Overview

Dataset statistics

Number of variables8
Number of observations455
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.5 KiB
Average record size in memory66.3 B

Variable types

Categorical1
Text4
Numeric2
DateTime1

Dataset

Description부천시 관내의 유흥단란주점 현황으로 업종명, 업소명, 소재지(지번,도로명), 소재지전화번호, 영업자시작일의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15047813/fileData.do

Alerts

업종명 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation

Reproduction

Analysis started2023-12-13 00:15:19.545269
Analysis finished2023-12-13 00:15:20.360994
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
유흥주점영업
455 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유흥주점영업 455
100.0%

Length

2023-12-13T09:15:20.407809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:15:20.475785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유흥주점영업 455
100.0%

업소명
Text

Distinct408
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-13T09:15:20.675301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length5.4989011
Min length1

Characters and Unicode

Total characters2502
Distinct characters339
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique373 ?
Unique (%)82.0%

Sample

1st row별천지노래바
2nd row코리아노래광장
3rd row코코성인노래마당
4th row가요메들리부천회관
5th row짝꿍
ValueCountFrequency (%)
팡팡노래바 5
 
1.1%
썸노래바 4
 
0.8%
킹노래클럽 4
 
0.8%
노래클럽 4
 
0.8%
명월관 3
 
0.6%
헤라노래클럽 3
 
0.6%
궁노래빠 3
 
0.6%
궁전 3
 
0.6%
빙고노래바 3
 
0.6%
준코뮤직타운 3
 
0.6%
Other values (406) 438
92.6%
2023-12-13T09:15:21.007897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
래 305
 
12.2%
노 301
 
12.0%
럽 137
 
5.5%
클 130
 
5.2%
바 124
 
5.0%
스 54
 
2.2%
이 49
 
2.0%
타 40
 
1.6%
운 28
 
1.1%
) 26
 
1.0%
Other values (329) 1308
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2283
91.2%
Decimal Number 89
 
3.6%
Uppercase Letter 48
 
1.9%
Close Punctuation 26
 
1.0%
Open Punctuation 26
 
1.0%
Space Separator 19
 
0.8%
Lowercase Letter 11
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
래 305
 
13.4%
노 301
 
13.2%
럽 137
 
6.0%
클 130
 
5.7%
바 124
 
5.4%
스 54
 
2.4%
이 49
 
2.1%
타 40
 
1.8%
운 28
 
1.2%
코 25
 
1.1%
Other values (293) 1090
47.7%
Uppercase Letter
ValueCountFrequency (%)
S 8
16.7%
N 4
8.3%
B 4
8.3%
J 4
8.3%
K 4
8.3%
O 4
8.3%
T 3
 
6.2%
I 3
 
6.2%
E 3
 
6.2%
D 2
 
4.2%
Other values (6) 9
18.8%
Decimal Number
ValueCountFrequency (%)
0 20
22.5%
1 16
18.0%
8 14
15.7%
7 13
14.6%
3 12
13.5%
2 10
11.2%
9 2
 
2.2%
6 1
 
1.1%
4 1
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
o 3
27.3%
l 2
18.2%
y 1
 
9.1%
f 1
 
9.1%
r 1
 
9.1%
c 1
 
9.1%
u 1
 
9.1%
b 1
 
9.1%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Space Separator
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2281
91.2%
Common 160
 
6.4%
Latin 59
 
2.4%
Han 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
래 305
 
13.4%
노 301
 
13.2%
럽 137
 
6.0%
클 130
 
5.7%
바 124
 
5.4%
스 54
 
2.4%
이 49
 
2.1%
타 40
 
1.8%
운 28
 
1.2%
코 25
 
1.1%
Other values (291) 1088
47.7%
Latin
ValueCountFrequency (%)
S 8
13.6%
N 4
 
6.8%
B 4
 
6.8%
J 4
 
6.8%
K 4
 
6.8%
O 4
 
6.8%
T 3
 
5.1%
o 3
 
5.1%
I 3
 
5.1%
E 3
 
5.1%
Other values (14) 19
32.2%
Common
ValueCountFrequency (%)
) 26
16.2%
( 26
16.2%
0 20
12.5%
19
11.9%
1 16
10.0%
8 14
8.8%
7 13
8.1%
3 12
7.5%
2 10
 
6.2%
9 2
 
1.2%
Other values (2) 2
 
1.2%
Han
ValueCountFrequency (%)
家 1
50.0%
大 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2281
91.2%
ASCII 219
 
8.8%
CJK 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
래 305
 
13.4%
노 301
 
13.2%
럽 137
 
6.0%
클 130
 
5.7%
바 124
 
5.4%
스 54
 
2.4%
이 49
 
2.1%
타 40
 
1.8%
운 28
 
1.2%
코 25
 
1.1%
Other values (291) 1088
47.7%
ASCII
ValueCountFrequency (%)
) 26
11.9%
( 26
11.9%
0 20
 
9.1%
19
 
8.7%
1 16
 
7.3%
8 14
 
6.4%
7 13
 
5.9%
3 12
 
5.5%
2 10
 
4.6%
S 8
 
3.7%
Other values (26) 55
25.1%
CJK
ValueCountFrequency (%)
家 1
50.0%
大 1
50.0%

도로명주소
Text

Distinct447
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-13T09:15:21.250980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length42
Mean length31.925275
Min length20

Characters and Unicode

Total characters14526
Distinct characters172
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

Unique439 ?
Unique (%)96.5%

Sample

1st row경기도 부천시 신흥로22번길 54, 지하1층 (심곡동)
2nd row경기도 부천시 부일로 494 (심곡동,(지상2층))
3rd row경기도 부천시 부천로 54 (심곡동,지하일부)
4th row경기도 부천시 부천로 36-1 (심곡동)
5th row경기도 부천시 부일로 424, 지하1층 (심곡동)
ValueCountFrequency (%)
경기도 455
 
16.2%
부천시 455
 
16.2%
지하1층 108
 
3.9%
중동 108
 
3.9%
심곡동 94
 
3.4%
상동 65
 
2.3%
부일로 37
 
1.3%
일부 36
 
1.3%
중동로254번길 32
 
1.1%
조마루로291번길 25
 
0.9%
Other values (532) 1390
49.6%
2023-12-13T09:15:21.622806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2351
 
16.2%
부 694
 
4.8%
1 660
 
4.5%
천 544
 
3.7%
동 536
 
3.7%
, 507
 
3.5%
2 498
 
3.4%
경 483
 
3.3%
) 482
 
3.3%
( 482
 
3.3%
Other values (162) 7289
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7880
54.2%
Decimal Number 2719
 
18.7%
Space Separator 2351
 
16.2%
Other Punctuation 507
 
3.5%
Close Punctuation 482
 
3.3%
Open Punctuation 482
 
3.3%
Uppercase Letter 51
 
0.4%
Dash Punctuation 50
 
0.3%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 694
 
8.8%
천 544
 
6.9%
동 536
 
6.8%
경 483
 
6.1%
시 461
 
5.9%
로 461
 
5.9%
도 458
 
5.8%
기 455
 
5.8%
길 369
 
4.7%
번 336
 
4.3%
Other values (144) 3083
39.1%
Decimal Number
ValueCountFrequency (%)
1 660
24.3%
2 498
18.3%
0 294
10.8%
3 281
10.3%
4 230
 
8.5%
5 191
 
7.0%
7 175
 
6.4%
9 154
 
5.7%
6 140
 
5.1%
8 96
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
B 49
96.1%
A 2
 
3.9%
Space Separator
ValueCountFrequency (%)
2351
100.0%
Other Punctuation
ValueCountFrequency (%)
, 507
100.0%
Close Punctuation
ValueCountFrequency (%)
) 482
100.0%
Open Punctuation
ValueCountFrequency (%)
( 482
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7880
54.2%
Common 6595
45.4%
Latin 51
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 694
 
8.8%
천 544
 
6.9%
동 536
 
6.8%
경 483
 
6.1%
시 461
 
5.9%
로 461
 
5.9%
도 458
 
5.8%
기 455
 
5.8%
길 369
 
4.7%
번 336
 
4.3%
Other values (144) 3083
39.1%
Common
ValueCountFrequency (%)
2351
35.6%
1 660
 
10.0%
, 507
 
7.7%
2 498
 
7.6%
) 482
 
7.3%
( 482
 
7.3%
0 294
 
4.5%
3 281
 
4.3%
4 230
 
3.5%
5 191
 
2.9%
Other values (6) 619
 
9.4%
Latin
ValueCountFrequency (%)
B 49
96.1%
A 2
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7880
54.2%
ASCII 6646
45.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2351
35.4%
1 660
 
9.9%
, 507
 
7.6%
2 498
 
7.5%
) 482
 
7.3%
( 482
 
7.3%
0 294
 
4.4%
3 281
 
4.2%
4 230
 
3.5%
5 191
 
2.9%
Other values (8) 670
 
10.1%
Hangul
ValueCountFrequency (%)
부 694
 
8.8%
천 544
 
6.9%
동 536
 
6.8%
경 483
 
6.1%
시 461
 
5.9%
로 461
 
5.9%
도 458
 
5.8%
기 455
 
5.8%
길 369
 
4.7%
번 336
 
4.3%
Other values (144) 3083
39.1%

지번주소
Text

Distinct448
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-13T09:15:21.816138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36
Mean length25.802198
Min length15

Characters and Unicode

Total characters11740
Distinct characters162
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

Unique441 ?
Unique (%)96.9%

Sample

1st row경기도 부천시 심곡동 388-12 지하1층
2nd row경기도 부천시 심곡동 170-1 (지상2층)
3rd row경기도 부천시 심곡동 158-10 지하일부
4th row경기도 부천시 심곡동 164-12
5th row경기도 부천시 심곡동 463-4 ,지하1층
ValueCountFrequency (%)
경기도 455
18.3%
부천시 455
18.3%
중동 166
 
6.7%
지하1층 140
 
5.6%
심곡동 122
 
4.9%
상동 101
 
4.1%
일부 43
 
1.7%
심곡본동 20
 
0.8%
역곡동 19
 
0.8%
지하 19
 
0.8%
Other values (586) 947
38.1%
2023-12-13T09:15:22.109451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2437
20.8%
1 985
 
8.4%
부 542
 
4.6%
동 468
 
4.0%
시 461
 
3.9%
천 460
 
3.9%
도 458
 
3.9%
경 455
 
3.9%
기 455
 
3.9%
- 416
 
3.5%
Other values (152) 4603
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5803
49.4%
Decimal Number 2864
24.4%
Space Separator 2437
20.8%
Dash Punctuation 416
 
3.5%
Other Punctuation 111
 
0.9%
Uppercase Letter 50
 
0.4%
Close Punctuation 27
 
0.2%
Open Punctuation 27
 
0.2%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 542
 
9.3%
동 468
 
8.1%
시 461
 
7.9%
천 460
 
7.9%
도 458
 
7.9%
경 455
 
7.8%
기 455
 
7.8%
지 261
 
4.5%
층 220
 
3.8%
하 220
 
3.8%
Other values (133) 1803
31.1%
Decimal Number
ValueCountFrequency (%)
1 985
34.4%
3 321
 
11.2%
0 319
 
11.1%
2 290
 
10.1%
4 229
 
8.0%
5 227
 
7.9%
7 139
 
4.9%
8 133
 
4.6%
6 126
 
4.4%
9 95
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 110
99.1%
. 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
B 48
96.0%
A 2
 
4.0%
Space Separator
ValueCountFrequency (%)
2437
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 416
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5887
50.1%
Hangul 5803
49.4%
Latin 50
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 542
 
9.3%
동 468
 
8.1%
시 461
 
7.9%
천 460
 
7.9%
도 458
 
7.9%
경 455
 
7.8%
기 455
 
7.8%
지 261
 
4.5%
층 220
 
3.8%
하 220
 
3.8%
Other values (133) 1803
31.1%
Common
ValueCountFrequency (%)
2437
41.4%
1 985
16.7%
- 416
 
7.1%
3 321
 
5.5%
0 319
 
5.4%
2 290
 
4.9%
4 229
 
3.9%
5 227
 
3.9%
7 139
 
2.4%
8 133
 
2.3%
Other values (7) 391
 
6.6%
Latin
ValueCountFrequency (%)
B 48
96.0%
A 2
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5937
50.6%
Hangul 5803
49.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2437
41.0%
1 985
16.6%
- 416
 
7.0%
3 321
 
5.4%
0 319
 
5.4%
2 290
 
4.9%
4 229
 
3.9%
5 227
 
3.8%
7 139
 
2.3%
8 133
 
2.2%
Other values (9) 441
 
7.4%
Hangul
ValueCountFrequency (%)
부 542
 
9.3%
동 468
 
8.1%
시 461
 
7.9%
천 460
 
7.9%
도 458
 
7.9%
경 455
 
7.8%
기 455
 
7.8%
지 261
 
4.5%
층 220
 
3.8%
하 220
 
3.8%
Other values (133) 1803
31.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct340
Distinct (%)74.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.494953
Minimum37.48022
Maximum37.525258
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-13T09:15:22.217345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.48022
5-th percentile37.483416
Q137.486115
median37.496613
Q337.502462
95-th percentile37.506797
Maximum37.525258
Range0.04503846
Interquartile range (IQR)0.016346845

Descriptive statistics

Standard deviation0.0093288424
Coefficient of variation (CV)0.00024880262
Kurtosis0.041762086
Mean37.494953
Median Absolute Deviation (MAD)0.0081297
Skewness0.56580667
Sum17060.203
Variance8.7027301 × 10-5
MonotonicityNot monotonic
2023-12-13T09:15:22.321321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.50626373 5
 
1.1%
37.49995583 5
 
1.1%
37.50615733 5
 
1.1%
37.50197717 3
 
0.7%
37.49918318 3
 
0.7%
37.50246199 3
 
0.7%
37.49966462 3
 
0.7%
37.50480059 3
 
0.7%
37.48312752 3
 
0.7%
37.49940407 3
 
0.7%
Other values (330) 419
92.1%
ValueCountFrequency (%)
37.48021968 1
0.2%
37.48089658 1
0.2%
37.48096717 1
0.2%
37.48108208 1
0.2%
37.48123917 1
0.2%
37.48183263 1
0.2%
37.48195402 1
0.2%
37.48283292 1
0.2%
37.48292312 1
0.2%
37.48297976 1
0.2%
ValueCountFrequency (%)
37.52525814 1
0.2%
37.52469481 1
0.2%
37.52455055 1
0.2%
37.52429148 1
0.2%
37.52425234 1
0.2%
37.52424002 1
0.2%
37.52423469 1
0.2%
37.52419068 1
0.2%
37.52381652 2
0.4%
37.50720253 1
0.2%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct339
Distinct (%)74.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.7747
Minimum126.74952
Maximum126.81388
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-13T09:15:22.422106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.74952
5-th percentile126.75129
Q1126.76246
median126.77601
Q3126.78259
95-th percentile126.81136
Maximum126.81388
Range0.0643576
Interquartile range (IQR)0.0201353

Descriptive statistics

Standard deviation0.015668288
Coefficient of variation (CV)0.0001235916
Kurtosis0.29609088
Mean126.7747
Median Absolute Deviation (MAD)0.0075413
Skewness0.50244899
Sum57682.489
Variance0.00024549525
MonotonicityNot monotonic
2023-12-13T09:15:22.749964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7553601 5
 
1.1%
126.7563798 5
 
1.1%
126.7760138 5
 
1.1%
126.7509852 3
 
0.7%
126.752354 3
 
0.7%
126.7700579 3
 
0.7%
126.7757358 3
 
0.7%
126.7736963 3
 
0.7%
126.7507586 3
 
0.7%
126.7780519 3
 
0.7%
Other values (329) 419
92.1%
ValueCountFrequency (%)
126.7495241 1
 
0.2%
126.7495609 1
 
0.2%
126.7499984 1
 
0.2%
126.7501018 1
 
0.2%
126.7503341 2
0.4%
126.7503384 1
 
0.2%
126.7506219 1
 
0.2%
126.750685 1
 
0.2%
126.7507586 3
0.7%
126.7508483 2
0.4%
ValueCountFrequency (%)
126.8138817 1
0.2%
126.8132905 1
0.2%
126.8130469 1
0.2%
126.8129813 1
0.2%
126.8128052 2
0.4%
126.8127733 1
0.2%
126.8127332 2
0.4%
126.8127118 1
0.2%
126.8124868 1
0.2%
126.8124758 2
0.4%

소재지전화
Text

Distinct361
Distinct (%)79.3%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-13T09:15:22.974627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.008791
Min length12

Characters and Unicode

Total characters5464
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

Unique351 ?
Unique (%)77.1%

Sample

1st row032-654-1711
2nd row032-611-7919
3rd row032-613-7171
4th row032-664-5045
5th row032-657-1157
ValueCountFrequency (%)
032-000-0000 86
 
18.9%
032-614-1224 2
 
0.4%
032-613-2754 2
 
0.4%
032-328-8609 2
 
0.4%
032-321-4223 2
 
0.4%
032-321-7963 2
 
0.4%
032-326-6464 2
 
0.4%
032-328-0023 2
 
0.4%
032-322-5343 2
 
0.4%
032-665-4242 2
 
0.4%
Other values (351) 351
77.1%
2023-12-13T09:15:23.281672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1233
22.6%
- 910
16.7%
3 870
15.9%
2 841
15.4%
6 348
 
6.4%
1 261
 
4.8%
5 245
 
4.5%
4 236
 
4.3%
8 204
 
3.7%
7 182
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4554
83.3%
Dash Punctuation 910
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1233
27.1%
3 870
19.1%
2 841
18.5%
6 348
 
7.6%
1 261
 
5.7%
5 245
 
5.4%
4 236
 
5.2%
8 204
 
4.5%
7 182
 
4.0%
9 134
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 910
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5464
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1233
22.6%
- 910
16.7%
3 870
15.9%
2 841
15.4%
6 348
 
6.4%
1 261
 
4.8%
5 245
 
4.5%
4 236
 
4.3%
8 204
 
3.7%
7 182
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5464
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1233
22.6%
- 910
16.7%
3 870
15.9%
2 841
15.4%
6 348
 
6.4%
1 261
 
4.8%
5 245
 
4.5%
4 236
 
4.3%
8 204
 
3.7%
7 182
 
3.3%

영업자시작일
Date

Distinct393
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum2003-04-29 00:00:00
Maximum2023-07-10 00:00:00
2023-12-13T09:15:23.391941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:15:23.489703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-13T09:15:20.078220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:15:19.950597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:15:20.144836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:15:20.013442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:15:23.553376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.865
경도0.8651.000
2023-12-13T09:15:23.619503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.697
경도-0.6971.000

Missing values

2023-12-13T09:15:20.236532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:15:20.324587image/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

업종명업소명도로명주소지번주소위도경도소재지전화영업자시작일
0유흥주점영업별천지노래바경기도 부천시 신흥로22번길 54, 지하1층 (심곡동)경기도 부천시 심곡동 388-12 지하1층37.485124126.779399032-654-17112020-05-27
1유흥주점영업코리아노래광장경기도 부천시 부일로 494 (심곡동,(지상2층))경기도 부천시 심곡동 170-1 (지상2층)37.485388126.784935032-611-79192017-09-28
2유흥주점영업코코성인노래마당경기도 부천시 부천로 54 (심곡동,지하일부)경기도 부천시 심곡동 158-10 지하일부37.489029126.784119032-613-71712017-02-08
3유흥주점영업가요메들리부천회관경기도 부천시 부천로 36-1 (심곡동)경기도 부천시 심곡동 164-1237.487512126.783793032-664-50452018-03-07
4유흥주점영업짝꿍경기도 부천시 부일로 424, 지하1층 (심곡동)경기도 부천시 심곡동 463-4 ,지하1층37.486543126.777273032-657-11572016-02-25
5유흥주점영업숲속경기도 부천시 부일로483번길 31 (심곡동)경기도 부천시 심곡동 164-937.487136126.784014032-662-29972014-11-24
6유흥주점영업환상노래빠경기도 부천시 심곡로9번길 41, 지하1층 (심곡본동)경기도 부천시 심곡본동 666 ,지하1층37.482833126.778317032-665-78782019-10-28
7유흥주점영업공주노래광장경기도 부천시 부일로483번길 21 (심곡동)경기도 부천시 심곡동 168-1037.486675126.783885032-665-12272015-11-20
8유흥주점영업파티노래바경기도 부천시 부일로 444 (심곡동)경기도 부천시 심곡동 396-237.486195126.779314032-656-60742019-12-06
9유흥주점영업세븐노래바경기도 부천시 경인로 212-1, 지하1층 (심곡본동)경기도 부천시 심곡본동 667-9 ,10~14, 지하1층37.48311126.779013032-611-25612018-02-28
업종명업소명도로명주소지번주소위도경도소재지전화영업자시작일
445유흥주점영업봉봉노래바경기도 부천시 중동로254번길 23, 알파프라자 지층 B02호 (중동)경기도 부천시 중동 1150-10 알파프라자 지층 B02호37.502462126.770058032-000-00002021-12-01
446유흥주점영업환상노래바경기도 부천시 부천로10번길 16, 지하1층 (심곡동)경기도 부천시 심곡동 171-8 지하1층37.484925126.783744032-000-00002022-08-02
447유흥주점영업구찌노래클럽경기도 부천시 조마루로291번길 30, 중동유림프라자빌딩 2층 202호 (중동)경기도 부천시 중동 1130-1 중동유림프라자빌딩 202호37.498955126.775928032-000-00002023-06-30
448유흥주점영업황제노래방주점경기도 부천시 중동로262번길 72, 중동프라자 지하1층 02호 (중동)경기도 부천시 중동 1142-3 중동프라자 지하1층 02호37.502375126.772955032-000-00002021-03-02
449유흥주점영업엄지노래클럽경기도 부천시 중동로254번길 71, 정중프라자 B01호 (중동)경기도 부천시 중동 1142-17 정중프라자 B01호37.502095126.772903032-000-00002020-05-22
450유흥주점영업로즈클럽경기도 부천시 부일로469번길 17, 지하1층 일부 (심곡동)경기도 부천시 심곡동 179-1 지하1층 일부37.48674126.782369032-662-02552021-03-12
451유흥주점영업테스노래바경기도 부천시 부천로3번길 43, 지산프라자, 지하1층일부 (심곡동)경기도 부천시 심곡동 386-4 지산프라자, 지하1층일부37.484809126.780309032-666-55572021-11-09
452유흥주점영업런던나이츠라이브경기도 부천시 상일로122번길 40, 3층 일부호 (상동)경기도 부천시 상동 456-237.489514126.755446032-000-00002022-09-27
453유흥주점영업추억경기도 부천시 부흥로307번길 32, 복사골프라자 2층 일부호 (중동)경기도 부천시 중동 1124-3 복사골프라자 2층 일부37.496035126.776722032-000-00002023-02-08
454유흥주점영업뉴코노래타운부천역점경기도 부천시 부천로 11, 해태쇼핑 지하1층 102호 일부 (심곡동)경기도 부천시 심곡동 175-6 해태쇼핑 지하1층 102호 일부37.485559126.782275032-000-00002023-03-03