Overview

Dataset statistics

Number of variables18
Number of observations555
Missing cells794
Missing cells (%)7.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory79.3 KiB
Average record size in memory146.2 B

Variable types

Text11
Categorical3
Numeric2
DateTime2

Dataset

Description대구광역시_북구_병의원_현황_20190819
Author대구광역시 북구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15025621&dataSetDetailId=150256211af2abe75b39b_201908281103&provdMethod=FILE

Alerts

영업상태 has constant value ""Constant
데이터기준일자 has constant value ""Constant
금요일 진료 has a high cardinality: 51 distinct valuesHigh cardinality
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
금요일 진료 is highly overall correlated with 공휴일 진료High correlation
공휴일 진료 is highly overall correlated with 금요일 진료High correlation
공휴일 진료 is highly imbalanced (68.9%)Imbalance
소재지지번주소 has 119 (21.4%) missing valuesMissing
토요일 진료 has 132 (23.8%) missing valuesMissing
일요일 진료 has 532 (95.9%) missing valuesMissing
병원명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 19:49:06.725196
Analysis finished2023-12-10 19:49:10.363091
Duration3.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

병원명
Text

UNIQUE 

Distinct555
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2023-12-11T04:49:10.619287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length7.4936937
Min length3

Characters and Unicode

Total characters4159
Distinct characters301
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique555 ?
Unique (%)100.0%

Sample

1st row2080연합피부과의원
2nd row365늘속편한내과의원
3rd rowM병원
4th row가람한의원
5th row가원한의원
ValueCountFrequency (%)
대구병원 2
 
0.4%
의료법인 2
 
0.4%
2080연합피부과의원 1
 
0.2%
이앤이치과의원 1
 
0.2%
이상재정형외과의원 1
 
0.2%
이인구치과의원 1
 
0.2%
이유원치과의원 1
 
0.2%
이원기연합내과의원 1
 
0.2%
이엔아이치과의원 1
 
0.2%
이아름다운치과의원 1
 
0.2%
Other values (558) 558
97.9%
2023-12-11T04:49:11.256841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 573
 
13.8%
의 556
 
13.4%
과 357
 
8.6%
한 157
 
3.8%
치 146
 
3.5%
연 77
 
1.9%
이 73
 
1.8%
합 69
 
1.7%
정 60
 
1.4%
인 51
 
1.2%
Other values (291) 2040
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4121
99.1%
Space Separator 15
 
0.4%
Decimal Number 8
 
0.2%
Uppercase Letter 7
 
0.2%
Dash Punctuation 3
 
0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 573
 
13.9%
의 556
 
13.5%
과 357
 
8.7%
한 157
 
3.8%
치 146
 
3.5%
연 77
 
1.9%
이 73
 
1.8%
합 69
 
1.7%
정 60
 
1.5%
인 51
 
1.2%
Other values (275) 2002
48.6%
Decimal Number
ValueCountFrequency (%)
3 2
25.0%
0 2
25.0%
2 1
12.5%
8 1
12.5%
5 1
12.5%
6 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
S 3
42.9%
J 1
 
14.3%
A 1
 
14.3%
K 1
 
14.3%
M 1
 
14.3%
Space Separator
ValueCountFrequency (%)
15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4121
99.1%
Common 30
 
0.7%
Latin 8
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 573
 
13.9%
의 556
 
13.5%
과 357
 
8.7%
한 157
 
3.8%
치 146
 
3.5%
연 77
 
1.9%
이 73
 
1.8%
합 69
 
1.7%
정 60
 
1.5%
인 51
 
1.2%
Other values (275) 2002
48.6%
Common
ValueCountFrequency (%)
15
50.0%
- 3
 
10.0%
3 2
 
6.7%
0 2
 
6.7%
) 2
 
6.7%
( 2
 
6.7%
2 1
 
3.3%
8 1
 
3.3%
5 1
 
3.3%
6 1
 
3.3%
Latin
ValueCountFrequency (%)
S 3
37.5%
e 1
 
12.5%
J 1
 
12.5%
A 1
 
12.5%
K 1
 
12.5%
M 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4121
99.1%
ASCII 38
 
0.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 573
 
13.9%
의 556
 
13.5%
과 357
 
8.7%
한 157
 
3.8%
치 146
 
3.5%
연 77
 
1.9%
이 73
 
1.8%
합 69
 
1.7%
정 60
 
1.5%
인 51
 
1.2%
Other values (275) 2002
48.6%
ASCII
ValueCountFrequency (%)
15
39.5%
S 3
 
7.9%
- 3
 
7.9%
3 2
 
5.3%
0 2
 
5.3%
) 2
 
5.3%
( 2
 
5.3%
e 1
 
2.6%
J 1
 
2.6%
A 1
 
2.6%
Other values (6) 6
 
15.8%

영업상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
영업중
555 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 555
100.0%

Length

2023-12-11T04:49:11.502296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:49:11.682964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 555
100.0%

소재지도로명주소
Text

Distinct508
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2023-12-11T04:49:12.222996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length47
Mean length27.837838
Min length20

Characters and Unicode

Total characters15450
Distinct characters195
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique468 ?
Unique (%)84.3%

Sample

1st row대구광역시 북구 침산로 138 (침산동)
2nd row대구광역시 북구 학정로 415, 2층 (동천동, 메가타운)
3rd row대구광역시 북구 팔달로 147 (노원동3가)
4th row대구광역시 북구 대학로 5 (산격동)
5th row대구광역시 북구 칠곡중앙대로 457 (관음동)
ValueCountFrequency (%)
대구광역시 555
 
17.0%
북구 555
 
17.0%
2층 95
 
2.9%
칠곡중앙대로 83
 
2.5%
산격동 72
 
2.2%
동천동 66
 
2.0%
태전동 62
 
1.9%
동북로 60
 
1.8%
3층 56
 
1.7%
침산동 55
 
1.7%
Other values (547) 1609
49.2%
2023-12-11T04:49:13.077259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2716
17.6%
구 1165
 
7.5%
동 761
 
4.9%
대 735
 
4.8%
북 617
 
4.0%
시 570
 
3.7%
광 560
 
3.6%
역 556
 
3.6%
로 555
 
3.6%
) 554
 
3.6%
Other values (185) 6661
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8772
56.8%
Space Separator 2716
 
17.6%
Decimal Number 2352
 
15.2%
Close Punctuation 554
 
3.6%
Open Punctuation 554
 
3.6%
Other Punctuation 443
 
2.9%
Dash Punctuation 35
 
0.2%
Math Symbol 13
 
0.1%
Uppercase Letter 8
 
0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1165
13.3%
동 761
 
8.7%
대 735
 
8.4%
북 617
 
7.0%
시 570
 
6.5%
광 560
 
6.4%
역 556
 
6.3%
로 555
 
6.3%
층 267
 
3.0%
산 206
 
2.3%
Other values (158) 2780
31.7%
Decimal Number
ValueCountFrequency (%)
1 454
19.3%
2 438
18.6%
3 325
13.8%
4 284
12.1%
0 239
10.2%
5 175
 
7.4%
6 119
 
5.1%
9 119
 
5.1%
7 103
 
4.4%
8 96
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
K 1
12.5%
S 1
12.5%
A 1
12.5%
D 1
12.5%
U 1
12.5%
C 1
12.5%
B 1
12.5%
M 1
12.5%
Lowercase Letter
ValueCountFrequency (%)
t 1
33.3%
p 1
33.3%
a 1
33.3%
Space Separator
ValueCountFrequency (%)
2716
100.0%
Close Punctuation
ValueCountFrequency (%)
) 554
100.0%
Open Punctuation
ValueCountFrequency (%)
( 554
100.0%
Other Punctuation
ValueCountFrequency (%)
, 443
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8772
56.8%
Common 6667
43.2%
Latin 11
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1165
13.3%
동 761
 
8.7%
대 735
 
8.4%
북 617
 
7.0%
시 570
 
6.5%
광 560
 
6.4%
역 556
 
6.3%
로 555
 
6.3%
층 267
 
3.0%
산 206
 
2.3%
Other values (158) 2780
31.7%
Common
ValueCountFrequency (%)
2716
40.7%
) 554
 
8.3%
( 554
 
8.3%
1 454
 
6.8%
, 443
 
6.6%
2 438
 
6.6%
3 325
 
4.9%
4 284
 
4.3%
0 239
 
3.6%
5 175
 
2.6%
Other values (6) 485
 
7.3%
Latin
ValueCountFrequency (%)
K 1
9.1%
S 1
9.1%
A 1
9.1%
D 1
9.1%
U 1
9.1%
C 1
9.1%
B 1
9.1%
t 1
9.1%
p 1
9.1%
a 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8772
56.8%
ASCII 6678
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2716
40.7%
) 554
 
8.3%
( 554
 
8.3%
1 454
 
6.8%
, 443
 
6.6%
2 438
 
6.6%
3 325
 
4.9%
4 284
 
4.3%
0 239
 
3.6%
5 175
 
2.6%
Other values (17) 496
 
7.4%
Hangul
ValueCountFrequency (%)
구 1165
13.3%
동 761
 
8.7%
대 735
 
8.4%
북 617
 
7.0%
시 570
 
6.5%
광 560
 
6.4%
역 556
 
6.3%
로 555
 
6.3%
층 267
 
3.0%
산 206
 
2.3%
Other values (158) 2780
31.7%

소재지지번주소
Text

MISSING 

Distinct417
Distinct (%)95.6%
Missing119
Missing (%)21.4%
Memory size4.5 KiB
2023-12-11T04:49:13.523118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length43
Mean length25.777523
Min length18

Characters and Unicode

Total characters11239
Distinct characters158
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique399 ?
Unique (%)91.5%

Sample

1st row대구광역시 북구 침산2동 285번지 5호 명성프라임 401호
2nd row대구광역시 북구 동천동 912번지 3호 2층
3rd row대구광역시 북구 산격4동 1382번지 33호
4th row대구광역시 북구 관음동 1386번지 15호 3층
5th row대구광역시 북구 동천동 877번지 1호 2층
ValueCountFrequency (%)
대구광역시 436
 
17.7%
북구 436
 
17.7%
2층 74
 
3.0%
1호 57
 
2.3%
동천동 54
 
2.2%
3호 47
 
1.9%
4호 37
 
1.5%
3층 35
 
1.4%
태전동 32
 
1.3%
2호 32
 
1.3%
Other values (403) 1219
49.6%
2023-12-11T04:49:14.200809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2036
18.1%
구 895
 
8.0%
동 520
 
4.6%
대 470
 
4.2%
1 465
 
4.1%
2 454
 
4.0%
지 447
 
4.0%
시 440
 
3.9%
광 440
 
3.9%
북 437
 
3.9%
Other values (148) 4635
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6423
57.1%
Decimal Number 2541
 
22.6%
Space Separator 2036
 
18.1%
Close Punctuation 94
 
0.8%
Open Punctuation 94
 
0.8%
Other Punctuation 38
 
0.3%
Uppercase Letter 7
 
0.1%
Math Symbol 4
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 895
13.9%
동 520
 
8.1%
대 470
 
7.3%
지 447
 
7.0%
시 440
 
6.9%
광 440
 
6.9%
북 437
 
6.8%
역 436
 
6.8%
번 436
 
6.8%
호 435
 
6.8%
Other values (126) 1467
22.8%
Decimal Number
ValueCountFrequency (%)
1 465
18.3%
2 454
17.9%
3 346
13.6%
0 232
9.1%
4 200
7.9%
6 193
7.6%
5 176
 
6.9%
7 173
 
6.8%
9 167
 
6.6%
8 135
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
U 2
28.6%
S 1
14.3%
K 1
14.3%
A 1
14.3%
M 1
14.3%
B 1
14.3%
Space Separator
ValueCountFrequency (%)
2036
100.0%
Close Punctuation
ValueCountFrequency (%)
) 94
100.0%
Open Punctuation
ValueCountFrequency (%)
( 94
100.0%
Other Punctuation
ValueCountFrequency (%)
, 38
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6423
57.1%
Common 4809
42.8%
Latin 7
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 895
13.9%
동 520
 
8.1%
대 470
 
7.3%
지 447
 
7.0%
시 440
 
6.9%
광 440
 
6.9%
북 437
 
6.8%
역 436
 
6.8%
번 436
 
6.8%
호 435
 
6.8%
Other values (126) 1467
22.8%
Common
ValueCountFrequency (%)
2036
42.3%
1 465
 
9.7%
2 454
 
9.4%
3 346
 
7.2%
0 232
 
4.8%
4 200
 
4.2%
6 193
 
4.0%
5 176
 
3.7%
7 173
 
3.6%
9 167
 
3.5%
Other values (6) 367
 
7.6%
Latin
ValueCountFrequency (%)
U 2
28.6%
S 1
14.3%
K 1
14.3%
A 1
14.3%
M 1
14.3%
B 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6423
57.1%
ASCII 4816
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2036
42.3%
1 465
 
9.7%
2 454
 
9.4%
3 346
 
7.2%
0 232
 
4.8%
4 200
 
4.2%
6 193
 
4.0%
5 176
 
3.7%
7 173
 
3.6%
9 167
 
3.5%
Other values (12) 374
 
7.8%
Hangul
ValueCountFrequency (%)
구 895
13.9%
동 520
 
8.1%
대 470
 
7.3%
지 447
 
7.0%
시 440
 
6.9%
광 440
 
6.9%
북 437
 
6.8%
역 436
 
6.8%
번 436
 
6.8%
호 435
 
6.8%
Other values (126) 1467
22.8%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct367
Distinct (%)66.2%
Missing1
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean35.910546
Minimum35.87457
Maximum35.958848
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2023-12-11T04:49:14.438267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.87457
5-th percentile35.879577
Q135.889117
median35.900436
Q335.933839
95-th percentile35.943976
Maximum35.958848
Range0.084278
Interquartile range (IQR)0.0447215

Descriptive statistics

Standard deviation0.023432868
Coefficient of variation (CV)0.00065253443
Kurtosis-1.4881303
Mean35.910546
Median Absolute Deviation (MAD)0.018453
Skewness0.22563293
Sum19894.443
Variance0.00054909929
MonotonicityNot monotonic
2023-12-11T04:49:14.664574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.901205 11
 
2.0%
35.900436 10
 
1.8%
35.888786 7
 
1.3%
35.89889 7
 
1.3%
35.88784 6
 
1.1%
35.931785 6
 
1.1%
35.92136 5
 
0.9%
35.887651 5
 
0.9%
35.932521 5
 
0.9%
35.941837 5
 
0.9%
Other values (357) 487
87.7%
ValueCountFrequency (%)
35.87457 1
 
0.2%
35.875165 4
0.7%
35.875553 1
 
0.2%
35.875932 1
 
0.2%
35.875944 1
 
0.2%
35.876245 1
 
0.2%
35.876255 1
 
0.2%
35.876569 1
 
0.2%
35.8765747 1
 
0.2%
35.876633 1
 
0.2%
ValueCountFrequency (%)
35.958848 1
0.2%
35.956164 1
0.2%
35.952385 1
0.2%
35.952358 1
0.2%
35.951738 1
0.2%
35.95066 1
0.2%
35.948336 1
0.2%
35.948312 1
0.2%
35.94827 1
0.2%
35.947911 1
0.2%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct366
Distinct (%)66.1%
Missing1
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean128.57807
Minimum128.5099
Maximum128.62884
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2023-12-11T04:49:14.855866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.5099
5-th percentile128.54473
Q1128.55308
median128.57269
Q3128.60461
95-th percentile128.61911
Maximum128.62884
Range0.1189444
Interquartile range (IQR)0.051528

Descriptive statistics

Standard deviation0.027324247
Coefficient of variation (CV)0.00021251095
Kurtosis-1.0253941
Mean128.57807
Median Absolute Deviation (MAD)0.0238085
Skewness-0.081285139
Sum71232.249
Variance0.00074661448
MonotonicityNot monotonic
2023-12-11T04:49:15.074987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.51276 11
 
2.0%
128.61116 10
 
1.8%
128.591893 7
 
1.3%
128.611299 7
 
1.3%
128.592272 6
 
1.1%
128.548612 6
 
1.1%
128.562993 5
 
0.9%
128.598825 5
 
0.9%
128.591853 5
 
0.9%
128.54798 5
 
0.9%
Other values (356) 487
87.7%
ValueCountFrequency (%)
128.5098986 1
 
0.2%
128.5103407 1
 
0.2%
128.51276 11
2.0%
128.540733 1
 
0.2%
128.540904 1
 
0.2%
128.543257 4
 
0.7%
128.54345 1
 
0.2%
128.543573 2
 
0.4%
128.543583 1
 
0.2%
128.544059 2
 
0.4%
ValueCountFrequency (%)
128.628843 1
 
0.2%
128.625765 1
 
0.2%
128.623914 1
 
0.2%
128.6232 2
0.4%
128.622992 1
 
0.2%
128.6226 2
0.4%
128.622296 1
 
0.2%
128.6222011 1
 
0.2%
128.622085 1
 
0.2%
128.622049 3
0.5%

인허가일자
Date

Distinct519
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
Minimum1961-06-12 00:00:00
Maximum2019-07-30 00:00:00
2023-12-11T04:49:15.270774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:49:15.818699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업장 면적
Text

Distinct506
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2023-12-11T04:49:16.434824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.8234234
Min length1

Characters and Unicode

Total characters2677
Distinct characters12
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

Unique474 ?
Unique (%)85.4%

Sample

1st row275
2nd row339.9
3rd row3281.82
4th row36.78
5th row195.21
ValueCountFrequency (%)
0 6
 
1.1%
92.4 6
 
1.1%
165 5
 
0.9%
99 5
 
0.9%
132 3
 
0.5%
103.3 3
 
0.5%
95.7 3
 
0.5%
120 2
 
0.4%
130 2
 
0.4%
79.8 2
 
0.4%
Other values (496) 518
93.3%
2023-12-11T04:49:17.303686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 437
16.3%
1 403
15.1%
2 300
11.2%
5 216
8.1%
4 203
7.6%
6 199
7.4%
9 196
7.3%
3 193
7.2%
7 193
7.2%
8 192
7.2%
Other values (2) 145
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2235
83.5%
Other Punctuation 442
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 403
18.0%
2 300
13.4%
5 216
9.7%
4 203
9.1%
6 199
8.9%
9 196
8.8%
3 193
8.6%
7 193
8.6%
8 192
8.6%
0 140
 
6.3%
Other Punctuation
ValueCountFrequency (%)
. 437
98.9%
, 5
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common 2677
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 437
16.3%
1 403
15.1%
2 300
11.2%
5 216
8.1%
4 203
7.6%
6 199
7.4%
9 196
7.3%
3 193
7.2%
7 193
7.2%
8 192
7.2%
Other values (2) 145
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2677
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 437
16.3%
1 403
15.1%
2 300
11.2%
5 216
8.1%
4 203
7.6%
6 199
7.4%
9 196
7.3%
3 193
7.2%
7 193
7.2%
8 192
7.2%
Other values (2) 145
 
5.4%

월요일 진료
Text

Distinct51
Distinct (%)9.2%
Missing1
Missing (%)0.2%
Memory size4.5 KiB
2023-12-11T04:49:17.683929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters6094
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)4.0%

Sample

1st row09:30~19:00
2nd row08:30~20:30
3rd row09:00~18:00
4th row10:00~17:00
5th row10:00~17:00
ValueCountFrequency (%)
09:00~19:00 107
19.3%
10:00~17:00 96
17.3%
09:30~19:00 60
10.8%
09:30~18:30 40
 
7.2%
09:00~18:30 35
 
6.3%
09:00~18:00 32
 
5.8%
10:00~19:00 29
 
5.2%
09:00~20:00 19
 
3.4%
09:30~18:00 12
 
2.2%
10:00~18:30 11
 
2.0%
Other values (41) 113
20.4%
2023-12-11T04:49:18.198816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2514
41.3%
: 1108
18.2%
1 708
 
11.6%
9 568
 
9.3%
~ 554
 
9.1%
3 271
 
4.4%
8 180
 
3.0%
7 121
 
2.0%
2 52
 
0.9%
6 11
 
0.2%
Other values (2) 7
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4432
72.7%
Other Punctuation 1108
 
18.2%
Math Symbol 554
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2514
56.7%
1 708
 
16.0%
9 568
 
12.8%
3 271
 
6.1%
8 180
 
4.1%
7 121
 
2.7%
2 52
 
1.2%
6 11
 
0.2%
4 5
 
0.1%
5 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
: 1108
100.0%
Math Symbol
ValueCountFrequency (%)
~ 554
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6094
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2514
41.3%
: 1108
18.2%
1 708
 
11.6%
9 568
 
9.3%
~ 554
 
9.1%
3 271
 
4.4%
8 180
 
3.0%
7 121
 
2.0%
2 52
 
0.9%
6 11
 
0.2%
Other values (2) 7
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6094
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2514
41.3%
: 1108
18.2%
1 708
 
11.6%
9 568
 
9.3%
~ 554
 
9.1%
3 271
 
4.4%
8 180
 
3.0%
7 121
 
2.0%
2 52
 
0.9%
6 11
 
0.2%
Other values (2) 7
 
0.1%

화요일 진료
Text

Distinct53
Distinct (%)9.6%
Missing2
Missing (%)0.4%
Memory size4.5 KiB
2023-12-11T04:49:18.573707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters6083
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)4.2%

Sample

1st row09:30~20:00
2nd row08:30~20:30
3rd row09:00~18:00
4th row10:00~17:00
5th row10:00~17:00
ValueCountFrequency (%)
09:00~19:00 106
19.2%
10:00~17:00 96
17.4%
09:30~19:00 58
10.5%
09:30~18:30 38
 
6.9%
09:00~18:30 35
 
6.3%
09:00~18:00 32
 
5.8%
10:00~19:00 25
 
4.5%
09:00~20:00 19
 
3.4%
10:00~17:01 11
 
2.0%
10:00~18:30 10
 
1.8%
Other values (43) 123
22.2%
2023-12-11T04:49:19.153650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2517
41.4%
: 1106
18.2%
1 698
 
11.5%
9 561
 
9.2%
~ 553
 
9.1%
3 268
 
4.4%
8 173
 
2.8%
7 122
 
2.0%
2 65
 
1.1%
6 11
 
0.2%
Other values (2) 9
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4424
72.7%
Other Punctuation 1106
 
18.2%
Math Symbol 553
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2517
56.9%
1 698
 
15.8%
9 561
 
12.7%
3 268
 
6.1%
8 173
 
3.9%
7 122
 
2.8%
2 65
 
1.5%
6 11
 
0.2%
4 7
 
0.2%
5 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
: 1106
100.0%
Math Symbol
ValueCountFrequency (%)
~ 553
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6083
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2517
41.4%
: 1106
18.2%
1 698
 
11.5%
9 561
 
9.2%
~ 553
 
9.1%
3 268
 
4.4%
8 173
 
2.8%
7 122
 
2.0%
2 65
 
1.1%
6 11
 
0.2%
Other values (2) 9
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6083
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2517
41.4%
: 1106
18.2%
1 698
 
11.5%
9 561
 
9.2%
~ 553
 
9.1%
3 268
 
4.4%
8 173
 
2.8%
7 122
 
2.0%
2 65
 
1.1%
6 11
 
0.2%
Other values (2) 9
 
0.1%

수요일 진료
Text

Distinct57
Distinct (%)10.3%
Missing3
Missing (%)0.5%
Memory size4.5 KiB
2023-12-11T04:49:19.488956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters6072
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)4.5%

Sample

1st row09:30~19:00
2nd row08:30~20:30
3rd row09:00~18:00
4th row10:00~17:00
5th row10:00~17:00
ValueCountFrequency (%)
09:00~19:00 107
19.4%
10:00~17:00 96
17.4%
09:30~19:00 60
10.9%
09:30~18:30 40
 
7.2%
09:00~18:30 33
 
6.0%
10:00~19:00 30
 
5.4%
09:00~18:00 29
 
5.3%
09:00~20:00 16
 
2.9%
09:30~18:00 11
 
2.0%
10:00~18:30 11
 
2.0%
Other values (47) 119
21.6%
2023-12-11T04:49:20.121120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2499
41.2%
: 1104
18.2%
1 714
 
11.8%
9 563
 
9.3%
~ 552
 
9.1%
3 272
 
4.5%
8 174
 
2.9%
7 123
 
2.0%
2 47
 
0.8%
6 11
 
0.2%
Other values (2) 13
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4416
72.7%
Other Punctuation 1104
 
18.2%
Math Symbol 552
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2499
56.6%
1 714
 
16.2%
9 563
 
12.7%
3 272
 
6.2%
8 174
 
3.9%
7 123
 
2.8%
2 47
 
1.1%
6 11
 
0.2%
4 10
 
0.2%
5 3
 
0.1%
Other Punctuation
ValueCountFrequency (%)
: 1104
100.0%
Math Symbol
ValueCountFrequency (%)
~ 552
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6072
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2499
41.2%
: 1104
18.2%
1 714
 
11.8%
9 563
 
9.3%
~ 552
 
9.1%
3 272
 
4.5%
8 174
 
2.9%
7 123
 
2.0%
2 47
 
0.8%
6 11
 
0.2%
Other values (2) 13
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6072
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2499
41.2%
: 1104
18.2%
1 714
 
11.8%
9 563
 
9.3%
~ 552
 
9.1%
3 272
 
4.5%
8 174
 
2.9%
7 123
 
2.0%
2 47
 
0.8%
6 11
 
0.2%
Other values (2) 13
 
0.2%

목요일 진료
Text

Distinct59
Distinct (%)10.7%
Missing3
Missing (%)0.5%
Memory size4.5 KiB
2023-12-11T04:49:20.468730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters6072
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)4.3%

Sample

1st row09:30~19:00
2nd row08:30~20:30
3rd row09:00~18:00
4th row10:00~17:00
5th row10:00~17:00
ValueCountFrequency (%)
09:00~19:00 103
18.7%
10:00~17:00 96
17.4%
09:30~19:00 55
10.0%
09:30~18:30 37
 
6.7%
09:00~18:30 35
 
6.3%
09:00~18:00 31
 
5.6%
10:00~19:00 24
 
4.3%
09:00~20:00 19
 
3.4%
10:00~18:30 11
 
2.0%
10:00~17:01 11
 
2.0%
Other values (49) 130
23.6%
2023-12-11T04:49:21.035010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2508
41.3%
: 1103
18.2%
1 704
 
11.6%
~ 552
 
9.1%
9 549
 
9.0%
3 268
 
4.4%
8 174
 
2.9%
7 120
 
2.0%
2 66
 
1.1%
4 14
 
0.2%
Other values (3) 14
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4416
72.7%
Other Punctuation 1104
 
18.2%
Math Symbol 552
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2508
56.8%
1 704
 
15.9%
9 549
 
12.4%
3 268
 
6.1%
8 174
 
3.9%
7 120
 
2.7%
2 66
 
1.5%
4 14
 
0.3%
6 11
 
0.2%
5 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
: 1103
99.9%
; 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 552
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6072
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2508
41.3%
: 1103
18.2%
1 704
 
11.6%
~ 552
 
9.1%
9 549
 
9.0%
3 268
 
4.4%
8 174
 
2.9%
7 120
 
2.0%
2 66
 
1.1%
4 14
 
0.2%
Other values (3) 14
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6072
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2508
41.3%
: 1103
18.2%
1 704
 
11.6%
~ 552
 
9.1%
9 549
 
9.0%
3 268
 
4.4%
8 174
 
2.9%
7 120
 
2.0%
2 66
 
1.1%
4 14
 
0.2%
Other values (3) 14
 
0.2%

금요일 진료
Categorical

HIGH CARDINALITY  HIGH CORRELATION 

Distinct51
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
09:00~19:00
109 
10:00~17:00
96 
09:30~19:00
64 
09:30~18:30
40 
09:00~18:30
35 
Other values (46)
211 

Length

Max length11
Median length11
Mean length10.974775
Min length4

Unique

Unique21 ?
Unique (%)3.8%

Sample

1st row09:30~20:00
2nd row08:30~20:30
3rd row09:00~18:00
4th row10:00~17:00
5th row10:00~17:00

Common Values

ValueCountFrequency (%)
09:00~19:00 109
19.6%
10:00~17:00 96
17.3%
09:30~19:00 64
11.5%
09:30~18:30 40
 
7.2%
09:00~18:30 35
 
6.3%
09:00~18:00 33
 
5.9%
10:00~19:00 31
 
5.6%
09:00~20:00 18
 
3.2%
09:30~18:00 12
 
2.2%
10:00~18:30 11
 
2.0%
Other values (41) 106
19.1%

Length

2023-12-11T04:49:21.272801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
09:00~19:00 109
19.6%
10:00~17:00 96
17.3%
09:30~19:00 64
11.5%
09:30~18:30 40
 
7.2%
09:00~18:30 35
 
6.3%
09:00~18:00 33
 
5.9%
10:00~19:00 31
 
5.6%
09:00~20:00 18
 
3.2%
09:30~18:00 12
 
2.2%
10:00~18:30 11
 
2.0%
Other values (41) 106
19.1%

토요일 진료
Text

MISSING 

Distinct56
Distinct (%)13.2%
Missing132
Missing (%)23.8%
Memory size4.5 KiB
2023-12-11T04:49:21.595834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters4653
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)5.0%

Sample

1st row09:30~16:00
2nd row08:00~16:00
3rd row09:00~13:00
4th row09:00~15:00
5th row08:00~13:00
ValueCountFrequency (%)
09:00~16:00 56
13.2%
09:00~13:00 37
 
8.7%
09:30~16:00 34
 
8.0%
09:00~17:00 33
 
7.8%
09:30~14:00 29
 
6.9%
09:00~15:00 28
 
6.6%
09:00~14:00 26
 
6.1%
09:30~17:00 22
 
5.2%
09:30~13:00 16
 
3.8%
10:00~16:00 15
 
3.5%
Other values (46) 127
30.0%
2023-12-11T04:49:22.132668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1926
41.4%
: 846
18.2%
1 471
 
10.1%
~ 423
 
9.1%
9 352
 
7.6%
3 265
 
5.7%
6 119
 
2.6%
4 74
 
1.6%
7 69
 
1.5%
5 56
 
1.2%
Other values (2) 52
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3384
72.7%
Other Punctuation 846
 
18.2%
Math Symbol 423
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1926
56.9%
1 471
 
13.9%
9 352
 
10.4%
3 265
 
7.8%
6 119
 
3.5%
4 74
 
2.2%
7 69
 
2.0%
5 56
 
1.7%
8 28
 
0.8%
2 24
 
0.7%
Other Punctuation
ValueCountFrequency (%)
: 846
100.0%
Math Symbol
ValueCountFrequency (%)
~ 423
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4653
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1926
41.4%
: 846
18.2%
1 471
 
10.1%
~ 423
 
9.1%
9 352
 
7.6%
3 265
 
5.7%
6 119
 
2.6%
4 74
 
1.6%
7 69
 
1.5%
5 56
 
1.2%
Other values (2) 52
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4653
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1926
41.4%
: 846
18.2%
1 471
 
10.1%
~ 423
 
9.1%
9 352
 
7.6%
3 265
 
5.7%
6 119
 
2.6%
4 74
 
1.6%
7 69
 
1.5%
5 56
 
1.2%
Other values (2) 52
 
1.1%

일요일 진료
Text

MISSING 

Distinct15
Distinct (%)65.2%
Missing532
Missing (%)95.9%
Memory size4.5 KiB
2023-12-11T04:49:22.414312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.913043
Min length9

Characters and Unicode

Total characters251
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)47.8%

Sample

1st row08:30~12:30
2nd row09:00~13:00
3rd row09:00~13:00
4th row09:00~19:00
5th row09:00~13:00
ValueCountFrequency (%)
09:00~13:00 6
26.1%
09:00~14:00 2
 
8.7%
00:05~24:00 2
 
8.7%
09:00~15:00 2
 
8.7%
08:30~12:30 1
 
4.3%
09:00~19:00 1
 
4.3%
09:30~13:00 1
 
4.3%
09:00~21:30 1
 
4.3%
09:00~12:00 1
 
4.3%
10:30~17:00 1
 
4.3%
Other values (5) 5
21.7%
2023-12-11T04:49:22.920823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 110
43.8%
: 44
 
17.5%
~ 23
 
9.2%
1 22
 
8.8%
9 17
 
6.8%
3 15
 
6.0%
2 6
 
2.4%
4 5
 
2.0%
5 4
 
1.6%
8 3
 
1.2%
Other values (2) 2
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 184
73.3%
Other Punctuation 44
 
17.5%
Math Symbol 23
 
9.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 110
59.8%
1 22
 
12.0%
9 17
 
9.2%
3 15
 
8.2%
2 6
 
3.3%
4 5
 
2.7%
5 4
 
2.2%
8 3
 
1.6%
7 1
 
0.5%
6 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
: 44
100.0%
Math Symbol
ValueCountFrequency (%)
~ 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 251
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 110
43.8%
: 44
 
17.5%
~ 23
 
9.2%
1 22
 
8.8%
9 17
 
6.8%
3 15
 
6.0%
2 6
 
2.4%
4 5
 
2.0%
5 4
 
1.6%
8 3
 
1.2%
Other values (2) 2
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 251
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 110
43.8%
: 44
 
17.5%
~ 23
 
9.2%
1 22
 
8.8%
9 17
 
6.8%
3 15
 
6.0%
2 6
 
2.4%
4 5
 
2.0%
5 4
 
1.6%
8 3
 
1.2%
Other values (2) 2
 
0.8%

공휴일 진료
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct25
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
<NA>
429 
09:00~13:00
66 
09:30~13:00
 
10
09:00~15:00
 
6
09:00~17:00
 
5
Other values (20)
 
39

Length

Max length11
Median length4
Mean length5.5891892
Min length4

Unique

Unique10 ?
Unique (%)1.8%

Sample

1st row09:30~13:00
2nd row08:30~12:30
3rd row09:00~13:00
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 429
77.3%
09:00~13:00 66
 
11.9%
09:30~13:00 10
 
1.8%
09:00~15:00 6
 
1.1%
09:00~17:00 5
 
0.9%
09:00~14:00 4
 
0.7%
09:00~12:30 4
 
0.7%
09:00~12:00 4
 
0.7%
09:00~19:00 3
 
0.5%
08:30~13:00 3
 
0.5%
Other values (15) 21
 
3.8%

Length

2023-12-11T04:49:23.131621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 429
77.3%
09:00~13:00 66
 
11.9%
09:30~13:00 10
 
1.8%
09:00~15:00 6
 
1.1%
09:00~17:00 5
 
0.9%
09:00~14:00 4
 
0.7%
09:00~12:30 4
 
0.7%
09:00~12:00 4
 
0.7%
09:00~19:00 3
 
0.5%
08:30~13:00 3
 
0.5%
Other values (15) 21
 
3.8%

전화번호
Text

Distinct549
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2023-12-11T04:49:23.530973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters6660
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

Unique543 ?
Unique (%)97.8%

Sample

1st row053-354-2800
2nd row053-325-0365
3rd row053-359-3771
4th row053-941-0144
5th row053-311-1075
ValueCountFrequency (%)
053-326-2824 2
 
0.4%
053-326-7510 2
 
0.4%
053-213-2325 2
 
0.4%
053-325-7582 2
 
0.4%
053-322-8275 2
 
0.4%
053-669-1000 2
 
0.4%
053-321-6383 1
 
0.2%
053-357-9889 1
 
0.2%
053-322-7705 1
 
0.2%
053-353-0007 1
 
0.2%
Other values (539) 539
97.1%
2023-12-11T04:49:24.099488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 1156
17.4%
5 1153
17.3%
- 1110
16.7%
0 929
13.9%
2 553
8.3%
7 403
 
6.1%
1 374
 
5.6%
8 296
 
4.4%
9 277
 
4.2%
4 215
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5550
83.3%
Dash Punctuation 1110
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 1156
20.8%
5 1153
20.8%
0 929
16.7%
2 553
10.0%
7 403
 
7.3%
1 374
 
6.7%
8 296
 
5.3%
9 277
 
5.0%
4 215
 
3.9%
6 194
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 1110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6660
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 1156
17.4%
5 1153
17.3%
- 1110
16.7%
0 929
13.9%
2 553
8.3%
7 403
 
6.1%
1 374
 
5.6%
8 296
 
4.4%
9 277
 
4.2%
4 215
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6660
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 1156
17.4%
5 1153
17.3%
- 1110
16.7%
0 929
13.9%
2 553
8.3%
7 403
 
6.1%
1 374
 
5.6%
8 296
 
4.4%
9 277
 
4.2%
4 215
 
3.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
Minimum2019-08-19 00:00:00
Maximum2019-08-19 00:00:00
2023-12-11T04:49:24.262837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:49:24.386394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T04:49:09.001936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:49:08.641005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:49:09.194952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:49:08.812045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T04:49:24.511403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도월요일 진료화요일 진료수요일 진료목요일 진료금요일 진료토요일 진료일요일 진료공휴일 진료
위도1.0000.8000.4980.4840.4610.4920.4940.3540.5110.000
경도0.8001.0000.0660.0000.0000.1340.0000.4420.5020.293
월요일 진료0.4980.0661.0000.9990.9990.9991.0000.9810.6780.938
화요일 진료0.4840.0000.9991.0000.9980.9990.9990.9810.6780.939
수요일 진료0.4610.0000.9990.9981.0000.9970.9980.9780.6780.938
목요일 진료0.4920.1340.9990.9990.9971.0000.9980.9900.6780.940
금요일 진료0.4940.0001.0000.9990.9980.9981.0000.9810.6780.938
토요일 진료0.3540.4420.9810.9810.9780.9900.9811.0000.8130.980
일요일 진료0.5110.5020.6780.6780.6780.6780.6780.8131.0000.992
공휴일 진료0.0000.2930.9380.9390.9380.9400.9380.9800.9921.000
2023-12-11T04:49:24.683840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공휴일 진료금요일 진료
공휴일 진료1.0000.558
금요일 진료0.5581.000
2023-12-11T04:49:24.781749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도금요일 진료공휴일 진료
위도1.000-0.5740.1720.000
경도-0.5741.0000.0000.100
금요일 진료0.1720.0001.0000.558
공휴일 진료0.0000.1000.5581.000

Missing values

2023-12-11T04:49:09.453975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T04:49:09.856553image/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.
2023-12-11T04:49:10.147864image/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

병원명영업상태소재지도로명주소소재지지번주소위도경도인허가일자영업장 면적월요일 진료화요일 진료수요일 진료목요일 진료금요일 진료토요일 진료일요일 진료공휴일 진료전화번호데이터기준일자
02080연합피부과의원영업중대구광역시 북구 침산로 138 (침산동)대구광역시 북구 침산2동 285번지 5호 명성프라임 401호35.888786128.5918932008-03-1427509:30~19:0009:30~20:0009:30~19:0009:30~19:0009:30~20:0009:30~16:00<NA>09:30~13:00053-354-28002019-08-19
1365늘속편한내과의원영업중대구광역시 북구 학정로 415, 2층 (동천동, 메가타운)대구광역시 북구 동천동 912번지 3호 2층35.941837128.5629932017-02-27339.908:30~20:3008:30~20:3008:30~20:3008:30~20:3008:30~20:3008:00~16:0008:30~12:3008:30~12:30053-325-03652019-08-19
2M병원영업중대구광역시 북구 팔달로 147 (노원동3가)<NA>35.889424128.5662262001-10-053281.8209:00~18:0009:00~18:0009:00~18:0009:00~18:0009:00~18:0009:00~13:00<NA>09:00~13:00053-359-37712019-08-19
3가람한의원영업중대구광역시 북구 대학로 5 (산격동)대구광역시 북구 산격4동 1382번지 33호35.888547128.6022931991-11-2636.7810:00~17:0010:00~17:0010:00~17:0010:00~17:0010:00~17:00<NA><NA><NA>053-941-01442019-08-19
4가원한의원영업중대구광역시 북구 칠곡중앙대로 457 (관음동)대구광역시 북구 관음동 1386번지 15호 3층35.936584128.5487472007-08-20195.2110:00~17:0010:00~17:0010:00~17:0010:00~17:0010:00~17:00<NA><NA><NA>053-311-10752019-08-19
5가톨릭건강의원영업중대구광역시 북구 구암로 149, 2층 (동천동)대구광역시 북구 동천동 877번지 1호 2층35.931999128.5570882016-03-1628109:00~19:0009:00~19:0009:00~19:0009:00~19:0009:00~19:0009:00~15:00<NA><NA>053-313-04002019-08-19
6가톨릭비뇨기과의원영업중대구광역시 북구 칠곡중앙대로 442, 2층,3층 (읍내동)대구광역시 북구 읍내동 1341번지 4호35.935146128.5491562002-03-2960008:00~17:0008:00~17:0008:00~17:0008:00~17:0008:00~17:0008:00~13:00<NA>08:00~13:00053-325-00212019-08-19
7가톨릭이비인후과의원영업중대구광역시 북구 칠곡중앙대로 411, 2층 (태전동, 우영펠리스 )<NA>35.932521128.547982011-02-24196.6409:30~19:0009:30~19:0009:30~19:0009:30~19:0009:30~19:0009:30~16:00<NA><NA>053-311-75792019-08-19
8가톨릭정충일안과의원영업중대구광역시 북구 학정로 431, 3층 301호 (동천동, 우리빌딩)대구광역시 북구 동천동 896번지 4호 우리빌딩 301호35.94331128.5632622006-12-2718209:00~19:0009:00~19:0009:00~19:0009:00~19:0009:00~19:0009:00~19:00<NA>09:00~16:00053-322-75252019-08-19
9가톨릭피부과의원영업중대구광역시 북구 구암로15길 28 (읍내동)대구광역시 북구 읍내동 1140번지35.935079128.5501471996-10-311016.609:00~16:3009:00~16:3009:00~16:3009:00~16:3009:00~16:3009:00~12:30<NA><NA>053-320-20292019-08-19
병원명영업상태소재지도로명주소소재지지번주소위도경도인허가일자영업장 면적월요일 진료화요일 진료수요일 진료목요일 진료금요일 진료토요일 진료일요일 진료공휴일 진료전화번호데이터기준일자
545호동연합의원영업중대구광역시 북구 관음중앙로28길 7, 2층 (관음동)대구광역시 북구 관음동 1284번지 2호 (2층)35.944442128.5471942002-03-14167.609:30~19:3009:30~18:3009:30~18:3009:30~18:3009:30~18:3009:30~14:00<NA><NA>053-326-00812019-08-19
546호성연합의원영업중대구광역시 북구 매전로 14, 2층 (매천동)<NA>35.908391128.5435732016-07-19166.5209:00~20:0009:00~20:0009:00~20:0009:00~20:0009:00~20:0009:00~16:00<NA>09:00~13:00053-311-90962019-08-19
547홍S치과의원영업중대구광역시 북구 팔달로 149, 6층 (노원동3가, 덕인빌딩)대구광역시 북구 노원동3가 763번지 3호35.889117128.5667072013-11-25253.3909:30~18:3009:30~18:3009:30~18:3009:30~18:3009:30~18:3009:30~17:00<NA><NA>053-351-20802019-08-19
548홍안과의원영업중대구광역시 북구 침산로 138, 명성프라임 3층 301호 (침산동)<NA>35.888807128.5918712018-06-20293.809:00~18:3009:00~18:3009:00~18:3009:00~18:3009:00~18:3009:00~13:00<NA><NA>053-356-10402019-08-19
549홍인치과의원영업중대구광역시 북구 칠성남로 101 (칠성동2가)대구광역시 북구 칠성동2가 715번지 204호35.878327128.5917142012-04-23107.3410:00~19:0010:00~21:0010:00~19:0010:00~19:0010:00~19:0010:00~14:00<NA><NA>053-286-28752019-08-19
550화담한의원영업중대구광역시 북구 칠곡중앙대로46길 29-1 (태전동)대구광역시 북구 태전동 547번지 1호35.918893128.5500912008-11-2752.9210:00~17:0010:00~17:0010:00~17:0010:00~17:0010:00~17:00<NA><NA><NA>053-314-10752019-08-19
551황부부치과의원영업중대구광역시 북구 검단로 117, 201호 (검단동, 유성상가)대구광역시 북구 검단동 887번지 67호35.907482128.6201571999-04-01159.409:30~19:0009:30~19:0009:30~19:0009:30~19:0009:30~19:0009:30~14:00<NA><NA>053-383-28752019-08-19
552효제통마취통증의학과의원영업중대구광역시 북구 팔달로 157 (노원동3가)대구광역시 북구 노원동3가 765번지 8호 (2층)35.889181128.5673432007-03-21109.8209:30~20:0009:30~19:0009:30~19:0009:30~20:0009:30~19:0009:30~17:00<NA>09:30~13:00053-358-02902019-08-19
553희영한의원영업중대구광역시 북구 호암로 30 (칠성동2가)대구광역시 북구 칠성동2가 378번지 26호35.882334128.5939312002-04-09156.110:00~17:0010:00~17:0010:00~17:0010:00~17:0010:00~17:00<NA><NA><NA>053-351-10752019-08-19
554흰돌치과의원영업중대구광역시 북구 대천로 94, 4층 (동천동)대구광역시 북구 동천동 934번지 6호 (4층일부)35.936652128.5593812002-12-14198.7209:30~19:0009:30~19:0009:30~19:0009:30~19:0009:30~19:0009:30~16:00<NA><NA>053-326-65432019-08-19