Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells18334
Missing cells (%)13.1%
Duplicate rows2717
Duplicate rows (%)27.2%
Total size in memory1.2 MiB
Average record size in memory126.0 B

Variable types

Categorical2
Text5
DateTime1
Unsupported1
Numeric5

Dataset

Description치과의원 현황(의원급)
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=QBWB2X1H679965HK50592054764&infSeq=1

Alerts

Dataset has 2717 (27.2%) duplicate rowsDuplicates
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
영업상태명 is highly imbalanced (63.0%)Imbalance
폐업일자 has 7767 (77.7%) missing valuesMissing
의료기관종별명 has 10000 (100.0%) missing valuesMissing
소재지도로명주소 has 156 (1.6%) missing valuesMissing
WGS84위도 has 136 (1.4%) missing valuesMissing
WGS84경도 has 136 (1.4%) missing valuesMissing
의료인수(명) is highly skewed (γ1 = 97.617295)Skewed
연면적(㎡) is highly skewed (γ1 = 40.48999188)Skewed
의료기관종별명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
연면적(㎡) has 211 (2.1%) zerosZeros

Reproduction

Analysis started2024-05-10 20:56:36.198680
Analysis finished2024-05-10 20:56:49.644718
Duration13.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
고양시
1630 
부천시
1380 
성남시
1376 
남양주
787 
시흥시
771 
Other values (11)
4056 

Length

Max length4
Median length3
Mean length3.0162
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고양시
2nd row가평군
3rd row고양시
4th row과천시
5th row광주시

Common Values

ValueCountFrequency (%)
고양시 1630
16.3%
부천시 1380
13.8%
성남시 1376
13.8%
남양주 787
7.9%
시흥시 771
7.7%
김포시 685
6.9%
광명시 629
 
6.3%
안산시 515
 
5.1%
군포시 488
 
4.9%
수원시 483
 
4.8%
Other values (6) 1256
12.6%

Length

2024-05-10T20:56:49.847992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고양시 1630
16.3%
부천시 1380
13.8%
성남시 1376
13.8%
남양주 787
7.9%
시흥시 771
7.7%
김포시 685
6.9%
광명시 629
 
6.3%
안산시 515
 
5.1%
군포시 488
 
4.9%
수원시 483
 
4.8%
Other values (6) 1256
12.6%

사업장명
Text

Distinct2502
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-10T20:56:50.337345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length7.6978
Min length4

Characters and Unicode

Total characters76978
Distinct characters539
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique379 ?
Unique (%)3.8%

Sample

1st row덴트웰치과의원
2nd row1퍼센트 치과의원
3rd row채한승치과의원
4th row미소치과의원
5th row플랜에이치과의원
ValueCountFrequency (%)
치과의원 91
 
0.9%
연세치과의원 41
 
0.4%
서울치과의원 41
 
0.4%
유디치과의원 39
 
0.4%
현대치과의원 38
 
0.4%
행복한치과의원 36
 
0.4%
우리치과의원 36
 
0.4%
하나치과의원 31
 
0.3%
미소치과의원 28
 
0.3%
미치과의원 28
 
0.3%
Other values (2526) 9837
96.0%
2024-05-10T20:56:51.250011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 10498
 
13.6%
치 10229
 
13.3%
원 10168
 
13.2%
의 9999
 
13.0%
이 1410
 
1.8%
서 1269
 
1.6%
울 1238
 
1.6%
세 1037
 
1.3%
연 970
 
1.3%
스 957
 
1.2%
Other values (529) 29203
37.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 75637
98.3%
Decimal Number 360
 
0.5%
Uppercase Letter 288
 
0.4%
Space Separator 246
 
0.3%
Lowercase Letter 161
 
0.2%
Open Punctuation 99
 
0.1%
Close Punctuation 99
 
0.1%
Dash Punctuation 59
 
0.1%
Other Punctuation 27
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 10498
 
13.9%
치 10229
 
13.5%
원 10168
 
13.4%
의 9999
 
13.2%
이 1410
 
1.9%
서 1269
 
1.7%
울 1238
 
1.6%
세 1037
 
1.4%
연 970
 
1.3%
스 957
 
1.3%
Other values (487) 27862
36.8%
Uppercase Letter
ValueCountFrequency (%)
S 56
19.4%
C 28
9.7%
D 27
9.4%
E 22
 
7.6%
U 20
 
6.9%
N 17
 
5.9%
T 17
 
5.9%
K 14
 
4.9%
M 13
 
4.5%
H 13
 
4.5%
Other values (8) 61
21.2%
Decimal Number
ValueCountFrequency (%)
5 63
17.5%
3 60
16.7%
1 56
15.6%
2 55
15.3%
6 46
12.8%
0 34
9.4%
7 19
 
5.3%
8 12
 
3.3%
4 8
 
2.2%
9 7
 
1.9%
Lowercase Letter
ValueCountFrequency (%)
e 133
82.6%
h 8
 
5.0%
r 8
 
5.0%
u 7
 
4.3%
n 4
 
2.5%
i 1
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 17
63.0%
& 5
 
18.5%
· 5
 
18.5%
Space Separator
ValueCountFrequency (%)
246
100.0%
Open Punctuation
ValueCountFrequency (%)
( 99
100.0%
Close Punctuation
ValueCountFrequency (%)
) 99
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 75628
98.2%
Common 892
 
1.2%
Latin 449
 
0.6%
Han 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 10498
 
13.9%
치 10229
 
13.5%
원 10168
 
13.4%
의 9999
 
13.2%
이 1410
 
1.9%
서 1269
 
1.7%
울 1238
 
1.6%
세 1037
 
1.4%
연 970
 
1.3%
스 957
 
1.3%
Other values (486) 27853
36.8%
Latin
ValueCountFrequency (%)
e 133
29.6%
S 56
12.5%
C 28
 
6.2%
D 27
 
6.0%
E 22
 
4.9%
U 20
 
4.5%
N 17
 
3.8%
T 17
 
3.8%
K 14
 
3.1%
M 13
 
2.9%
Other values (14) 102
22.7%
Common
ValueCountFrequency (%)
246
27.6%
( 99
11.1%
) 99
11.1%
5 63
 
7.1%
3 60
 
6.7%
- 59
 
6.6%
1 56
 
6.3%
2 55
 
6.2%
6 46
 
5.2%
0 34
 
3.8%
Other values (8) 75
 
8.4%
Han
ValueCountFrequency (%)
美 9
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 75628
98.2%
ASCII 1336
 
1.7%
CJK 9
 
< 0.1%
None 5
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 10498
 
13.9%
치 10229
 
13.5%
원 10168
 
13.4%
의 9999
 
13.2%
이 1410
 
1.9%
서 1269
 
1.7%
울 1238
 
1.6%
세 1037
 
1.4%
연 970
 
1.3%
스 957
 
1.3%
Other values (486) 27853
36.8%
ASCII
ValueCountFrequency (%)
246
18.4%
e 133
 
10.0%
( 99
 
7.4%
) 99
 
7.4%
5 63
 
4.7%
3 60
 
4.5%
- 59
 
4.4%
S 56
 
4.2%
1 56
 
4.2%
2 55
 
4.1%
Other values (31) 410
30.7%
CJK
ValueCountFrequency (%)
美 9
100.0%
None
ValueCountFrequency (%)
· 5
100.0%

인허가일자
Date

Distinct2733
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1967-05-30 00:00:00
Maximum2024-04-04 00:00:00
2024-05-10T20:56:51.758253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:52.264314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업/정상
7372 
폐업
2191 
영업중
 
364
취소/말소/만료/정지/중지
 
52
휴업
 
19
Other values (2)
 
2

Length

Max length14
Median length5
Mean length4.3106
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row폐업
2nd row영업/정상
3rd row영업/정상
4th row폐업
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 7372
73.7%
폐업 2191
 
21.9%
영업중 364
 
3.6%
취소/말소/만료/정지/중지 52
 
0.5%
휴업 19
 
0.2%
전출 1
 
< 0.1%
<NA> 1
 
< 0.1%

Length

2024-05-10T20:56:52.742799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T20:56:53.085487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 7372
73.7%
폐업 2191
 
21.9%
영업중 364
 
3.6%
취소/말소/만료/정지/중지 52
 
0.5%
휴업 19
 
0.2%
전출 1
 
< 0.1%
na 1
 
< 0.1%

폐업일자
Text

MISSING 

Distinct711
Distinct (%)31.8%
Missing7767
Missing (%)77.7%
Memory size156.2 KiB
2024-05-10T20:56:53.736768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.7536946
Min length5

Characters and Unicode

Total characters21780
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

Unique87 ?
Unique (%)3.9%

Sample

1st row2010-02-09
2nd row2017-09-18
3rd row2013-10-31
4th row2010-09-13
5th row2022-12-08
ValueCountFrequency (%)
2008-12-29 15
 
0.7%
2011-01-31 9
 
0.4%
2020-11-30 8
 
0.4%
2008-01-31 8
 
0.4%
2016-06-09 8
 
0.4%
2014-07-31 8
 
0.4%
2013-07-29 8
 
0.4%
2016-04-01 8
 
0.4%
2012-12-10 7
 
0.3%
2009-08-27 7
 
0.3%
Other values (701) 2147
96.1%
2024-05-10T20:56:54.667611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5203
23.9%
- 4246
19.5%
2 4132
19.0%
1 3538
16.2%
3 971
 
4.5%
9 820
 
3.8%
4 691
 
3.2%
8 597
 
2.7%
6 557
 
2.6%
7 531
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17534
80.5%
Dash Punctuation 4246
 
19.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5203
29.7%
2 4132
23.6%
1 3538
20.2%
3 971
 
5.5%
9 820
 
4.7%
4 691
 
3.9%
8 597
 
3.4%
6 557
 
3.2%
7 531
 
3.0%
5 494
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 4246
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21780
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5203
23.9%
- 4246
19.5%
2 4132
19.0%
1 3538
16.2%
3 971
 
4.5%
9 820
 
3.8%
4 691
 
3.2%
8 597
 
2.7%
6 557
 
2.6%
7 531
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21780
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5203
23.9%
- 4246
19.5%
2 4132
19.0%
1 3538
16.2%
3 971
 
4.5%
9 820
 
3.8%
4 691
 
3.2%
8 597
 
2.7%
6 557
 
2.6%
7 531
 
2.4%

의료기관종별명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

의료인수(명)
Real number (ℝ)

SKEWED 

Distinct22
Distinct (%)0.2%
Missing22
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean1.4684305
Minimum0
Maximum1068
Zeros25
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T20:56:54.981820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile3
Maximum1068
Range1068
Interquartile range (IQR)0

Descriptive statistics

Standard deviation10.761609
Coefficient of variation (CV)7.3286468
Kurtosis9672.0347
Mean1.4684305
Median Absolute Deviation (MAD)0
Skewness97.617295
Sum14652
Variance115.81222
MonotonicityNot monotonic
2024-05-10T20:56:55.299802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 7793
77.9%
2 1533
 
15.3%
3 362
 
3.6%
4 135
 
1.4%
5 46
 
0.5%
6 29
 
0.3%
0 25
 
0.2%
7 24
 
0.2%
9 10
 
0.1%
8 4
 
< 0.1%
Other values (12) 17
 
0.2%
(Missing) 22
 
0.2%
ValueCountFrequency (%)
0 25
 
0.2%
1 7793
77.9%
2 1533
 
15.3%
3 362
 
3.6%
4 135
 
1.4%
5 46
 
0.5%
6 29
 
0.3%
7 24
 
0.2%
8 4
 
< 0.1%
9 10
 
0.1%
ValueCountFrequency (%)
1068 1
 
< 0.1%
49 1
 
< 0.1%
45 2
< 0.1%
36 1
 
< 0.1%
31 1
 
< 0.1%
23 4
< 0.1%
22 1
 
< 0.1%
19 1
 
< 0.1%
17 1
 
< 0.1%
15 1
 
< 0.1%

진료과목내용
Text

Distinct476
Distinct (%)4.8%
Missing23
Missing (%)0.2%
Memory size156.2 KiB
2024-05-10T20:56:55.720242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length145
Median length141
Mean length30.918613
Min length2

Characters and Unicode

Total characters308475
Distinct characters41
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

Unique163 ?
Unique (%)1.6%

Sample

1st row치과
2nd row구강악안면외과, 치과보철과, 치과교정과, 소아치과, 치주과, 치과보존과, 구강내과, 영상치의학과, 구강병리과, 예방치과, 통합치의학과
3rd row치주과, 치과보존과, 구강내과
4th row치과
5th row구강악안면외과, 치과보철과, 소아치과, 치주과, 치과보존과, 구강내과, 구강병리과, 예방치과
ValueCountFrequency (%)
치과 5100
9.9%
치주과 4556
8.8%
치과보철과 4472
8.7%
치과보존과 4432
8.6%
소아치과 4310
8.3%
구강악안면외과 4199
8.1%
구강내과 4090
7.9%
치과교정과 4088
7.9%
예방치과 3937
7.6%
구강병리과 2884
 
5.6%
Other values (61) 9613
18.6%
2024-05-10T20:56:56.712044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 60327
19.6%
41704
13.5%
, 38189
12.4%
치 35465
11.5%
구 11849
 
3.8%
강 11849
 
3.8%
보 8904
 
2.9%
악 4875
 
1.6%
안 4875
 
1.6%
면 4875
 
1.6%
Other values (31) 85563
27.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 215544
69.9%
Space Separator 41704
 
13.5%
Other Punctuation 38189
 
12.4%
Decimal Number 13038
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 60327
28.0%
치 35465
16.5%
구 11849
 
5.5%
강 11849
 
5.5%
보 8904
 
4.1%
악 4875
 
2.3%
안 4875
 
2.3%
면 4875
 
2.3%
방 4616
 
2.1%
의 4573
 
2.1%
Other values (19) 63336
29.4%
Decimal Number
ValueCountFrequency (%)
0 3824
29.3%
4 3627
27.8%
1 1872
14.4%
2 1362
 
10.4%
3 477
 
3.7%
6 422
 
3.2%
5 410
 
3.1%
7 379
 
2.9%
8 343
 
2.6%
9 322
 
2.5%
Space Separator
ValueCountFrequency (%)
41704
100.0%
Other Punctuation
ValueCountFrequency (%)
, 38189
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 215544
69.9%
Common 92931
30.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 60327
28.0%
치 35465
16.5%
구 11849
 
5.5%
강 11849
 
5.5%
보 8904
 
4.1%
악 4875
 
2.3%
안 4875
 
2.3%
면 4875
 
2.3%
방 4616
 
2.1%
의 4573
 
2.1%
Other values (19) 63336
29.4%
Common
ValueCountFrequency (%)
41704
44.9%
, 38189
41.1%
0 3824
 
4.1%
4 3627
 
3.9%
1 1872
 
2.0%
2 1362
 
1.5%
3 477
 
0.5%
6 422
 
0.5%
5 410
 
0.4%
7 379
 
0.4%
Other values (2) 665
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 215544
69.9%
ASCII 92931
30.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 60327
28.0%
치 35465
16.5%
구 11849
 
5.5%
강 11849
 
5.5%
보 8904
 
4.1%
악 4875
 
2.3%
안 4875
 
2.3%
면 4875
 
2.3%
방 4616
 
2.1%
의 4573
 
2.1%
Other values (19) 63336
29.4%
ASCII
ValueCountFrequency (%)
41704
44.9%
, 38189
41.1%
0 3824
 
4.1%
4 3627
 
3.9%
1 1872
 
2.0%
2 1362
 
1.5%
3 477
 
0.5%
6 422
 
0.5%
5 410
 
0.4%
7 379
 
0.4%
Other values (2) 665
 
0.7%

연면적(㎡)
Real number (ℝ)

SKEWED  ZEROS 

Distinct2649
Distinct (%)26.5%
Missing22
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean243.61525
Minimum0
Maximum120985
Zeros211
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T20:56:57.134287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile51.04
Q197.2
median138.16
Q3201.2
95-th percentile370.43
Maximum120985
Range120985
Interquartile range (IQR)104

Descriptive statistics

Standard deviation2925.1702
Coefficient of variation (CV)12.007336
Kurtosis1648.1101
Mean243.61525
Median Absolute Deviation (MAD)48.75
Skewness40.489992
Sum2430793
Variance8556620.7
MonotonicityNot monotonic
2024-05-10T20:56:57.503487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 211
 
2.1%
1.0 76
 
0.8%
132.0 36
 
0.4%
120.0 26
 
0.3%
150.0 24
 
0.2%
100.0 24
 
0.2%
160.0 23
 
0.2%
99.17 22
 
0.2%
107.0 21
 
0.2%
90.0 21
 
0.2%
Other values (2639) 9494
94.9%
(Missing) 22
 
0.2%
ValueCountFrequency (%)
0.0 211
2.1%
1.0 76
 
0.8%
7.92 5
 
0.1%
12.4 1
 
< 0.1%
15.03 3
 
< 0.1%
22.9 3
 
< 0.1%
25.0 6
 
0.1%
27.36 3
 
< 0.1%
29.05 2
 
< 0.1%
30.0 4
 
< 0.1%
ValueCountFrequency (%)
120985.0 5
0.1%
109537.0 1
 
< 0.1%
11764.12 1
 
< 0.1%
7797.9 1
 
< 0.1%
6204.12 1
 
< 0.1%
4356.63 1
 
< 0.1%
4054.71 1
 
< 0.1%
3529.64 1
 
< 0.1%
3207.0 1
 
< 0.1%
2944.6 1
 
< 0.1%

소재지도로명주소
Text

MISSING 

Distinct3253
Distinct (%)33.0%
Missing156
Missing (%)1.6%
Memory size156.2 KiB
2024-05-10T20:56:58.135985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length62
Mean length34.590106
Min length14

Characters and Unicode

Total characters340505
Distinct characters550
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique543 ?
Unique (%)5.5%

Sample

1st row경기도 고양시 일산서구 고양대로 691, 3층 (일산동)
2nd row경기도 성남시 수정구 수정로 286, 정인빌딩 2층, 3층일부호 (신흥동)
3rd row경기도 고양시 일산동구 강송로 170 (마두동, 현대프라자빌딩205,206호)
4th row경기도 과천시 별양로 182-2, 2층 202호 (부림동, 시대빌딩)
5th row경기도 광주시 중앙로 107, 3층 (경안동)
ValueCountFrequency (%)
경기도 9844
 
13.8%
2층 1538
 
2.1%
수원시 1439
 
2.0%
고양시 1394
 
1.9%
성남시 1393
 
1.9%
3층 1225
 
1.7%
부천시 1171
 
1.6%
분당구 795
 
1.1%
남양주시 785
 
1.1%
원미구 715
 
1.0%
Other values (4415) 51243
71.6%
2024-05-10T20:56:59.270134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
61740
 
18.1%
, 13106
 
3.8%
시 10737
 
3.2%
경 10395
 
3.1%
동 10358
 
3.0%
도 10306
 
3.0%
기 10033
 
2.9%
2 9801
 
2.9%
로 9765
 
2.9%
1 9207
 
2.7%
Other values (540) 185057
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 186948
54.9%
Space Separator 61740
 
18.1%
Decimal Number 57605
 
16.9%
Other Punctuation 13178
 
3.9%
Close Punctuation 9111
 
2.7%
Open Punctuation 9109
 
2.7%
Dash Punctuation 1110
 
0.3%
Uppercase Letter 879
 
0.3%
Math Symbol 628
 
0.2%
Lowercase Letter 169
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 10737
 
5.7%
경 10395
 
5.6%
동 10358
 
5.5%
도 10306
 
5.5%
기 10033
 
5.4%
로 9765
 
5.2%
구 6520
 
3.5%
호 5991
 
3.2%
층 4459
 
2.4%
원 3620
 
1.9%
Other values (473) 104764
56.0%
Uppercase Letter
ValueCountFrequency (%)
B 116
13.2%
A 111
12.6%
C 101
11.5%
S 63
 
7.2%
I 55
 
6.3%
D 41
 
4.7%
T 39
 
4.4%
M 38
 
4.3%
E 37
 
4.2%
K 37
 
4.2%
Other values (14) 241
27.4%
Lowercase Letter
ValueCountFrequency (%)
e 58
34.3%
r 12
 
7.1%
a 11
 
6.5%
t 10
 
5.9%
m 8
 
4.7%
n 8
 
4.7%
i 8
 
4.7%
o 7
 
4.1%
w 7
 
4.1%
l 7
 
4.1%
Other values (6) 33
19.5%
Decimal Number
ValueCountFrequency (%)
2 9801
17.0%
1 9207
16.0%
0 8638
15.0%
3 8595
14.9%
4 5780
10.0%
5 4408
7.7%
6 3271
 
5.7%
7 2806
 
4.9%
8 2697
 
4.7%
9 2402
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 13106
99.5%
. 54
 
0.4%
& 6
 
< 0.1%
/ 5
 
< 0.1%
· 4
 
< 0.1%
@ 3
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 15
53.6%
Ⅰ 6
 
21.4%
Ⅲ 4
 
14.3%
Ⅳ 3
 
10.7%
Math Symbol
ValueCountFrequency (%)
~ 625
99.5%
∼ 2
 
0.3%
∥ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
61740
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9111
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 186947
54.9%
Common 152481
44.8%
Latin 1076
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 10737
 
5.7%
경 10395
 
5.6%
동 10358
 
5.5%
도 10306
 
5.5%
기 10033
 
5.4%
로 9765
 
5.2%
구 6520
 
3.5%
호 5991
 
3.2%
층 4459
 
2.4%
원 3620
 
1.9%
Other values (472) 104763
56.0%
Latin
ValueCountFrequency (%)
B 116
 
10.8%
A 111
 
10.3%
C 101
 
9.4%
S 63
 
5.9%
e 58
 
5.4%
I 55
 
5.1%
D 41
 
3.8%
T 39
 
3.6%
M 38
 
3.5%
E 37
 
3.4%
Other values (34) 417
38.8%
Common
ValueCountFrequency (%)
61740
40.5%
, 13106
 
8.6%
2 9801
 
6.4%
1 9207
 
6.0%
) 9111
 
6.0%
( 9109
 
6.0%
0 8638
 
5.7%
3 8595
 
5.6%
4 5780
 
3.8%
5 4408
 
2.9%
Other values (13) 12986
 
8.5%
Han
ValueCountFrequency (%)
外 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 186947
54.9%
ASCII 153522
45.1%
Number Forms 28
 
< 0.1%
None 4
 
< 0.1%
Math Operators 3
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
61740
40.2%
, 13106
 
8.5%
2 9801
 
6.4%
1 9207
 
6.0%
) 9111
 
5.9%
( 9109
 
5.9%
0 8638
 
5.6%
3 8595
 
5.6%
4 5780
 
3.8%
5 4408
 
2.9%
Other values (50) 14027
 
9.1%
Hangul
ValueCountFrequency (%)
시 10737
 
5.7%
경 10395
 
5.6%
동 10358
 
5.5%
도 10306
 
5.5%
기 10033
 
5.4%
로 9765
 
5.2%
구 6520
 
3.5%
호 5991
 
3.2%
층 4459
 
2.4%
원 3620
 
1.9%
Other values (472) 104763
56.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 15
53.6%
Ⅰ 6
 
21.4%
Ⅲ 4
 
14.3%
Ⅳ 3
 
10.7%
None
ValueCountFrequency (%)
· 4
100.0%
Math Operators
ValueCountFrequency (%)
∼ 2
66.7%
∥ 1
33.3%
CJK
ValueCountFrequency (%)
外 1
100.0%

소재지지번주소
Text

Distinct3278
Distinct (%)32.8%
Missing8
Missing (%)0.1%
Memory size156.2 KiB
2024-05-10T20:56:59.926857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length49
Mean length28.290532
Min length2

Characters and Unicode

Total characters282679
Distinct characters513
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique542 ?
Unique (%)5.4%

Sample

1st row경기도 고양시 일산서구 일산동 644. 3층
2nd row경기도 성남시 수정구 신흥동 947 정인빌딩 2층, 3층일부호
3rd row경기도 고양시 일산동구 마두동 781. 현대프라자빌딩205,206호
4th row경기도 과천시 부림동 46번지 시대빌딩 202호
5th row경기도 광주시 경안동 31번지 13호
ValueCountFrequency (%)
경기도 9755
 
15.8%
수원시 1443
 
2.3%
고양시 1277
 
2.1%
부천시 1163
 
1.9%
성남시 1120
 
1.8%
2층 920
 
1.5%
남양주시 805
 
1.3%
1호 705
 
1.1%
3층 704
 
1.1%
시흥시 670
 
1.1%
Other values (4808) 43263
70.0%
2024-05-10T20:57:01.120613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52241
 
18.5%
시 10747
 
3.8%
1 10253
 
3.6%
동 10222
 
3.6%
도 10032
 
3.5%
경 9890
 
3.5%
기 9877
 
3.5%
2 8680
 
3.1%
3 7708
 
2.7%
호 7558
 
2.7%
Other values (503) 145471
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 164529
58.2%
Decimal Number 58298
 
20.6%
Space Separator 52241
 
18.5%
Dash Punctuation 3683
 
1.3%
Other Punctuation 2051
 
0.7%
Uppercase Letter 834
 
0.3%
Open Punctuation 291
 
0.1%
Close Punctuation 291
 
0.1%
Math Symbol 240
 
0.1%
Lowercase Letter 182
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 10747
 
6.5%
동 10222
 
6.2%
도 10032
 
6.1%
경 9890
 
6.0%
기 9877
 
6.0%
호 7558
 
4.6%
지 7297
 
4.4%
번 6634
 
4.0%
구 6346
 
3.9%
양 3310
 
2.0%
Other values (439) 82616
50.2%
Uppercase Letter
ValueCountFrequency (%)
C 94
 
11.3%
A 90
 
10.8%
B 81
 
9.7%
S 64
 
7.7%
I 52
 
6.2%
E 46
 
5.5%
M 46
 
5.5%
D 41
 
4.9%
L 40
 
4.8%
G 36
 
4.3%
Other values (14) 244
29.3%
Lowercase Letter
ValueCountFrequency (%)
e 50
27.5%
l 22
12.1%
a 14
 
7.7%
t 13
 
7.1%
r 12
 
6.6%
i 8
 
4.4%
p 8
 
4.4%
n 8
 
4.4%
o 7
 
3.8%
w 7
 
3.8%
Other values (7) 33
18.1%
Decimal Number
ValueCountFrequency (%)
1 10253
17.6%
2 8680
14.9%
3 7708
13.2%
0 7324
12.6%
4 5906
10.1%
5 4586
7.9%
6 4080
 
7.0%
7 3586
 
6.2%
8 3344
 
5.7%
9 2831
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 1402
68.4%
. 608
29.6%
@ 22
 
1.1%
/ 14
 
0.7%
& 5
 
0.2%
Letter Number
ValueCountFrequency (%)
Ⅱ 27
69.2%
Ⅲ 6
 
15.4%
Ⅰ 6
 
15.4%
Space Separator
ValueCountFrequency (%)
52241
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3683
100.0%
Open Punctuation
ValueCountFrequency (%)
( 291
100.0%
Close Punctuation
ValueCountFrequency (%)
) 291
100.0%
Math Symbol
ValueCountFrequency (%)
~ 240
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 164528
58.2%
Common 117095
41.4%
Latin 1055
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 10747
 
6.5%
동 10222
 
6.2%
도 10032
 
6.1%
경 9890
 
6.0%
기 9877
 
6.0%
호 7558
 
4.6%
지 7297
 
4.4%
번 6634
 
4.0%
구 6346
 
3.9%
양 3310
 
2.0%
Other values (438) 82615
50.2%
Latin
ValueCountFrequency (%)
C 94
 
8.9%
A 90
 
8.5%
B 81
 
7.7%
S 64
 
6.1%
I 52
 
4.9%
e 50
 
4.7%
E 46
 
4.4%
M 46
 
4.4%
D 41
 
3.9%
L 40
 
3.8%
Other values (34) 451
42.7%
Common
ValueCountFrequency (%)
52241
44.6%
1 10253
 
8.8%
2 8680
 
7.4%
3 7708
 
6.6%
0 7324
 
6.3%
4 5906
 
5.0%
5 4586
 
3.9%
6 4080
 
3.5%
- 3683
 
3.1%
7 3586
 
3.1%
Other values (10) 9048
 
7.7%
Han
ValueCountFrequency (%)
外 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 164528
58.2%
ASCII 118111
41.8%
Number Forms 39
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52241
44.2%
1 10253
 
8.7%
2 8680
 
7.3%
3 7708
 
6.5%
0 7324
 
6.2%
4 5906
 
5.0%
5 4586
 
3.9%
6 4080
 
3.5%
- 3683
 
3.1%
7 3586
 
3.0%
Other values (51) 10064
 
8.5%
Hangul
ValueCountFrequency (%)
시 10747
 
6.5%
동 10222
 
6.2%
도 10032
 
6.1%
경 9890
 
6.0%
기 9877
 
6.0%
호 7558
 
4.6%
지 7297
 
4.4%
번 6634
 
4.0%
구 6346
 
3.9%
양 3310
 
2.0%
Other values (438) 82615
50.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 27
69.2%
Ⅲ 6
 
15.4%
Ⅰ 6
 
15.4%
CJK
ValueCountFrequency (%)
外 1
100.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct1144
Distinct (%)11.5%
Missing64
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean13511.959
Minimum10011
Maximum16713
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T20:57:01.579094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10011
5-th percentile10113
Q111948
median13618
Q315052
95-th percentile16537
Maximum16713
Range6702
Interquartile range (IQR)3104

Descriptive statistics

Standard deviation2105.7162
Coefficient of variation (CV)0.15584092
Kurtosis-1.1435631
Mean13511.959
Median Absolute Deviation (MAD)1561
Skewness-0.23075689
Sum1.3425483 × 108
Variance4434040.7
MonotonicityNot monotonic
2024-05-10T20:57:02.192296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15865 112
 
1.1%
15066 71
 
0.7%
10414 69
 
0.7%
10071 66
 
0.7%
13591 65
 
0.7%
10386 59
 
0.6%
10500 58
 
0.6%
13558 53
 
0.5%
10083 52
 
0.5%
13837 50
 
0.5%
Other values (1134) 9281
92.8%
(Missing) 64
 
0.6%
ValueCountFrequency (%)
10011 4
 
< 0.1%
10018 24
0.2%
10019 8
 
0.1%
10024 9
 
0.1%
10031 9
 
0.1%
10039 15
0.1%
10040 1
 
< 0.1%
10048 7
 
0.1%
10049 6
 
0.1%
10059 32
0.3%
ValueCountFrequency (%)
16713 13
 
0.1%
16712 2
 
< 0.1%
16707 8
 
0.1%
16706 5
 
0.1%
16705 4
 
< 0.1%
16704 36
0.4%
16703 25
0.2%
16700 5
 
0.1%
16699 2
 
< 0.1%
16698 24
0.2%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct2767
Distinct (%)28.1%
Missing136
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean37.478286
Minimum37.233477
Maximum37.90845
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T20:57:02.621603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.233477
5-th percentile37.264351
Q137.358177
median37.465676
Q337.623311
95-th percentile37.691127
Maximum37.90845
Range0.6749726
Interquartile range (IQR)0.26513409

Descriptive statistics

Standard deviation0.14826123
Coefficient of variation (CV)0.0039559235
Kurtosis-0.88235387
Mean37.478286
Median Absolute Deviation (MAD)0.13280395
Skewness0.26274501
Sum369685.81
Variance0.021981392
MonotonicityNot monotonic
2024-05-10T20:57:03.086836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.387792366 19
 
0.2%
37.4105911732 18
 
0.2%
37.6541135945 18
 
0.2%
37.2652290262 17
 
0.2%
37.2955258737 17
 
0.2%
37.6535494257 17
 
0.2%
37.4727049587 16
 
0.2%
37.2550152411 16
 
0.2%
37.4963836443 16
 
0.2%
37.3605616827 15
 
0.1%
Other values (2757) 9695
97.0%
(Missing) 136
 
1.4%
ValueCountFrequency (%)
37.2334769857 3
< 0.1%
37.2352148618 4
< 0.1%
37.2360230333 3
< 0.1%
37.2371433088 4
< 0.1%
37.2376038855 5
0.1%
37.2376155666 4
< 0.1%
37.2386493715 3
< 0.1%
37.238688097 1
 
< 0.1%
37.238891478 1
 
< 0.1%
37.2389687138 3
< 0.1%
ValueCountFrequency (%)
37.9084495901 2
 
< 0.1%
37.9081162039 2
 
< 0.1%
37.9063410328 1
 
< 0.1%
37.9055183713 4
< 0.1%
37.9054371701 5
0.1%
37.9025608444 1
 
< 0.1%
37.9017652587 3
< 0.1%
37.9005406874 2
 
< 0.1%
37.9001975107 3
< 0.1%
37.8928217769 2
 
< 0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct2767
Distinct (%)28.1%
Missing136
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean126.94962
Minimum126.55327
Maximum127.52138
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T20:57:03.582064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55327
5-th percentile126.72003
Q1126.7865
median126.9306
Q3127.11792
95-th percentile127.23774
Maximum127.52138
Range0.9681149
Interquartile range (IQR)0.3314203

Descriptive statistics

Standard deviation0.18002355
Coefficient of variation (CV)0.0014180707
Kurtosis-0.77638665
Mean126.94962
Median Absolute Deviation (MAD)0.15388157
Skewness0.30761414
Sum1252231.1
Variance0.032408477
MonotonicityNot monotonic
2024-05-10T20:57:04.045323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1244225085 19
 
0.2%
127.1282185032 18
 
0.2%
127.2445701661 18
 
0.2%
127.0327990111 17
 
0.2%
126.9936074645 17
 
0.2%
126.8376999667 17
 
0.2%
127.1429411379 16
 
0.2%
127.0756344537 16
 
0.2%
126.7646980209 16
 
0.2%
126.9304076978 15
 
0.1%
Other values (2757) 9695
97.0%
(Missing) 136
 
1.4%
ValueCountFrequency (%)
126.5532656671 9
0.1%
126.5828112985 1
 
< 0.1%
126.5838463141 8
0.1%
126.5844087398 4
< 0.1%
126.5848517955 3
 
< 0.1%
126.5852196596 4
< 0.1%
126.5856269206 1
 
< 0.1%
126.5966352318 3
 
< 0.1%
126.5972829105 4
< 0.1%
126.5978179671 1
 
< 0.1%
ValueCountFrequency (%)
127.5213805697 4
< 0.1%
127.5154533294 4
< 0.1%
127.514693355 3
< 0.1%
127.5143294607 5
0.1%
127.5141363561 4
< 0.1%
127.5141356339 2
 
< 0.1%
127.5139545893 3
< 0.1%
127.5132387972 7
0.1%
127.5129206845 4
< 0.1%
127.5127503949 5
0.1%

Interactions

2024-05-10T20:56:46.522435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:40.218189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:41.907252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:43.519293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:45.128654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:46.784133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:40.485659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:42.201925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:43.852310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:45.411883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:47.050845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:40.764686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:42.543059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:44.159999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:45.716956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:47.322288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:41.056721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:42.857818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:44.485540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:45.987863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:47.602404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:41.465813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:43.172321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:44.845803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T20:56:46.270643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T20:57:04.324339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명의료인수(명)연면적(㎡)소재지우편번호WGS84위도WGS84경도
시군명1.0000.3990.0000.0730.9590.9030.882
영업상태명0.3991.0000.0670.0000.1250.1000.097
의료인수(명)0.0000.0671.0000.3150.0000.0000.000
연면적(㎡)0.0730.0000.3151.0000.0790.0570.122
소재지우편번호0.9590.1250.0000.0791.0000.9610.906
WGS84위도0.9030.1000.0000.0570.9611.0000.867
WGS84경도0.8820.0970.0000.1220.9060.8671.000
2024-05-10T20:57:04.619154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명시군명
영업상태명1.0000.204
시군명0.2041.000
2024-05-10T20:57:04.877375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
의료인수(명)연면적(㎡)소재지우편번호WGS84위도WGS84경도시군명영업상태명
의료인수(명)1.0000.3570.014-0.011-0.0230.0000.048
연면적(㎡)0.3571.0000.0060.006-0.0620.0570.000
소재지우편번호0.0140.0061.000-0.8640.0700.8170.066
WGS84위도-0.0110.006-0.8641.000-0.1970.6530.052
WGS84경도-0.023-0.0620.070-0.1971.0000.6080.051
시군명0.0000.0570.8170.6530.6081.0000.204
영업상태명0.0480.0000.0660.0520.0510.2041.000

Missing values

2024-05-10T20:56:47.994180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T20:56:48.810403image/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.
2024-05-10T20:56:49.294569image/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

시군명사업장명인허가일자영업상태명폐업일자의료기관종별명의료인수(명)진료과목내용연면적(㎡)소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
7108고양시덴트웰치과의원2005-09-20폐업2010-02-09<NA>1치과150.0경기도 고양시 일산서구 고양대로 691, 3층 (일산동)경기도 고양시 일산서구 일산동 644. 3층1034137.683967126.773057
317가평군1퍼센트 치과의원2023-08-23영업/정상<NA><NA>2구강악안면외과, 치과보철과, 치과교정과, 소아치과, 치주과, 치과보존과, 구강내과, 영상치의학과, 구강병리과, 예방치과, 통합치의학과257.39경기도 성남시 수정구 수정로 286, 정인빌딩 2층, 3층일부호 (신흥동)경기도 성남시 수정구 신흥동 947 정인빌딩 2층, 3층일부호1326237.449948127.146814
2354고양시채한승치과의원2000-06-09영업/정상<NA><NA>1치주과, 치과보존과, 구강내과132.99경기도 고양시 일산동구 강송로 170 (마두동, 현대프라자빌딩205,206호)경기도 고양시 일산동구 마두동 781. 현대프라자빌딩205,206호1041637.653913126.784279
7830과천시미소치과의원2012-07-19폐업2017-09-18<NA>1치과52.5경기도 과천시 별양로 182-2, 2층 202호 (부림동, 시대빌딩)경기도 과천시 부림동 46번지 시대빌딩 202호1383137.434096126.998158
10969광주시플랜에이치과의원2015-07-29영업/정상<NA><NA>1구강악안면외과, 치과보철과, 소아치과, 치주과, 치과보존과, 구강내과, 구강병리과, 예방치과190.34경기도 광주시 중앙로 107, 3층 (경안동)경기도 광주시 경안동 31번지 13호1275937.409396127.258251
27533부천시유플란트치과의원2013-09-17폐업2013-10-31<NA>1치과160.38경기도 부천시 원미구 부일로297번길 3, 2층 (상동)경기도 부천시 원미구 상동 318-4번지 2층1462137.488567126.76301
36042수원시글로리아치과의원2001-09-25폐업2010-09-13<NA>1치과89.88경기도 수원시 장안구 덕영대로535번길 46경기도 수원시 장안구 천천동 524-4번지1632937.29729126.982685
706고양시김중기치과의원2006-09-08영업/정상<NA><NA>1205 206 20756.98경기도 고양시 일산동구 일산로 452 (정발산동)경기도 고양시 일산동구 정발산동 1138. 일산프라자 203호1035737.67404126.776953
2200고양시서울연치과의원2024-02-16영업/정상<NA><NA>1구강악안면외과, 치과보철과, 치과교정과, 소아치과, 치주과, 치과보존과, 구강내과, 영상치의학과, 구강병리과, 예방치과, 통합치의학과214.61경기도 고양시 덕양구 화신로 254, 202, 301호 (화정동)경기도 고양시 덕양구 화정동 986-91050037.630811126.833255
15765군포시미켈란쉐르빌치과의원2004-01-05폐업2022-12-08<NA>1치과93.0경기도 성남시 분당구 정자일로 100, 204호 (정자동, 미켈란쉐르빌상가동)경기도 성남시분당구 정자동 180번지 미켈란쉐르빌상가동 204호1356237.358755127.106601
시군명사업장명인허가일자영업상태명폐업일자의료기관종별명의료인수(명)진료과목내용연면적(㎡)소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
35651수원시연세크린치과1986-05-08폐업2012-01-14<NA>1치과76.53경기도 수원시 팔달구 덕영대로 944 (매산로1가)수원시 팔달구 매산로1가 181662237.264354127.001621
23809부천시정진부부치과의원2001-05-26영업/정상<NA><NA>2치과130.0경기도 수원시 권선구 세권로304번길 44, 삼성프라자 204, 205호 (권선동)경기도 수원시 권선구 권선동 1297-2 삼성프라자1655337.250404127.035867
10018광명시광명서울치과의원2009-04-10폐업2013-08-31<NA>1구강악안면외과, 치과보철과, 치과교정과, 소아치과, 치주과, 치과보존과, 구강내과, 구강악안면방사선과, 구강병리과, 예방치과, 치과376.67경기도 광명시 디지털로 29, 3층 301호 (철산동, 정인코아빌딩)경기도 광명시 철산3동 447번지 1호 , 정인코아빌딩 301호.1423937.474165126.870828
7977광명시정송우바른이치과의원2012-11-02영업/정상<NA><NA>1치과156.09경기도 수원시 영통구 효원로 387, 404호 (매탄동, 풍성프라자)경기도 수원시 영통구 매탄동 1267번지 3호 풍성프라자 404호1654537.259242127.043933
31502성남시청치과의원1996-02-23영업/정상<NA><NA>1구강악안면외과, 치과보철과, 치과교정과, 소아치과, 치주과, 치과보존과, 구강내과, 영상치의학과, 구강병리과, 예방치과150.6경기도 성남시 수정구 산성대로 237, 2층 (신흥동)경기도 성남시수정구 신흥1동 4229,2층1334537.439582127.143596
27204부천시서울건치과의원2022-03-18영업중<NA><NA>1통합치의학과259.05경기도 부천시 소사구 소사로 250, 2층 (소사본동)경기도 부천시 소사구 소사본동 128-161469437.480673126.795786
30793성남시유선규치과의원1992-12-24영업/정상<NA><NA>1치과91.28경기도 수원시 권선구 정조로 558 (세류동)수원시 권선구 세류3동 534-251657737.258846127.012483
20125남양주장현치과의원1987-05-12영업/정상<NA><NA>1치과89.1경기도 남양주시 진접읍 장현로47번길 6-2경기도 남양주시 진접읍 장현리 659번지1201537.715867127.179242
33105성남시초림지세븐치과의원2009-11-16영업/정상<NA><NA>2치과266.83경기도 성남시 분당구 수내로46번길 11, 308~309호 (수내동, 대덕글로리)경기도 성남시 분당구 수내동 7번지 1호 대덕글로리 309호1359537.379971127.116815
11347광주시광주플란트치과의원2019-10-11영업/정상<NA><NA>3구강악안면외과, 치과보철과, 치과교정과, 소아치과, 치주과, 치과보존과, 구강내과, 영상치의학과, 구강병리과, 예방치과372.0경기도 광주시 중앙로 105, 3층 (경안동)경기도 광주시 경안동 32번지 1호1275937.409279127.258331

Duplicate rows

Most frequently occurring

시군명사업장명인허가일자영업상태명폐업일자의료인수(명)진료과목내용연면적(㎡)소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도# duplicates
1144김포시안아픈치과의원2009-12-30영업/정상<NA>1치과155.9경기도 김포시 김포한강4로 131, 504호 (장기동, 정현메디피아)경기도 김포시 장기동 1602번지 정현메디피아1008337.644929126.6665138
2458시흥시시화센타치과의원2014-08-13영업/정상<NA>1치과165.6경기도 시흥시 중심상가2길 12-2, 3층 302호 (정왕동)경기도 시흥시 정왕동 1736번지 2호 302호1506637.345543126.7364798
30가평군현리명치과의원2003-05-07영업/정상<NA>1치과155.0경기도 가평군 조종면 조종새싹로 2경기도 가평군 조종면 현리 272번지 3호 2층1243737.819146127.3483177
475과천시고릴라소아치과의원2022-04-16영업/정상<NA>1구강악안면외과, 치과보철과, 치과교정과, 소아치과, 치주과, 치과보존과, 구강내과, 영상치의학과, 구강병리과, 예방치과, 통합치의학과174.63경기도 과천시 별양로 28, 래미안 슈르 상가동 4층 4002-2호~7호 (원문동)경기도 과천시 원문동 4 래미안 슈르1383537.421222126.9912257
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1414남양주캘리포니아치과의원2001-09-13폐업2009-08-271치과96.56<NA>경기도 남양주시 도농동 부영@2차상가 20120212261<NA><NA>7
1486부천시e-하얀치과의원2008-07-31영업/정상<NA>1구강악안면외과, 치과보철과, 치과교정과, 소아치과, 치주과, 치과보존과, 구강내과, 예방치과137.7경기도 부천시 소사구 경인로 126, 길메디칼빌딩 4층 (송내동)경기도 부천시 소사구 송내동 381-1 ,길메디칼빌딩 4층1472637.483847126.7693117
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