Overview

Dataset statistics

Number of variables6
Number of observations228
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.3 KiB
Average record size in memory50.6 B

Variable types

Numeric2
Categorical2
Text2

Dataset

Description광주광역시 서구에 위치한 유흥주점의 업종명, 업소명, 도로명주소, 영업장 면적에 대한 정보를 제공하고 있는 데이터입니다.
Author광주광역시 서구
URLhttps://www.data.go.kr/data/15125008/fileData.do

Alerts

업종명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:22:33.677867
Analysis finished2023-12-12 08:22:34.715170
Duration1.04 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct228
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean114.5
Minimum1
Maximum228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T17:22:34.827763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.35
Q157.75
median114.5
Q3171.25
95-th percentile216.65
Maximum228
Range227
Interquartile range (IQR)113.5

Descriptive statistics

Standard deviation65.96211
Coefficient of variation (CV)0.5760883
Kurtosis-1.2
Mean114.5
Median Absolute Deviation (MAD)57
Skewness0
Sum26106
Variance4351
MonotonicityStrictly increasing
2023-12-12T17:22:34.991643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
145 1
 
0.4%
147 1
 
0.4%
148 1
 
0.4%
149 1
 
0.4%
150 1
 
0.4%
151 1
 
0.4%
152 1
 
0.4%
153 1
 
0.4%
154 1
 
0.4%
Other values (218) 218
95.6%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
228 1
0.4%
227 1
0.4%
226 1
0.4%
225 1
0.4%
224 1
0.4%
223 1
0.4%
222 1
0.4%
221 1
0.4%
220 1
0.4%
219 1
0.4%

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
유흥주점영업
228 

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 228
100.0%

Length

2023-12-12T17:22:35.129567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:22:35.222659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유흥주점영업 228
100.0%

업소명
Text

Distinct225
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T17:22:35.537398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length5.1052632
Min length1

Characters and Unicode

Total characters1164
Distinct characters289
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique222 ?
Unique (%)97.4%

Sample

1st row나주집
2nd row무안
3rd row신세계
4th row고성명월
5th row비엠더블
ValueCountFrequency (%)
노래홀 7
 
2.7%
룸소주방 5
 
1.9%
술마시는 5
 
1.9%
더 3
 
1.2%
상무 2
 
0.8%
헤라 2
 
0.8%
유토피아 2
 
0.8%
오렌지 2
 
0.8%
유흥주점 2
 
0.8%
썸 2
 
0.8%
Other values (223) 228
87.7%
2023-12-12T17:22:36.077332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 49
 
4.2%
소 46
 
4.0%
룸 43
 
3.7%
방 41
 
3.5%
래 37
 
3.2%
노 35
 
3.0%
시 33
 
2.8%
32
 
2.7%
홀 32
 
2.7%
이 31
 
2.7%
Other values (279) 785
67.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1038
89.2%
Uppercase Letter 33
 
2.8%
Space Separator 32
 
2.7%
Decimal Number 18
 
1.5%
Lowercase Letter 14
 
1.2%
Close Punctuation 13
 
1.1%
Open Punctuation 13
 
1.1%
Other Punctuation 2
 
0.2%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 49
 
4.7%
소 46
 
4.4%
룸 43
 
4.1%
방 41
 
3.9%
래 37
 
3.6%
노 35
 
3.4%
시 33
 
3.2%
홀 32
 
3.1%
이 31
 
3.0%
마 29
 
2.8%
Other values (238) 662
63.8%
Uppercase Letter
ValueCountFrequency (%)
O 5
15.2%
M 3
 
9.1%
B 3
 
9.1%
N 2
 
6.1%
W 2
 
6.1%
E 2
 
6.1%
C 2
 
6.1%
P 2
 
6.1%
J 2
 
6.1%
A 1
 
3.0%
Other values (9) 9
27.3%
Lowercase Letter
ValueCountFrequency (%)
a 3
21.4%
i 3
21.4%
o 1
 
7.1%
y 1
 
7.1%
l 1
 
7.1%
e 1
 
7.1%
f 1
 
7.1%
c 1
 
7.1%
g 1
 
7.1%
n 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
0 7
38.9%
7 3
16.7%
2 3
16.7%
8 2
 
11.1%
1 2
 
11.1%
5 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
· 1
50.0%
% 1
50.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1037
89.1%
Common 78
 
6.7%
Latin 48
 
4.1%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 49
 
4.7%
소 46
 
4.4%
룸 43
 
4.1%
방 41
 
4.0%
래 37
 
3.6%
노 35
 
3.4%
시 33
 
3.2%
홀 32
 
3.1%
이 31
 
3.0%
마 29
 
2.8%
Other values (237) 661
63.7%
Latin
ValueCountFrequency (%)
O 5
 
10.4%
a 3
 
6.2%
i 3
 
6.2%
M 3
 
6.2%
B 3
 
6.2%
N 2
 
4.2%
W 2
 
4.2%
E 2
 
4.2%
C 2
 
4.2%
P 2
 
4.2%
Other values (20) 21
43.8%
Common
ValueCountFrequency (%)
32
41.0%
) 13
16.7%
( 13
16.7%
0 7
 
9.0%
7 3
 
3.8%
2 3
 
3.8%
8 2
 
2.6%
1 2
 
2.6%
· 1
 
1.3%
5 1
 
1.3%
Han
ValueCountFrequency (%)
歌 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1037
89.1%
ASCII 124
 
10.7%
None 1
 
0.1%
CJK 1
 
0.1%
Number Forms 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 49
 
4.7%
소 46
 
4.4%
룸 43
 
4.1%
방 41
 
4.0%
래 37
 
3.6%
노 35
 
3.4%
시 33
 
3.2%
홀 32
 
3.1%
이 31
 
3.0%
마 29
 
2.8%
Other values (237) 661
63.7%
ASCII
ValueCountFrequency (%)
32
25.8%
) 13
 
10.5%
( 13
 
10.5%
0 7
 
5.6%
O 5
 
4.0%
a 3
 
2.4%
7 3
 
2.4%
2 3
 
2.4%
i 3
 
2.4%
M 3
 
2.4%
Other values (29) 39
31.5%
None
ValueCountFrequency (%)
· 1
100.0%
CJK
ValueCountFrequency (%)
歌 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명주소
Text

Distinct219
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T17:22:36.365735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length37
Mean length29.934211
Min length20

Characters and Unicode

Total characters6825
Distinct characters96
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

Unique210 ?
Unique (%)92.1%

Sample

1st row광주광역시 서구 구성로 53 (양동, (구,33번지))
2nd row광주광역시 서구 양동시장3길 18 (양동,(1층))
3rd row광주광역시 서구 구성로93번길 4-2 (양동,(일층))
4th row광주광역시 서구 구성로 59 (양동,(1층))
5th row광주광역시 서구 구성로93번길 2 (양동,(지하1층))
ValueCountFrequency (%)
광주광역시 228
18.0%
서구 228
18.0%
치평동 84
 
6.6%
상무연하로 74
 
5.9%
2층 25
 
2.0%
시청로60번길 25
 
2.0%
3층 23
 
1.8%
4층 17
 
1.3%
상무번영로 17
 
1.3%
지하1층 15
 
1.2%
Other values (201) 528
41.8%
2023-12-12T17:22:36.886724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1036
 
15.2%
광 457
 
6.7%
( 349
 
5.1%
) 349
 
5.1%
시 285
 
4.2%
구 241
 
3.5%
, 233
 
3.4%
동 230
 
3.4%
역 228
 
3.3%
주 228
 
3.3%
Other values (86) 3189
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3864
56.6%
Space Separator 1036
 
15.2%
Decimal Number 933
 
13.7%
Open Punctuation 349
 
5.1%
Close Punctuation 349
 
5.1%
Other Punctuation 233
 
3.4%
Dash Punctuation 51
 
0.7%
Uppercase Letter 9
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 457
 
11.8%
시 285
 
7.4%
구 241
 
6.2%
동 230
 
6.0%
역 228
 
5.9%
주 228
 
5.9%
서 228
 
5.9%
로 227
 
5.9%
층 220
 
5.7%
평 181
 
4.7%
Other values (65) 1339
34.7%
Decimal Number
ValueCountFrequency (%)
1 183
19.6%
2 145
15.5%
3 117
12.5%
6 91
9.8%
5 90
9.6%
0 85
9.1%
4 69
 
7.4%
7 65
 
7.0%
8 51
 
5.5%
9 37
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
L 2
22.2%
I 2
22.2%
G 2
22.2%
C 2
22.2%
B 1
11.1%
Space Separator
ValueCountFrequency (%)
1036
100.0%
Open Punctuation
ValueCountFrequency (%)
( 349
100.0%
Close Punctuation
ValueCountFrequency (%)
) 349
100.0%
Other Punctuation
ValueCountFrequency (%)
, 233
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3864
56.6%
Common 2952
43.3%
Latin 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 457
 
11.8%
시 285
 
7.4%
구 241
 
6.2%
동 230
 
6.0%
역 228
 
5.9%
주 228
 
5.9%
서 228
 
5.9%
로 227
 
5.9%
층 220
 
5.7%
평 181
 
4.7%
Other values (65) 1339
34.7%
Common
ValueCountFrequency (%)
1036
35.1%
( 349
 
11.8%
) 349
 
11.8%
, 233
 
7.9%
1 183
 
6.2%
2 145
 
4.9%
3 117
 
4.0%
6 91
 
3.1%
5 90
 
3.0%
0 85
 
2.9%
Other values (6) 274
 
9.3%
Latin
ValueCountFrequency (%)
L 2
22.2%
I 2
22.2%
G 2
22.2%
C 2
22.2%
B 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3864
56.6%
ASCII 2961
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1036
35.0%
( 349
 
11.8%
) 349
 
11.8%
, 233
 
7.9%
1 183
 
6.2%
2 145
 
4.9%
3 117
 
4.0%
6 91
 
3.1%
5 90
 
3.0%
0 85
 
2.9%
Other values (11) 283
 
9.6%
Hangul
ValueCountFrequency (%)
광 457
 
11.8%
시 285
 
7.4%
구 241
 
6.2%
동 230
 
6.0%
역 228
 
5.9%
주 228
 
5.9%
서 228
 
5.9%
로 227
 
5.9%
층 220
 
5.7%
평 181
 
4.7%
Other values (65) 1339
34.7%

영업장면적(제곱미터)
Real number (ℝ)

Distinct221
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean232.64601
Minimum0
Maximum2720.52
Zeros1
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T17:22:37.061395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile39.441
Q185.2025
median190.285
Q3333.1075
95-th percentile531.7865
Maximum2720.52
Range2720.52
Interquartile range (IQR)247.905

Descriptive statistics

Standard deviation232.06615
Coefficient of variation (CV)0.99750754
Kurtosis57.477059
Mean232.64601
Median Absolute Deviation (MAD)109.85
Skewness5.7265436
Sum53043.29
Variance53854.697
MonotonicityNot monotonic
2023-12-12T17:22:37.235412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
98.0 2
 
0.9%
418.16 2
 
0.9%
90.0 2
 
0.9%
99.0 2
 
0.9%
335.11 2
 
0.9%
268.0 2
 
0.9%
198.43 2
 
0.9%
147.03 1
 
0.4%
92.26 1
 
0.4%
82.51 1
 
0.4%
Other values (211) 211
92.5%
ValueCountFrequency (%)
0.0 1
0.4%
10.48 1
0.4%
19.4 1
0.4%
22.5 1
0.4%
24.08 1
0.4%
25.14 1
0.4%
26.91 1
0.4%
28.71 1
0.4%
29.55 1
0.4%
37.1 1
0.4%
ValueCountFrequency (%)
2720.52 1
0.4%
807.72 1
0.4%
720.0 1
0.4%
705.28 1
0.4%
651.69 1
0.4%
604.47 1
0.4%
596.23 1
0.4%
596.18 1
0.4%
572.67 1
0.4%
568.44 1
0.4%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-11-14
228 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-11-14
2nd row2023-11-14
3rd row2023-11-14
4th row2023-11-14
5th row2023-11-14

Common Values

ValueCountFrequency (%)
2023-11-14 228
100.0%

Length

2023-12-12T17:22:37.388437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:22:37.487916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-14 228
100.0%

Interactions

2023-12-12T17:22:34.221316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:22:33.997976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:22:34.339170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:22:34.107416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:22:37.553409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번영업장면적(제곱미터)
연번1.0000.092
영업장면적(제곱미터)0.0921.000
2023-12-12T17:22:37.647886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번영업장면적(제곱미터)
연번1.0000.233
영업장면적(제곱미터)0.2331.000

Missing values

2023-12-12T17:22:34.513171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:22:34.654510image/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

연번업종명업소명도로명주소영업장면적(제곱미터)데이터기준일자
01유흥주점영업나주집광주광역시 서구 구성로 53 (양동, (구,33번지))0.02023-11-14
12유흥주점영업무안광주광역시 서구 양동시장3길 18 (양동,(1층))10.482023-11-14
23유흥주점영업신세계광주광역시 서구 구성로93번길 4-2 (양동,(일층))26.912023-11-14
34유흥주점영업고성명월광주광역시 서구 구성로 59 (양동,(1층))29.552023-11-14
45유흥주점영업비엠더블광주광역시 서구 구성로93번길 2 (양동,(지하1층))201.442023-11-14
56유흥주점영업올인광주광역시 서구 죽봉대로38번길 3 (농성동,(일층))83.522023-11-14
67유흥주점영업효일광주광역시 서구 내방로 394, 지하1층 (농성동)38.232023-11-14
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