0%
산 5
 
2.0%
Other values (67) 118
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 234
92.1%
Space Separator 18
 
7.1%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 28
 
12.0%
병 25
 
10.7%
대 13
 
5.6%
의 12
 
5.1%
학 11
 
4.7%
교 11
 
4.7%
료 8
 
3.4%
단 5
 
2.1%
산 5
 
2.1%
양 5
 
2.1%
Other values (64) 111
47.4%
Space Separator
ValueCountFrequency (%)
18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 234
92.1%
Common 20
 
7.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 28
 
12.0%
병 25
 
10.7%
대 13
 
5.6%
의 12
 
5.1%
학 11
 
4.7%
교 11
 
4.7%
료 8
 
3.4%
단 5
 
2.1%
산 5
 
2.1%
양 5
 
2.1%
Other values (64) 111
47.4%
Common
ValueCountFrequency (%)
18
90.0%
) 1
 
5.0%
( 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 234
92.1%
ASCII 20
 
7.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 28
 
12.0%
병 25
 
10.7%
대 13
 
5.6%
의 12
 
5.1%
학 11
 
4.7%
교 11
 
4.7%
료 8
 
3.4%
단 5
 
2.1%
산 5
 
2.1%
양 5
 
2.1%
Other values (64) 111
47.4%
ASCII
ValueCountFrequency (%)
18
90.0%
) 1
 
5.0%
( 1
 
5.0%

인허가일자
Real number (ℝ)

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20048206
Minimum19950728
Maximum20151021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-11T07:14:52.846417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19950728
5-th percentile19982439
Q120000307
median20040408
Q320090227
95-th percentile20131204
Maximum20151021
Range200293
Interquartile range (IQR)89920

Descriptive statistics

Standard deviation54531.499
Coefficient of variation (CV)0.0027200189
Kurtosis-0.96482987
Mean20048206
Median Absolute Deviation (MAD)40497
Skewness0.21326434
Sum5.0120515 × 108
Variance2.9736844 × 109
MonotonicityNot monotonic
2023-12-11T07:14:52.963611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
20000307 2
 
8.0%
20000731 2
 
8.0%
20081229 1
 
4.0%
19950728 1
 
4.0%
20131128 1
 
4.0%
20090227 1
 
4.0%
20080905 1
 
4.0%
19990129 1
 
4.0%
20040520 1
 
4.0%
20000119 1
 
4.0%
Other values (13) 13
52.0%
ValueCountFrequency (%)
19950728 1
4.0%
19980516 1
4.0%
19990129 1
4.0%
19990911 1
4.0%
20000119 1
4.0%
20000307 2
8.0%
20000731 2
8.0%
20030510 1
4.0%
20030701 1
4.0%
20040221 1
4.0%
ValueCountFrequency (%)
20151021 1
4.0%
20131223 1
4.0%
20131128 1
4.0%
20110329 1
4.0%
20110216 1
4.0%
20090522 1
4.0%
20090227 1
4.0%
20081229 1
4.0%
20080905 1
4.0%
20070307 1
4.0%

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
운영중
25 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 25
100.0%

Length

2023-12-11T07:14:53.100698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:14:53.181211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 25
100.0%

소재지도로명주소
Text

MISSING 

Distinct23
Distinct (%)100.0%
Missing2
Missing (%)8.0%
Memory size332.0 B
2023-12-11T07:14:53.357373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length21.304348
Min length15

Characters and Unicode

Total characters490
Distinct characters90
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row경기도 고양시 일산동구 동국로 27
2nd row경기도 고양시 덕양구 화수로14번길 55
3rd row경기도 고양시 일산서구 주화로 170
4th row경기도 고양시 일산동구 일산로 100
5th row경기도 광명시 디지털로 36
ValueCountFrequency (%)
경기도 23
 
19.8%
고양시 4
 
3.4%
분당구 3
 
2.6%
성남시 3
 
2.6%
남양주시 2
 
1.7%
오남읍 2
 
1.7%
일산동구 2
 
1.7%
중부대로 2
 
1.7%
용인시 2
 
1.7%
안산시 2
 
1.7%
Other values (67) 71
61.2%
2023-12-11T07:14:53.683149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
93
19.0%
경 24
 
4.9%
기 24
 
4.9%
도 23
 
4.7%
로 23
 
4.7%
시 23
 
4.7%
1 17
 
3.5%
구 17
 
3.5%
동 11
 
2.2%
양 10
 
2.0%
Other values (80) 225
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 306
62.4%
Space Separator 93
 
19.0%
Decimal Number 76
 
15.5%
Open Punctuation 7
 
1.4%
Close Punctuation 7
 
1.4%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 24
 
7.8%
기 24
 
7.8%
도 23
 
7.5%
로 23
 
7.5%
시 23
 
7.5%
구 17
 
5.6%
동 11
 
3.6%
양 10
 
3.3%
산 8
 
2.6%
남 8
 
2.6%
Other values (66) 135
44.1%
Decimal Number
ValueCountFrequency (%)
1 17
22.4%
2 10
13.2%
0 9
11.8%
7 8
10.5%
3 7
9.2%
9 7
9.2%
5 7
9.2%
8 6
 
7.9%
4 4
 
5.3%
6 1
 
1.3%
Space Separator
ValueCountFrequency (%)
93
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 306
62.4%
Common 184
37.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 24
 
7.8%
기 24
 
7.8%
도 23
 
7.5%
로 23
 
7.5%
시 23
 
7.5%
구 17
 
5.6%
동 11
 
3.6%
양 10
 
3.3%
산 8
 
2.6%
남 8
 
2.6%
Other values (66) 135
44.1%
Common
ValueCountFrequency (%)
93
50.5%
1 17
 
9.2%
2 10
 
5.4%
0 9
 
4.9%
7 8
 
4.3%
3 7
 
3.8%
9 7
 
3.8%
( 7
 
3.8%
5 7
 
3.8%
) 7
 
3.8%
Other values (4) 12
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 306
62.4%
ASCII 184
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
93
50.5%
1 17
 
9.2%
2 10
 
5.4%
0 9
 
4.9%
7 8
 
4.3%
3 7
 
3.8%
9 7
 
3.8%
( 7
 
3.8%
5 7
 
3.8%
) 7
 
3.8%
Other values (4) 12
 
6.5%
Hangul
ValueCountFrequency (%)
경 24
 
7.8%
기 24
 
7.8%
도 23
 
7.5%
로 23
 
7.5%
시 23
 
7.5%
구 17
 
5.6%
동 11
 
3.6%
양 10
 
3.3%
산 8
 
2.6%
남 8
 
2.6%
Other values (66) 135
44.1%

소재지지번주소
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-11T07:14:53.877264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length23
Mean length21.24
Min length14

Characters and Unicode

Total characters531
Distinct characters87
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

Unique25 ?
Unique (%)100.0%

Sample

1st row경기도 고양시 일산동구 식사동 동국대일산불교종합병원
2nd row경기도 고양시 덕양구 화정동 697-24
3rd row경기도 고양시 일산서구 대화동 2240
4th row경기도 고양시 일산동구 백석동 1232
5th row경기도 광명시 철산동 389
ValueCountFrequency (%)
경기도 24
 
19.4%
고양시 4
 
3.2%
1호 4
 
3.2%
분당구 3
 
2.4%
성남시 3
 
2.4%
안산시 2
 
1.6%
안양시 2
 
1.6%
일산동구 2
 
1.6%
수원시 2
 
1.6%
4호 2
 
1.6%
Other values (69) 76
61.3%
2023-12-11T07:14:54.183901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
120
22.6%
동 26
 
4.9%
기 25
 
4.7%
경 24
 
4.5%
도 24
 
4.5%
시 24
 
4.5%
1 22
 
4.1%
구 17
 
3.2%
2 13
 
2.4%
지 12
 
2.3%
Other values (77) 224
42.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 314
59.1%
Space Separator 120
 
22.6%
Decimal Number 90
 
16.9%
Dash Punctuation 7
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 26
 
8.3%
기 25
 
8.0%
경 24
 
7.6%
도 24
 
7.6%
시 24
 
7.6%
구 17
 
5.4%
지 12
 
3.8%
양 11
 
3.5%
번 10
 
3.2%
호 10
 
3.2%
Other values (65) 131
41.7%
Decimal Number
ValueCountFrequency (%)
1 22
24.4%
2 13
14.4%
5 9
10.0%
3 8
 
8.9%
4 8
 
8.9%
0 7
 
7.8%
6 7
 
7.8%
9 7
 
7.8%
8 5
 
5.6%
7 4
 
4.4%
Space Separator
ValueCountFrequency (%)
120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 314
59.1%
Common 217
40.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 26
 
8.3%
기 25
 
8.0%
경 24
 
7.6%
도 24
 
7.6%
시 24
 
7.6%
구 17
 
5.4%
지 12
 
3.8%
양 11
 
3.5%
번 10
 
3.2%
호 10
 
3.2%
Other values (65) 131
41.7%
Common
ValueCountFrequency (%)
120
55.3%
1 22
 
10.1%
2 13
 
6.0%
5 9
 
4.1%
3 8
 
3.7%
4 8
 
3.7%
0 7
 
3.2%
6 7
 
3.2%
9 7
 
3.2%
- 7
 
3.2%
Other values (2) 9
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 314
59.1%
ASCII 217
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
120
55.3%
1 22
 
10.1%
2 13
 
6.0%
5 9
 
4.1%
3 8
 
3.7%
4 8
 
3.7%
0 7
 
3.2%
6 7
 
3.2%
9 7
 
3.2%
- 7
 
3.2%
Other values (2) 9
 
4.1%
Hangul
ValueCountFrequency (%)
동 26
 
8.3%
기 25
 
8.0%
경 24
 
7.6%
도 24
 
7.6%
시 24
 
7.6%
구 17
 
5.4%
지 12
 
3.8%
양 11
 
3.5%
번 10
 
3.2%
호 10
 
3.2%
Other values (65) 131
41.7%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct24
Distinct (%)100.0%
Missing1
Missing (%)4.0%
Infinite0
Infinite (%)0.0%
Mean13376.083
Minimum10099
Maximum17064
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-11T07:14:54.296695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10099
5-th percentile10334.1
Q111554.25
median13605
Q315358
95-th percentile16940.6
Maximum17064
Range6965
Interquartile range (IQR)3803.75

Descriptive statistics

Standard deviation2279.8441
Coefficient of variation (CV)0.17044183
Kurtosis-1.2835288
Mean13376.083
Median Absolute Deviation (MAD)1801
Skewness0.028101255
Sum321026
Variance5197689
MonotonicityNot monotonic
2023-12-11T07:14:54.421464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
10326 1
 
4.0%
13620 1
 
4.0%
10922 1
 
4.0%
11765 1
 
4.0%
17063 1
 
4.0%
17064 1
 
4.0%
14068 1
 
4.0%
14030 1
 
4.0%
15355 1
 
4.0%
15367 1
 
4.0%
Other values (14) 14
56.0%
ValueCountFrequency (%)
10099 1
4.0%
10326 1
4.0%
10380 1
4.0%
10444 1
4.0%
10475 1
4.0%
10922 1
4.0%
11765 1
4.0%
11923 1
4.0%
12045 1
4.0%
12048 1
4.0%
ValueCountFrequency (%)
17064 1
4.0%
17063 1
4.0%
16247 1
4.0%
15865 1
4.0%
15839 1
4.0%
15367 1
4.0%
15355 1
4.0%
14754 1
4.0%
14241 1
4.0%
14068 1
4.0%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.483581
Minimum37.23155
Maximum37.758287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-11T07:14:54.571877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.23155
5-th percentile37.274438
Q137.349706
median37.410163
Q337.645494
95-th percentile37.743525
Maximum37.758287
Range0.52673668
Interquartile range (IQR)0.29578837

Descriptive statistics

Standard deviation0.17260719
Coefficient of variation (CV)0.0046048746
Kurtosis-1.5362211
Mean37.483581
Median Absolute Deviation (MAD)0.13226267
Skewness0.23619421
Sum937.08953
Variance0.029793242
MonotonicityNot monotonic
2023-12-11T07:14:54.695908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
37.6763218608 1
 
4.0%
37.6420784309 1
 
4.0%
37.7549281459 1
 
4.0%
37.7582869344 1
 
4.0%
37.2315502576 1
 
4.0%
37.2735728969 1
 
4.0%
37.3914417865 1
 
4.0%
37.3933329073 1
 
4.0%
37.3192252272 1
 
4.0%
37.3339471887 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
37.2315502576 1
4.0%
37.2735728969 1
4.0%
37.2779000043 1
4.0%
37.2833457572 1
4.0%
37.3192252272 1
4.0%
37.3339471887 1
4.0%
37.3497058843 1
4.0%
37.358611982 1
4.0%
37.3593345561 1
4.0%
37.3880556412 1
4.0%
ValueCountFrequency (%)
37.7582869344 1
4.0%
37.7549281459 1
4.0%
37.6979146701 1
4.0%
37.6828267197 1
4.0%
37.6763218608 1
4.0%
37.674125245 1
4.0%
37.6454942533 1
4.0%
37.6420784309 1
4.0%
37.6320212905 1
4.0%
37.6011202172 1
4.0%

WGS84경도
Real number (ℝ)

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.96471
Minimum126.71071
Maximum127.21137
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-11T07:14:54.807183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.71071
5-th percentile126.75637
Q1126.80758
median126.94729
Q3127.12157
95-th percentile127.20406
Maximum127.21137
Range0.50066007
Interquartile range (IQR)0.31399081

Descriptive statistics

Standard deviation0.16152837
Coefficient of variation (CV)0.0012722304
Kurtosis-1.4667802
Mean126.96471
Median Absolute Deviation (MAD)0.15452745
Skewness0.081150751
Sum3174.1177
Variance0.026091413
MonotonicityNot monotonic
2023-12-11T07:14:54.939484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
126.8064263572 1
 
4.0%
126.8310126485 1
 
4.0%
126.7797904403 1
 
4.0%
127.0776538955 1
 
4.0%
127.2113732269 1
 
4.0%
127.111469994 1
 
4.0%
126.96178865 1
 
4.0%
126.9242279124 1
 
4.0%
126.8251620394 1
 
4.0%
126.807580983 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
126.7107131531 1
4.0%
126.7505158517 1
4.0%
126.7797904403 1
4.0%
126.7912691432 1
4.0%
126.7927633131 1
4.0%
126.8064263572 1
4.0%
126.807580983 1
4.0%
126.8251620394 1
4.0%
126.8310126485 1
4.0%
126.8716560944 1
4.0%
ValueCountFrequency (%)
127.2113732269 1
4.0%
127.2047508165 1
4.0%
127.2013107115 1
4.0%
127.1323955028 1
4.0%
127.1252098475 1
4.0%
127.124186233 1
4.0%
127.1215717901 1
4.0%
127.111469994 1
4.0%
127.0776538955 1
4.0%
127.0464761597 1
4.0%

Interactions

2023-12-11T07:14:50.970645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:14:49.804644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:14:50.250115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:14:50.648211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:14:51.061565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:14:49.907436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:14:50.369949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:14:50.726713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:14:51.398666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:14:50.016299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:14:50.474653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:14:50.813801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:14:51.473359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:14:50.143890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:14:50.572362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:14:50.893959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:14:55.036575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명사업장명인허가일자소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
시군명1.0001.0000.7171.0001.0000.9710.9610.915
사업장명1.0001.0001.0001.0001.0001.0001.0001.000
인허가일자0.7171.0001.0001.0001.0000.7300.0000.351
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.000
소재지우편번호0.9711.0000.7301.0001.0001.0000.8260.000
WGS84위도0.9611.0000.0001.0001.0000.8261.0000.620
WGS84경도0.9151.0000.3511.0001.0000.0000.6201.000
2023-12-11T07:14:55.149473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가일자소재지우편번호WGS84위도WGS84경도
인허가일자1.0000.0660.145-0.205
소재지우편번호0.0661.000-0.8400.360
WGS84위도0.145-0.8401.000-0.251
WGS84경도-0.2050.360-0.2511.000

Missing values

2023-12-11T07:14:51.577013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:14:51.711277image/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.
2023-12-11T07:14:51.816425image/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

시군명사업장명인허가일자영업상태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0고양시동국대학교 일산불교병원20081229운영중경기도 고양시 일산동구 동국로 27경기도 고양시 일산동구 식사동 동국대일산불교종합병원1032637.676322126.806426
1고양시의료법인 명지의료재단 명지병원20040221운영중경기도 고양시 덕양구 화수로14번길 55경기도 고양시 덕양구 화정동 697-241047537.642078126.831013
2고양시인제대학교 일산백병원20000307운영중경기도 고양시 일산서구 주화로 170경기도 고양시 일산서구 대화동 22401038037.674125126.750516
3고양시국민건강보험공단 일산병원20000307운영중경기도 고양시 일산동구 일산로 100경기도 고양시 일산동구 백석동 12321044437.645494126.792763
4광명시의료법인 광명성애병원20040408운영중경기도 광명시 디지털로 36경기도 광명시 철산동 3891424137.473322126.871656
5구리시한양대학교 구리병원20030510운영중경기도 구리시 경춘로 153경기도 구리시 교문동 249-11192337.60112127.132396
6군포시원광대학교 의과대학 산본병원20110216운영중경기도 군포시 산본로 321 (산본동)경기도 군포시 산본동 1142번지1586537.359335126.933564
7군포시지샘병원20151021운영중경기도 군포시 군포로 591 (당동)경기도 군포시 당동 730번지1583937.358612126.947291
8김포시김포우리병원20131223운영중경기도 김포시 감암로 11 (걸포동)경기도 김포시 걸포동 389-15번지1009937.632021126.710713
9남양주시남양주한양병원20090522운영중경기도 남양주시 오남읍 양지로 47-55경기도 남양주시 오남읍 오남리 570번지1204837.682827127.204751
시군명사업장명인허가일자영업상태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
15수원시가톨릭대학교 성빈센트병원19990911운영중경기도 수원시 팔달구 중부대로 93경기도 수원시 팔달구 지동 93-61624737.2779127.02753
16수원시아주대학교병원20000731운영중<NA>경기도 수원시 영통구 원천동 산5<NA>37.283346127.046476
17안산시의료법인 대아의료재단 한도병원20061206운영중경기도 안산시 단원구 선부광장로 103 (선부동)경기도 안산시 단원구 선부동 1071번지 1호 1호1536737.333947126.807581
18안산시고대안산병원20000119운영중경기도 안산시 단원구 적금로 123경기도 안산시 단원구 고잔동 5161535537.319225126.825162
19안양시샘안양병원20040520운영중경기도 안양시 만안구 삼덕로 9경기도 안양시 만안구 안양동 613-81403037.393333126.924228
20안양시한림대학교 성심병원19990129운영중경기도 안양시 동안구 관평로170번길 22경기도 안양시 동안구 평촌동 8961406837.391442126.961789
21용인시강남병원20080905운영중경기도 용인시 기흥구 중부대로 411 (신갈동)경기도 용인시 기흥구 신갈동 65번지1706437.273573127.11147
22용인시(의)영문의료재단 다보스병원20090227운영중경기도 용인시 처인구 백옥대로1082번길 18경기도 용인시 처인구 김량장동 18번지 4호 4호1706337.23155127.211373
23의정부시가톨릭대학교 의정부성모병원20000731운영중<NA>경기도 의정부시 금오동 65-11176537.758287127.077654
24파주시경기도의료원 파주병원20131128운영중경기도 파주시 중앙로 207 (금촌동)경기도 파주시 금촌동 4번지 1호 1호1092237.754928126.77979