Overview

Dataset statistics

Number of variables16
Number of observations325
Missing cells553
Missing cells (%)10.6%
Duplicate rows2
Duplicate rows (%)0.6%
Total size in memory43.3 KiB
Average record size in memory136.4 B

Variable types

Categorical2
Text4
DateTime2
Numeric7
Unsupported1

Dataset

Description한방병원 현황(병원급)
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=35G1S85I0HLXLRTPKVL91996145&infSeq=1

Alerts

Dataset has 2 (0.6%) duplicate rowsDuplicates
병상수(개) is highly overall correlated with 의료인수(명) and 2 other fieldsHigh correlation
의료인수(명) is highly overall correlated with 병상수(개) and 2 other fieldsHigh correlation
입원실수(개) is highly overall correlated with 병상수(개) and 2 other fieldsHigh correlation
연면적(㎡) is highly overall correlated with 병상수(개) and 2 other fieldsHigh correlation
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
폐업일자 has 228 (70.2%) missing valuesMissing
의료기관종별명 has 325 (100.0%) missing valuesMissing
의료기관종별명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
입원실수(개) has 4 (1.2%) zerosZeros

Reproduction

Analysis started2024-05-03 19:18:11.901061
Analysis finished2024-05-03 19:18:35.858084
Duration23.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
안산시
57 
시흥시
40 
부천시
31 
김포시
21 
고양시
19 
Other values (23)
157 

Length

Max length4
Median length3
Mean length3.04
Min length3

Unique

Unique7 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
안산시 57
17.5%
시흥시 40
12.3%
부천시 31
9.5%
김포시 21
 
6.5%
고양시 19
 
5.8%
화성시 18
 
5.5%
성남시 18
 
5.5%
용인시 18
 
5.5%
평택시 16
 
4.9%
안양시 16
 
4.9%
Other values (18) 71
21.8%

Length

2024-05-03T19:18:36.098571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
안산시 57
17.5%
시흥시 40
12.3%
부천시 31
9.5%
김포시 21
 
6.5%
고양시 19
 
5.8%
화성시 18
 
5.5%
성남시 18
 
5.5%
용인시 18
 
5.5%
평택시 16
 
4.9%
안양시 16
 
4.9%
Other values (18) 71
21.8%

사업장명
Text

Distinct226
Distinct (%)69.5%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-05-03T19:18:36.815819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length7.8276923
Min length5

Characters and Unicode

Total characters2544
Distinct characters222
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique134 ?
Unique (%)41.2%

Sample

1st row청평푸른숲한방병원
2nd row소통한방병원
3rd row바른쎌한방병원
4th row여기한방병원
5th row더하다한방병원
ValueCountFrequency (%)
일로한방병원 4
 
1.2%
참잘함한방병원 4
 
1.2%
의료법인 4
 
1.2%
365매일한방병원 4
 
1.2%
시흥미소한방병원 3
 
0.9%
한의과대학 2
 
0.6%
성신한방병원 2
 
0.6%
경희다원한방병원 2
 
0.6%
필한방병원 2
 
0.6%
세화한방병원 2
 
0.6%
Other values (227) 317
91.6%
2024-05-03T19:18:38.236366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 346
 
13.6%
한 337
 
13.2%
병 327
 
12.9%
방 326
 
12.8%
의 45
 
1.8%
료 29
 
1.1%
인 26
 
1.0%
동 26
 
1.0%
산 23
 
0.9%
경 21
 
0.8%
Other values (212) 1038
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2486
97.7%
Decimal Number 22
 
0.9%
Space Separator 21
 
0.8%
Close Punctuation 5
 
0.2%
Open Punctuation 5
 
0.2%
Uppercase Letter 3
 
0.1%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 346
 
13.9%
한 337
 
13.6%
병 327
 
13.2%
방 326
 
13.1%
의 45
 
1.8%
료 29
 
1.2%
인 26
 
1.0%
동 26
 
1.0%
산 23
 
0.9%
경 21
 
0.8%
Other values (202) 980
39.4%
Decimal Number
ValueCountFrequency (%)
6 7
31.8%
3 7
31.8%
5 7
31.8%
2 1
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
K 2
66.7%
S 1
33.3%
Space Separator
ValueCountFrequency (%)
21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2486
97.7%
Common 55
 
2.2%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 346
 
13.9%
한 337
 
13.6%
병 327
 
13.2%
방 326
 
13.1%
의 45
 
1.8%
료 29
 
1.2%
인 26
 
1.0%
동 26
 
1.0%
산 23
 
0.9%
경 21
 
0.8%
Other values (202) 980
39.4%
Common
ValueCountFrequency (%)
21
38.2%
6 7
 
12.7%
3 7
 
12.7%
5 7
 
12.7%
) 5
 
9.1%
( 5
 
9.1%
- 2
 
3.6%
2 1
 
1.8%
Latin
ValueCountFrequency (%)
K 2
66.7%
S 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2486
97.7%
ASCII 58
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 346
 
13.9%
한 337
 
13.6%
병 327
 
13.2%
방 326
 
13.1%
의 45
 
1.8%
료 29
 
1.2%
인 26
 
1.0%
동 26
 
1.0%
산 23
 
0.9%
경 21
 
0.8%
Other values (202) 980
39.4%
ASCII
ValueCountFrequency (%)
21
36.2%
6 7
 
12.1%
3 7
 
12.1%
5 7
 
12.1%
) 5
 
8.6%
( 5
 
8.6%
- 2
 
3.4%
K 2
 
3.4%
S 1
 
1.7%
2 1
 
1.7%

인허가일자
Date

Distinct226
Distinct (%)69.5%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
Minimum1900-01-01 00:00:00
Maximum2024-03-20 00:00:00
2024-05-03T19:18:39.069261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:39.765220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태명
Categorical

Distinct4
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
영업/정상
138 
폐업
93 
영업중
89 
취소/말소/만료/정지/중지
 
5

Length

Max length14
Median length5
Mean length3.7323077
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 138
42.5%
폐업 93
28.6%
영업중 89
27.4%
취소/말소/만료/정지/중지 5
 
1.5%

Length

2024-05-03T19:18:40.514668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T19:18:40.982222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 138
42.5%
폐업 93
28.6%
영업중 89
27.4%
취소/말소/만료/정지/중지 5
 
1.5%

폐업일자
Date

MISSING 

Distinct92
Distinct (%)94.8%
Missing228
Missing (%)70.2%
Memory size2.7 KiB
Minimum2003-02-04 00:00:00
Maximum2024-02-29 00:00:00
2024-05-03T19:18:41.480727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:42.232873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

병상수(개)
Real number (ℝ)

HIGH CORRELATION 

Distinct65
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.172308
Minimum0
Maximum274
Zeros2
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-05-03T19:18:42.865458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile30
Q142
median51
Q363
95-th percentile93
Maximum274
Range274
Interquartile range (IQR)21

Descriptive statistics

Standard deviation26.691907
Coefficient of variation (CV)0.4751791
Kurtosis28.512531
Mean56.172308
Median Absolute Deviation (MAD)10
Skewness4.0865909
Sum18256
Variance712.45787
MonotonicityNot monotonic
2024-05-03T19:18:43.351786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30 22
 
6.8%
60 20
 
6.2%
51 14
 
4.3%
50 14
 
4.3%
47 12
 
3.7%
48 11
 
3.4%
52 11
 
3.4%
41 11
 
3.4%
44 11
 
3.4%
80 11
 
3.4%
Other values (55) 188
57.8%
ValueCountFrequency (%)
0 2
 
0.6%
17 1
 
0.3%
30 22
6.8%
31 5
 
1.5%
32 2
 
0.6%
33 3
 
0.9%
34 2
 
0.6%
35 4
 
1.2%
36 5
 
1.5%
37 3
 
0.9%
ValueCountFrequency (%)
274 2
0.6%
197 1
 
0.3%
134 2
0.6%
117 1
 
0.3%
116 1
 
0.3%
107 2
0.6%
100 2
0.6%
99 2
0.6%
95 2
0.6%
93 3
0.9%

의료기관종별명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing325
Missing (%)100.0%
Memory size3.0 KiB

의료인수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.018462
Minimum1
Maximum85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-05-03T19:18:43.919703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q16
median11
Q316
95-th percentile32
Maximum85
Range84
Interquartile range (IQR)10

Descriptive statistics

Standard deviation11.153515
Coefficient of variation (CV)0.856746
Kurtosis12.736928
Mean13.018462
Median Absolute Deviation (MAD)5
Skewness2.9388166
Sum4231
Variance124.40089
MonotonicityNot monotonic
2024-05-03T19:18:44.387342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
7 27
 
8.3%
12 24
 
7.4%
5 23
 
7.1%
11 19
 
5.8%
6 19
 
5.8%
13 18
 
5.5%
3 15
 
4.6%
15 15
 
4.6%
14 14
 
4.3%
4 14
 
4.3%
Other values (29) 137
42.2%
ValueCountFrequency (%)
1 8
 
2.5%
2 8
 
2.5%
3 15
4.6%
4 14
4.3%
5 23
7.1%
6 19
5.8%
7 27
8.3%
8 13
4.0%
9 12
3.7%
10 13
4.0%
ValueCountFrequency (%)
85 1
0.3%
84 1
0.3%
63 2
0.6%
50 1
0.3%
49 2
0.6%
48 2
0.6%
44 1
0.3%
40 2
0.6%
37 2
0.6%
33 2
0.6%

입원실수(개)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.04
Minimum0
Maximum79
Zeros4
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-05-03T19:18:44.816979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.2
Q112
median17
Q322
95-th percentile35.2
Maximum79
Range79
Interquartile range (IQR)10

Descriptive statistics

Standard deviation9.5869124
Coefficient of variation (CV)0.5314253
Kurtosis9.8654235
Mean18.04
Median Absolute Deviation (MAD)5
Skewness2.1690705
Sum5863
Variance91.908889
MonotonicityNot monotonic
2024-05-03T19:18:45.289111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
14 26
 
8.0%
17 24
 
7.4%
13 18
 
5.5%
16 18
 
5.5%
21 17
 
5.2%
15 16
 
4.9%
22 15
 
4.6%
18 15
 
4.6%
11 14
 
4.3%
19 14
 
4.3%
Other values (28) 148
45.5%
ValueCountFrequency (%)
0 4
 
1.2%
4 1
 
0.3%
5 5
 
1.5%
6 7
2.2%
7 7
2.2%
8 11
3.4%
9 10
3.1%
10 9
2.8%
11 14
4.3%
12 14
4.3%
ValueCountFrequency (%)
79 2
0.6%
48 2
0.6%
46 1
 
0.3%
45 1
 
0.3%
44 3
0.9%
40 1
 
0.3%
39 2
0.6%
38 2
0.6%
36 3
0.9%
32 3
0.9%

진료과목내용
Text

Distinct107
Distinct (%)32.9%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-05-03T19:18:45.877269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length138
Median length118
Mean length64.867692
Min length2

Characters and Unicode

Total characters21082
Distinct characters50
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)15.7%

Sample

1st row내과, 가정의학과, 한방내과, 한방부인과, 한방소아과, 사상체질과, 침구과
2nd row가정의학과, 한방내과, 침구과
3rd row내과, 피부과, 재활의학과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방재활의학과, 침구과
4th row내과, 정형외과, 영상의학과, 한방내과, 한방부인과, 한방소아과, 한방재활의학과, 사상체질과, 침구과
5th row정형외과, 가정의학과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과
ValueCountFrequency (%)
한방내과 324
11.4%
침구과 312
10.9%
한방부인과 298
10.5%
한방재활의학과 295
10.4%
한방소아과 293
10.3%
한방안·이비인후·피부과 283
9.9%
한방신경정신과 269
9.4%
사상체질과 242
8.5%
가정의학과 134
4.7%
내과 85
 
3.0%
Other values (18) 315
11.1%
2024-05-03T19:18:46.868376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 2850
13.5%
, 2525
 
12.0%
2525
 
12.0%
한 1763
 
8.4%
방 1763
 
8.4%
부 613
 
2.9%
인 604
 
2.9%
신 581
 
2.8%
· 566
 
2.7%
의 561
 
2.7%
Other values (40) 6731
31.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15466
73.4%
Other Punctuation 3091
 
14.7%
Space Separator 2525
 
12.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 2850
18.4%
한 1763
 
11.4%
방 1763
 
11.4%
부 613
 
4.0%
인 604
 
3.9%
신 581
 
3.8%
의 561
 
3.6%
학 561
 
3.6%
정 467
 
3.0%
내 409
 
2.6%
Other values (37) 5294
34.2%
Other Punctuation
ValueCountFrequency (%)
, 2525
81.7%
· 566
 
18.3%
Space Separator
ValueCountFrequency (%)
2525
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15466
73.4%
Common 5616
 
26.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 2850
18.4%
한 1763
 
11.4%
방 1763
 
11.4%
부 613
 
4.0%
인 604
 
3.9%
신 581
 
3.8%
의 561
 
3.6%
학 561
 
3.6%
정 467
 
3.0%
내 409
 
2.6%
Other values (37) 5294
34.2%
Common
ValueCountFrequency (%)
, 2525
45.0%
2525
45.0%
· 566
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15466
73.4%
ASCII 5050
 
24.0%
None 566
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 2850
18.4%
한 1763
 
11.4%
방 1763
 
11.4%
부 613
 
4.0%
인 604
 
3.9%
신 581
 
3.8%
의 561
 
3.6%
학 561
 
3.6%
정 467
 
3.0%
내 409
 
2.6%
Other values (37) 5294
34.2%
ASCII
ValueCountFrequency (%)
, 2525
50.0%
2525
50.0%
None
ValueCountFrequency (%)
· 566
100.0%

연면적(㎡)
Real number (ℝ)

HIGH CORRELATION 

Distinct217
Distinct (%)66.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1820.8346
Minimum0
Maximum9396
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-05-03T19:18:47.291900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile501.692
Q11114.55
median1535.7
Q32083
95-th percentile4416.78
Maximum9396
Range9396
Interquartile range (IQR)968.45

Descriptive statistics

Standard deviation1235.2841
Coefficient of variation (CV)0.67841642
Kurtosis8.8578385
Mean1820.8346
Median Absolute Deviation (MAD)454.39
Skewness2.468752
Sum591771.24
Variance1525926.8
MonotonicityNot monotonic
2024-05-03T19:18:47.830422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1661.84 4
 
1.2%
909.36 4
 
1.2%
1894.1 3
 
0.9%
1800.97 3
 
0.9%
1615.95 3
 
0.9%
1306.72 3
 
0.9%
898.22 3
 
0.9%
5049.3 2
 
0.6%
1636.0 2
 
0.6%
2085.74 2
 
0.6%
Other values (207) 296
91.1%
ValueCountFrequency (%)
0.0 1
0.3%
346.56 1
0.3%
354.44 1
0.3%
383.95 1
0.3%
403.4 1
0.3%
427.88 2
0.6%
429.2 1
0.3%
458.5 1
0.3%
465.2 1
0.3%
472.0 2
0.6%
ValueCountFrequency (%)
9396.0 1
0.3%
8120.0 1
0.3%
7780.0 1
0.3%
6675.69 2
0.6%
5552.0 2
0.6%
5049.3 2
0.6%
4988.22 2
0.6%
4988.0 2
0.6%
4468.09 2
0.6%
4454.43 2
0.6%

소재지도로명주소
Text

Distinct229
Distinct (%)70.5%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-05-03T19:18:48.511588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length54
Mean length37.086154
Min length15

Characters and Unicode

Total characters12053
Distinct characters325
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

Unique133 ?
Unique (%)40.9%

Sample

1st row경기도 가평군 청평면 북한강로1604번길 64-28
2nd row경기도 고양시 덕양구 지축로 52, 스타스퀘어 빌딩 5층~8층 (지축동)
3rd row경기도 고양시 덕양구 지축로 74, 벨라미 3~4층 전체호, 5층 일부(506~518)호 (지축동)
4th row경기도 고양시 덕양구 지축1로 41, 5층~6층 401호~405호 (지축동)
5th row경기도 고양시 덕양구 화신로 263, 브릿지타워(BRIDGE TOWER) 701,702,703,704,707, 8층(전체)호 (화정동)
ValueCountFrequency (%)
경기도 325
 
13.6%
안산시 57
 
2.4%
시흥시 40
 
1.7%
단원구 34
 
1.4%
부천시 31
 
1.3%
원미구 24
 
1.0%
상록구 23
 
1.0%
2층 22
 
0.9%
5층 22
 
0.9%
김포시 21
 
0.9%
Other values (757) 1788
74.9%
2024-05-03T19:18:50.114333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2062
 
17.1%
, 563
 
4.7%
1 422
 
3.5%
시 381
 
3.2%
동 370
 
3.1%
기 344
 
2.9%
경 343
 
2.8%
도 336
 
2.8%
) 319
 
2.6%
( 319
 
2.6%
Other values (315) 6594
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6307
52.3%
Decimal Number 2238
 
18.6%
Space Separator 2062
 
17.1%
Other Punctuation 563
 
4.7%
Close Punctuation 319
 
2.6%
Open Punctuation 319
 
2.6%
Math Symbol 120
 
1.0%
Dash Punctuation 67
 
0.6%
Uppercase Letter 57
 
0.5%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 381
 
6.0%
동 370
 
5.9%
기 344
 
5.5%
경 343
 
5.4%
도 336
 
5.3%
층 317
 
5.0%
로 304
 
4.8%
구 193
 
3.1%
호 120
 
1.9%
원 113
 
1.8%
Other values (281) 3486
55.3%
Uppercase Letter
ValueCountFrequency (%)
C 8
14.0%
E 8
14.0%
B 8
14.0%
T 4
 
7.0%
R 4
 
7.0%
H 4
 
7.0%
G 4
 
7.0%
W 3
 
5.3%
V 2
 
3.5%
L 2
 
3.5%
Other values (7) 10
17.5%
Decimal Number
ValueCountFrequency (%)
1 422
18.9%
3 276
12.3%
2 274
12.2%
0 264
11.8%
4 262
11.7%
5 243
10.9%
6 179
8.0%
7 124
 
5.5%
8 115
 
5.1%
9 79
 
3.5%
Space Separator
ValueCountFrequency (%)
2062
100.0%
Other Punctuation
ValueCountFrequency (%)
, 563
100.0%
Close Punctuation
ValueCountFrequency (%)
) 319
100.0%
Open Punctuation
ValueCountFrequency (%)
( 319
100.0%
Math Symbol
ValueCountFrequency (%)
~ 120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 67
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6305
52.3%
Common 5688
47.2%
Latin 58
 
0.5%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 381
 
6.0%
동 370
 
5.9%
기 344
 
5.5%
경 343
 
5.4%
도 336
 
5.3%
층 317
 
5.0%
로 304
 
4.8%
구 193
 
3.1%
호 120
 
1.9%
원 113
 
1.8%
Other values (280) 3484
55.3%
Latin
ValueCountFrequency (%)
C 8
13.8%
E 8
13.8%
B 8
13.8%
T 4
 
6.9%
R 4
 
6.9%
H 4
 
6.9%
G 4
 
6.9%
W 3
 
5.2%
V 2
 
3.4%
L 2
 
3.4%
Other values (8) 11
19.0%
Common
ValueCountFrequency (%)
2062
36.3%
, 563
 
9.9%
1 422
 
7.4%
) 319
 
5.6%
( 319
 
5.6%
3 276
 
4.9%
2 274
 
4.8%
0 264
 
4.6%
4 262
 
4.6%
5 243
 
4.3%
Other values (6) 684
 
12.0%
Han
ValueCountFrequency (%)
家 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6305
52.3%
ASCII 5745
47.7%
CJK 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2062
35.9%
, 563
 
9.8%
1 422
 
7.3%
) 319
 
5.6%
( 319
 
5.6%
3 276
 
4.8%
2 274
 
4.8%
0 264
 
4.6%
4 262
 
4.6%
5 243
 
4.2%
Other values (23) 741
 
12.9%
Hangul
ValueCountFrequency (%)
시 381
 
6.0%
동 370
 
5.9%
기 344
 
5.5%
경 343
 
5.4%
도 336
 
5.3%
층 317
 
5.0%
로 304
 
4.8%
구 193
 
3.1%
호 120
 
1.9%
원 113
 
1.8%
Other values (280) 3484
55.3%
CJK
ValueCountFrequency (%)
家 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

소재지지번주소
Text

Distinct231
Distinct (%)71.1%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-05-03T19:18:50.923289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length43
Mean length29.32
Min length11

Characters and Unicode

Total characters9529
Distinct characters278
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

Unique141 ?
Unique (%)43.4%

Sample

1st row경기도 가평군 청평면 삼회리 502번지
2nd row경기도 고양시 덕양구 지축동 996-1 스타스퀘어 빌딩
3rd row경기도 고양시 덕양구 지축동 1005-5 벨라미
4th row경기도 고양시 덕양구 지축동 0
5th row경기도 고양시 덕양구 화정동 1000번지 브릿지타워 701,702,703,704,707, 8층(전체)호
ValueCountFrequency (%)
경기도 322
 
16.2%
안산시 57
 
2.9%
시흥시 40
 
2.0%
단원구 34
 
1.7%
부천시 31
 
1.6%
원미구 23
 
1.2%
상록구 23
 
1.2%
김포시 21
 
1.1%
고잔동 20
 
1.0%
1호 20
 
1.0%
Other values (620) 1394
70.2%
2024-05-03T19:18:52.300622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1662
 
17.4%
1 403
 
4.2%
시 364
 
3.8%
동 342
 
3.6%
기 336
 
3.5%
도 331
 
3.5%
경 327
 
3.4%
지 258
 
2.7%
2 251
 
2.6%
0 240
 
2.5%
Other values (268) 5015
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5239
55.0%
Decimal Number 2112
22.2%
Space Separator 1662
 
17.4%
Other Punctuation 196
 
2.1%
Dash Punctuation 183
 
1.9%
Math Symbol 78
 
0.8%
Uppercase Letter 26
 
0.3%
Close Punctuation 16
 
0.2%
Open Punctuation 16
 
0.2%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 364
 
6.9%
동 342
 
6.5%
기 336
 
6.4%
도 331
 
6.3%
경 327
 
6.2%
지 258
 
4.9%
번 221
 
4.2%
층 200
 
3.8%
구 189
 
3.6%
호 138
 
2.6%
Other values (238) 2533
48.3%
Uppercase Letter
ValueCountFrequency (%)
C 6
23.1%
H 4
15.4%
E 4
15.4%
B 2
 
7.7%
L 2
 
7.7%
T 2
 
7.7%
A 1
 
3.8%
N 1
 
3.8%
Z 1
 
3.8%
W 1
 
3.8%
Other values (2) 2
 
7.7%
Decimal Number
ValueCountFrequency (%)
1 403
19.1%
2 251
11.9%
0 240
11.4%
5 231
10.9%
3 229
10.8%
4 194
9.2%
6 158
 
7.5%
7 153
 
7.2%
9 135
 
6.4%
8 118
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 195
99.5%
. 1
 
0.5%
Space Separator
ValueCountFrequency (%)
1662
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 183
100.0%
Math Symbol
ValueCountFrequency (%)
~ 78
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5237
55.0%
Common 4263
44.7%
Latin 27
 
0.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 364
 
7.0%
동 342
 
6.5%
기 336
 
6.4%
도 331
 
6.3%
경 327
 
6.2%
지 258
 
4.9%
번 221
 
4.2%
층 200
 
3.8%
구 189
 
3.6%
호 138
 
2.6%
Other values (237) 2531
48.3%
Common
ValueCountFrequency (%)
1662
39.0%
1 403
 
9.5%
2 251
 
5.9%
0 240
 
5.6%
5 231
 
5.4%
3 229
 
5.4%
, 195
 
4.6%
4 194
 
4.6%
- 183
 
4.3%
6 158
 
3.7%
Other values (7) 517
 
12.1%
Latin
ValueCountFrequency (%)
C 6
22.2%
H 4
14.8%
E 4
14.8%
B 2
 
7.4%
L 2
 
7.4%
T 2
 
7.4%
A 1
 
3.7%
N 1
 
3.7%
Ⅱ 1
 
3.7%
Z 1
 
3.7%
Other values (3) 3
11.1%
Han
ValueCountFrequency (%)
家 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5237
55.0%
ASCII 4289
45.0%
CJK 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1662
38.8%
1 403
 
9.4%
2 251
 
5.9%
0 240
 
5.6%
5 231
 
5.4%
3 229
 
5.3%
, 195
 
4.5%
4 194
 
4.5%
- 183
 
4.3%
6 158
 
3.7%
Other values (19) 543
 
12.7%
Hangul
ValueCountFrequency (%)
시 364
 
7.0%
동 342
 
6.5%
기 336
 
6.4%
도 331
 
6.3%
경 327
 
6.2%
지 258
 
4.9%
번 221
 
4.2%
층 200
 
3.8%
구 189
 
3.6%
호 138
 
2.6%
Other values (237) 2531
48.3%
CJK
ValueCountFrequency (%)
家 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct169
Distinct (%)52.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14438.425
Minimum10012
Maximum18611
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-05-03T19:18:52.912082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10012
5-th percentile10089
Q112919
median14916
Q315591
95-th percentile18242
Maximum18611
Range8599
Interquartile range (IQR)2672

Descriptive statistics

Standard deviation2326.7565
Coefficient of variation (CV)0.1611503
Kurtosis-0.59992333
Mean14438.425
Median Absolute Deviation (MAD)1388
Skewness-0.32836592
Sum4692488
Variance5413795.6
MonotonicityNot monotonic
2024-05-03T19:18:53.388638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10071 9
 
2.8%
14948 7
 
2.2%
10585 7
 
2.2%
15630 6
 
1.8%
15461 6
 
1.8%
12919 6
 
1.8%
10113 4
 
1.2%
15011 4
 
1.2%
14912 4
 
1.2%
17006 4
 
1.2%
Other values (159) 268
82.5%
ValueCountFrequency (%)
10012 1
 
0.3%
10029 2
 
0.6%
10071 9
2.8%
10077 3
 
0.9%
10083 2
 
0.6%
10113 4
1.2%
10326 2
 
0.6%
10381 2
 
0.6%
10387 1
 
0.3%
10414 1
 
0.3%
ValueCountFrequency (%)
18611 2
0.6%
18606 1
 
0.3%
18484 3
0.9%
18466 1
 
0.3%
18443 2
0.6%
18434 1
 
0.3%
18309 1
 
0.3%
18270 2
0.6%
18266 1
 
0.3%
18256 2
0.6%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct192
Distinct (%)59.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.415978
Minimum36.98933
Maximum38.091197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-05-03T19:18:53.859757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.98933
5-th percentile37.078492
Q137.303947
median37.392244
Q337.519616
95-th percentile37.732852
Maximum38.091197
Range1.1018669
Interquartile range (IQR)0.21566953

Descriptive statistics

Standard deviation0.18317057
Coefficient of variation (CV)0.0048955173
Kurtosis0.11902356
Mean37.415978
Median Absolute Deviation (MAD)0.10998391
Skewness0.081561229
Sum12160.193
Variance0.033551458
MonotonicityNot monotonic
2024-05-03T19:18:54.361362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.2846394091 6
 
1.8%
37.3135475014 6
 
1.8%
37.4399149017 5
 
1.5%
37.5537508746 4
 
1.2%
37.4447408301 4
 
1.2%
36.9893298788 4
 
1.2%
37.6430559536 3
 
0.9%
37.3520978048 3
 
0.9%
37.6453298622 3
 
0.9%
37.6454645894 3
 
0.9%
Other values (182) 284
87.4%
ValueCountFrequency (%)
36.9893298788 4
1.2%
36.9926695383 2
0.6%
36.9989221214 2
0.6%
37.0078368535 1
 
0.3%
37.0168974507 2
0.6%
37.0196622525 2
0.6%
37.0468128148 1
 
0.3%
37.0564861183 1
 
0.3%
37.0695255894 2
0.6%
37.1143580002 2
0.6%
ValueCountFrequency (%)
38.0911967988 1
0.3%
37.8185529608 1
0.3%
37.7558650433 1
0.3%
37.7545225748 1
0.3%
37.7540043303 1
0.3%
37.7516717165 1
0.3%
37.7503907517 2
0.6%
37.7461588031 1
0.3%
37.7453057969 1
0.3%
37.7448652943 1
0.3%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct192
Distinct (%)59.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.92114
Minimum126.5871
Maximum127.63508
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-05-03T19:18:54.898762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.5871
5-th percentile126.68121
Q1126.78904
median126.85342
Q3127.07356
95-th percentile127.18771
Maximum127.63508
Range1.0479815
Interquartile range (IQR)0.28452679

Descriptive statistics

Standard deviation0.17830938
Coefficient of variation (CV)0.0014048832
Kurtosis0.70630462
Mean126.92114
Median Absolute Deviation (MAD)0.10188064
Skewness0.7635358
Sum41249.369
Variance0.031794234
MonotonicityNot monotonic
2024-05-03T19:18:55.524522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8534235772 6
 
1.8%
126.8276826053 6
 
1.8%
126.7854289209 5
 
1.5%
127.1857918529 4
 
1.2%
126.799593328 4
 
1.2%
127.1204348972 4
 
1.2%
127.1211801001 3
 
0.9%
126.7147788697 3
 
0.9%
126.6235711257 3
 
0.9%
126.6812090117 3
 
0.9%
Other values (182) 284
87.4%
ValueCountFrequency (%)
126.5870994059 2
0.6%
126.6227959716 2
0.6%
126.6235711257 3
0.9%
126.6244078438 2
0.6%
126.6266409118 2
0.6%
126.6378211989 1
 
0.3%
126.6663340954 2
0.6%
126.6769939531 1
 
0.3%
126.6812090117 3
0.9%
126.7147788697 3
0.9%
ValueCountFrequency (%)
127.6350809464 1
0.3%
127.6201407328 1
0.3%
127.5056786361 2
0.6%
127.3876603614 1
0.3%
127.2724560602 1
0.3%
127.258404853 1
0.3%
127.2581204458 2
0.6%
127.2446247815 1
0.3%
127.2037925189 2
0.6%
127.1908480352 2
0.6%

Interactions

2024-05-03T19:18:31.497758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:18.643639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:20.470141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:22.365865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:24.313425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:26.322672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:28.299221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:32.111305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:18.899753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:20.726766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:22.659889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:24.567732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:26.588162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:28.585338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:32.471602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:19.143307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:20.959352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:22.915669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:24.828202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:26.846413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:28.908545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:32.812164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:19.419101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:21.254244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:23.179638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:25.234397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:27.167197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:29.321266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:33.058335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:19.662819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:21.537332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:23.431381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:25.525751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:27.430818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:29.716873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:33.368299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:19.946362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:21.834003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:23.717094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:25.785702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:27.723545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:30.265922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:33.715056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:20.206054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:22.056780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:24.011633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:26.049850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:27.977125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:18:30.995103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T19:18:55.866737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명폐업일자병상수(개)의료인수(명)입원실수(개)연면적(㎡)소재지우편번호WGS84위도WGS84경도
시군명1.0000.5011.0000.7010.4680.5360.5440.9890.9830.972
영업상태명0.5011.0001.0000.2730.5190.5430.2920.1580.3660.202
폐업일자1.0001.0001.0001.0001.0001.0000.0001.0001.0001.000
병상수(개)0.7010.2731.0001.0000.7050.8210.5180.3640.4030.205
의료인수(명)0.4680.5191.0000.7051.0000.8440.6880.3850.0650.163
입원실수(개)0.5360.5431.0000.8210.8441.0000.5870.4000.1970.174
연면적(㎡)0.5440.2920.0000.5180.6880.5871.0000.3310.2900.272
소재지우편번호0.9890.1581.0000.3640.3850.4000.3311.0000.8470.898
WGS84위도0.9830.3661.0000.4030.0650.1970.2900.8471.0000.644
WGS84경도0.9720.2021.0000.2050.1630.1740.2720.8980.6441.000
2024-05-03T19:18:56.235421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명시군명
영업상태명1.0000.248
시군명0.2481.000
2024-05-03T19:18:56.494647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
병상수(개)의료인수(명)입원실수(개)연면적(㎡)소재지우편번호WGS84위도WGS84경도시군명영업상태명
병상수(개)1.0000.5070.8060.656-0.1000.064-0.0370.3340.189
의료인수(명)0.5071.0000.5440.5520.055-0.1010.2250.1940.251
입원실수(개)0.8060.5441.0000.670-0.0870.0400.0520.2310.265
연면적(㎡)0.6560.5520.6701.000-0.1020.0690.1220.2280.189
소재지우편번호-0.1000.055-0.087-0.1021.000-0.9340.2210.8960.093
WGS84위도0.064-0.1010.0400.069-0.9341.000-0.2940.8620.240
WGS84경도-0.0370.2250.0520.1220.221-0.2941.0000.8100.121
시군명0.3340.1940.2310.2280.8960.8620.8101.0000.248
영업상태명0.1890.2510.2650.1890.0930.2400.1210.2481.000

Missing values

2024-05-03T19:18:34.423062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T19:18:35.467996image/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

시군명사업장명인허가일자영업상태명폐업일자병상수(개)의료기관종별명의료인수(명)입원실수(개)진료과목내용연면적(㎡)소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0가평군청평푸른숲한방병원2014-12-05폐업2017-09-0268<NA>1723내과, 가정의학과, 한방내과, 한방부인과, 한방소아과, 사상체질과, 침구과1689.12경기도 가평군 청평면 북한강로1604번길 64-28경기도 가평군 청평면 삼회리 502번지1245837.663666127.38766
1고양시소통한방병원2023-02-27영업/정상<NA>51<NA>1328가정의학과, 한방내과, 침구과2329.0경기도 고양시 덕양구 지축로 52, 스타스퀘어 빌딩 5층~8층 (지축동)경기도 고양시 덕양구 지축동 996-1 스타스퀘어 빌딩1058537.64987126.913956
2고양시바른쎌한방병원2023-07-18영업/정상<NA>53<NA>724내과, 피부과, 재활의학과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방재활의학과, 침구과1894.1경기도 고양시 덕양구 지축로 74, 벨라미 3~4층 전체호, 5층 일부(506~518)호 (지축동)경기도 고양시 덕양구 지축동 1005-5 벨라미1058537.649106126.91615
3고양시여기한방병원2022-12-02영업/정상<NA>62<NA>520내과, 정형외과, 영상의학과, 한방내과, 한방부인과, 한방소아과, 한방재활의학과, 사상체질과, 침구과1297.56경기도 고양시 덕양구 지축1로 41, 5층~6층 401호~405호 (지축동)경기도 고양시 덕양구 지축동 01058537.648676126.914963
4고양시더하다한방병원2020-09-03영업/정상<NA>47<NA>2414정형외과, 가정의학과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과1285.06경기도 고양시 덕양구 화신로 263, 브릿지타워(BRIDGE TOWER) 701,702,703,704,707, 8층(전체)호 (화정동)경기도 고양시 덕양구 화정동 1000번지 브릿지타워 701,702,703,704,707, 8층(전체)호1050337.630453126.832046
5고양시동국대학교일산불교한방병원2005-07-11영업/정상<NA>71<NA>5022한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과4988.0경기도 고양시 일산동구 동국로 27 (식사동, 동국대학교일산병원)경기도 고양시 일산동구 식사동 814외9필지1032637.676439126.805563
6고양시일산365한방병원2022-05-12영업/정상<NA>51<NA>1418내과, 정형외과, 신경외과, 산부인과, 소아청소년과, 이비인후과, 피부과, 재활의학과, 가정의학과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과3177.17경기도 고양시 일산서구 중앙로 1581, 2층 203~209호 (대화동)경기도 고양시 일산서구 대화동 22191038137.676145126.746099
7고양시일산자생한방병원2009-10-01영업/정상<NA>52<NA>4013내과, 영상의학과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과2083.0경기도 고양시 일산동구 중앙로 1130, B2-01~19호 (마두동, 강촌마을6단지아파트)경기도 고양시 일산동구 마두동 806번지 강촌마을6단지아파트1042237.650121126.780211
8고양시일산자생한방병원2009-10-01영업중<NA>52<NA>4013내과, 영상의학과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과2083.0경기도 고양시 일산동구 중앙로 1130, B2-01~19호 (마두동, 강촌마을6단지아파트)경기도 고양시 일산동구 마두동 806번지 강촌마을6단지아파트1042237.650121126.780211
9고양시동국대학교일산불교한방병원2005-07-11영업중<NA>71<NA>4922한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과4988.0경기도 고양시 일산동구 동국로 27 (식사동, 동국대학교일산병원)경기도 고양시 일산동구 식사동 814외9필지1032637.676439126.805563
시군명사업장명인허가일자영업상태명폐업일자병상수(개)의료기관종별명의료인수(명)입원실수(개)진료과목내용연면적(㎡)소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
315화성시다래한방병원2022-08-24영업중<NA>30<NA>1211소아청소년과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과830.29경기도 화성시 향남읍 상신하길로298번길 7-29, 4층경기도 화성시 향남읍 하길리 1470-6번지 4층1861137.114358126.912605
316화성시한송한방병원2020-10-15폐업2023-12-2240<NA>411가정의학과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과1548.3경기도 화성시 남양읍 시청로160번길 46, 6,7층경기도 화성시 남양읍 남양리 2319-4번지 6,7층1827037.198816126.825648
317화성시송산한방병원2020-07-14폐업2024-02-2948<NA>514가정의학과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과1358.0경기도 화성시 노들길 6-8, 3,4,5층 (새솔동)경기도 화성시 새솔동 99-5번지 3,4,5층1824237.279989126.819747
318화성시경희동탄한방병원2018-03-19폐업2022-06-0149<NA>917가정의학과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과1198.0경기도 화성시 동탄솔빛로 57, 삼성미즈빌딩 2,3,4층 (반송동)경기도 화성시 반송동 220-3번지 삼성미즈빌딩 2,3,4층1844337.194109127.073564
319화성시한독한방병원2022-01-14폐업2023-05-0858<NA>617내과, 피부과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과1142.24경기도 화성시 동탄신리천로 411, 우성스타타워 4층,5층 (목동)경기도 화성시 목동 487-5번지 우성스타타워 4층,5층1848437.182706127.124088
320화성시화성제일한방병원2022-10-25폐업2024-01-3146<NA>1412가정의학과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과1233.88경기도 화성시 남양읍 남양로920번길 12, 4층경기도 화성시 남양읍 북양리 692-11825637.217753126.833369
321화성시송산한방병원2020-07-14폐업2024-02-2948<NA>514가정의학과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과1358.0경기도 화성시 노들길 6-8, 3,4,5층 (새솔동)경기도 화성시 새솔동 99-5번지 3,4,5층1824237.279989126.819747
322화성시화성제일한방병원2022-10-25폐업2024-01-3146<NA>1412가정의학과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과1233.88경기도 화성시 남양읍 남양로920번길 12, 4층경기도 화성시 남양읍 북양리 692-11825637.217753126.833369
323화성시동탄목동한방병원2020-04-22폐업2021-12-2558<NA>1617가정의학과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과1142.24경기도 화성시 동탄신리천로 411, 4,5층 (목동)경기도 화성시 목동 산 18번지1848437.182706127.124088
324화성시서울한방병원2019-06-12폐업2020-07-1544<NA>712내과, 정형외과, 신경외과, 산부인과, 이비인후과, 피부과, 영상의학과, 재활의학과, 가정의학과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과1548.3경기도 화성시 남양읍 시청로160번길 46, 6,7층경기도 화성시 남양읍 남양리 2319번지 4호1827037.198816126.825648

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시군명사업장명인허가일자영업상태명폐업일자병상수(개)의료인수(명)입원실수(개)진료과목내용연면적(㎡)소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도# duplicates
0화성시송산한방병원2020-07-14폐업2024-02-2948514가정의학과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과1358.0경기도 화성시 노들길 6-8, 3,4,5층 (새솔동)경기도 화성시 새솔동 99-5번지 3,4,5층1824237.279989126.8197472
1화성시화성제일한방병원2022-10-25폐업2024-01-31461412가정의학과, 한방내과, 한방부인과, 한방소아과, 한방안·이비인후·피부과, 한방신경정신과, 한방재활의학과, 사상체질과, 침구과1233.88경기도 화성시 남양읍 남양로920번길 12, 4층경기도 화성시 남양읍 북양리 692-11825637.217753126.8333692