Overview

Dataset statistics

Number of variables6
Number of observations153
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.6 KiB
Average record size in memory50.9 B

Variable types

Categorical2
Text2
Numeric2

Dataset

Description광주광역시 서구에 위치한 숙박시설의 업종명, 업소명, 영업소 주소, 위도, 경도, 행정동명 연락처 등에 대한 정보를 제공합니다.
Author광주광역시 서구
URLhttps://www.data.go.kr/data/15033519/fileData.do

Alerts

위도 is highly overall correlated with 행정동명(지번)High correlation
경도 is highly overall correlated with 행정동명(지번)High correlation
행정동명(지번) is highly overall correlated with 위도 and 1 other fieldsHigh correlation
업종명 is highly imbalanced (70.4%)Imbalance

Reproduction

Analysis started2023-12-12 21:00:55.990438
Analysis finished2023-12-12 21:00:56.980640
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
숙박업(일반)
145 
숙박업(생활)
 
8

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row숙박업(일반)
2nd row숙박업(일반)
3rd row숙박업(일반)
4th row숙박업(일반)
5th row숙박업(일반)

Common Values

ValueCountFrequency (%)
숙박업(일반) 145
94.8%
숙박업(생활) 8
 
5.2%

Length

2023-12-13T06:00:57.054042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:00:57.165889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박업(일반 145
94.8%
숙박업(생활 8
 
5.2%

업소명
Text

Distinct152
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T06:00:57.374688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length5.6339869
Min length1

Characters and Unicode

Total characters862
Distinct characters228
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

Unique151 ?
Unique (%)98.7%

Sample

1st row온천
2nd row미광여인숙
3rd row광전
4th row순천장
5th row백림장
ValueCountFrequency (%)
모텔 19
 
9.2%
호텔 10
 
4.9%
관광호텔 3
 
1.5%
상지호텔 2
 
1.0%
드라마 2
 
1.0%
하우스 2
 
1.0%
hotel 2
 
1.0%
베스트 1
 
0.5%
마스터스 1
 
0.5%
캐슬 1
 
0.5%
Other values (163) 163
79.1%
2023-12-13T06:00:57.719743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 94
 
10.9%
53
 
6.1%
모 50
 
5.8%
호 47
 
5.5%
스 36
 
4.2%
) 14
 
1.6%
( 14
 
1.6%
라 14
 
1.6%
인 13
 
1.5%
이 13
 
1.5%
Other values (218) 514
59.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 693
80.4%
Space Separator 53
 
6.1%
Uppercase Letter 49
 
5.7%
Lowercase Letter 26
 
3.0%
Close Punctuation 14
 
1.6%
Open Punctuation 14
 
1.6%
Decimal Number 11
 
1.3%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 94
 
13.6%
모 50
 
7.2%
호 47
 
6.8%
스 36
 
5.2%
라 14
 
2.0%
인 13
 
1.9%
이 13
 
1.9%
에 11
 
1.6%
하 11
 
1.6%
장 11
 
1.6%
Other values (179) 393
56.7%
Uppercase Letter
ValueCountFrequency (%)
L 6
12.2%
H 6
12.2%
I 5
10.2%
E 4
 
8.2%
T 4
 
8.2%
N 3
 
6.1%
B 3
 
6.1%
S 3
 
6.1%
M 2
 
4.1%
A 2
 
4.1%
Other values (8) 11
22.4%
Lowercase Letter
ValueCountFrequency (%)
e 5
19.2%
t 4
15.4%
a 3
11.5%
l 2
 
7.7%
o 2
 
7.7%
y 2
 
7.7%
h 2
 
7.7%
f 1
 
3.8%
i 1
 
3.8%
n 1
 
3.8%
Other values (3) 3
11.5%
Decimal Number
ValueCountFrequency (%)
5 5
45.5%
2 3
27.3%
3 2
 
18.2%
1 1
 
9.1%
Space Separator
ValueCountFrequency (%)
53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 693
80.4%
Common 94
 
10.9%
Latin 75
 
8.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 94
 
13.6%
모 50
 
7.2%
호 47
 
6.8%
스 36
 
5.2%
라 14
 
2.0%
인 13
 
1.9%
이 13
 
1.9%
에 11
 
1.6%
하 11
 
1.6%
장 11
 
1.6%
Other values (179) 393
56.7%
Latin
ValueCountFrequency (%)
L 6
 
8.0%
H 6
 
8.0%
e 5
 
6.7%
I 5
 
6.7%
t 4
 
5.3%
E 4
 
5.3%
T 4
 
5.3%
N 3
 
4.0%
a 3
 
4.0%
B 3
 
4.0%
Other values (21) 32
42.7%
Common
ValueCountFrequency (%)
53
56.4%
) 14
 
14.9%
( 14
 
14.9%
5 5
 
5.3%
2 3
 
3.2%
. 2
 
2.1%
3 2
 
2.1%
1 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 693
80.4%
ASCII 169
 
19.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 94
 
13.6%
모 50
 
7.2%
호 47
 
6.8%
스 36
 
5.2%
라 14
 
2.0%
인 13
 
1.9%
이 13
 
1.9%
에 11
 
1.6%
하 11
 
1.6%
장 11
 
1.6%
Other values (179) 393
56.7%
ASCII
ValueCountFrequency (%)
53
31.4%
) 14
 
8.3%
( 14
 
8.3%
L 6
 
3.6%
H 6
 
3.6%
5 5
 
3.0%
e 5
 
3.0%
I 5
 
3.0%
t 4
 
2.4%
E 4
 
2.4%
Other values (29) 53
31.4%

영업소 주소(도로명)
Text

Distinct152
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T06:00:57.937029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length34
Mean length27.928105
Min length20

Characters and Unicode

Total characters4273
Distinct characters93
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

Unique151 ?
Unique (%)98.7%

Sample

1st row광주광역시 서구 독립로204번길 25-1 (양동)
2nd row광주광역시 서구 천변좌로 216-10 (양동)
3rd row광주광역시 서구 독립로194번길 17-3 (양동)
4th row광주광역시 서구 경열로 12, 3-5층 (농성동)
5th row광주광역시 서구 죽봉대로97번길 1 (광천동)
ValueCountFrequency (%)
광주광역시 153
19.7%
서구 153
19.7%
치평동 20
 
2.6%
상무평화로 19
 
2.5%
쌍촌동 16
 
2.1%
상무연하로 16
 
2.1%
광천동 14
 
1.8%
양동 12
 
1.5%
농성동 10
 
1.3%
화정동 8
 
1.0%
Other values (221) 354
45.7%
2023-12-13T06:00:58.277590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
622
 
14.6%
광 323
 
7.6%
1 162
 
3.8%
시 159
 
3.7%
동 156
 
3.7%
구 154
 
3.6%
주 154
 
3.6%
역 153
 
3.6%
서 153
 
3.6%
) 153
 
3.6%
Other values (83) 2084
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2438
57.1%
Decimal Number 731
 
17.1%
Space Separator 622
 
14.6%
Close Punctuation 153
 
3.6%
Open Punctuation 153
 
3.6%
Other Punctuation 71
 
1.7%
Dash Punctuation 51
 
1.2%
Math Symbol 51
 
1.2%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 323
 
13.2%
시 159
 
6.5%
동 156
 
6.4%
구 154
 
6.3%
주 154
 
6.3%
역 153
 
6.3%
서 153
 
6.3%
로 153
 
6.3%
번 105
 
4.3%
길 100
 
4.1%
Other values (65) 828
34.0%
Decimal Number
ValueCountFrequency (%)
1 162
22.2%
2 96
13.1%
3 69
9.4%
4 66
9.0%
8 62
 
8.5%
5 61
 
8.3%
6 57
 
7.8%
0 55
 
7.5%
9 52
 
7.1%
7 51
 
7.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
622
100.0%
Close Punctuation
ValueCountFrequency (%)
) 153
100.0%
Open Punctuation
ValueCountFrequency (%)
( 153
100.0%
Other Punctuation
ValueCountFrequency (%)
, 71
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Math Symbol
ValueCountFrequency (%)
~ 51
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2438
57.1%
Common 1832
42.9%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 323
 
13.2%
시 159
 
6.5%
동 156
 
6.4%
구 154
 
6.3%
주 154
 
6.3%
역 153
 
6.3%
서 153
 
6.3%
로 153
 
6.3%
번 105
 
4.3%
길 100
 
4.1%
Other values (65) 828
34.0%
Common
ValueCountFrequency (%)
622
34.0%
1 162
 
8.8%
) 153
 
8.4%
( 153
 
8.4%
2 96
 
5.2%
, 71
 
3.9%
3 69
 
3.8%
4 66
 
3.6%
8 62
 
3.4%
5 61
 
3.3%
Other values (6) 317
17.3%
Latin
ValueCountFrequency (%)
A 2
66.7%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2438
57.1%
ASCII 1835
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
622
33.9%
1 162
 
8.8%
) 153
 
8.3%
( 153
 
8.3%
2 96
 
5.2%
, 71
 
3.9%
3 69
 
3.8%
4 66
 
3.6%
8 62
 
3.4%
5 61
 
3.3%
Other values (8) 320
17.4%
Hangul
ValueCountFrequency (%)
광 323
 
13.2%
시 159
 
6.5%
동 156
 
6.4%
구 154
 
6.3%
주 154
 
6.3%
역 153
 
6.3%
서 153
 
6.3%
로 153
 
6.3%
번 105
 
4.3%
길 100
 
4.1%
Other values (65) 828
34.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct149
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.151025
Minimum35.126134
Maximum35.163035
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T06:00:58.479588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.126134
5-th percentile35.13169
Q135.149542
median35.151824
Q335.154622
95-th percentile35.162232
Maximum35.163035
Range0.0369003
Interquartile range (IQR)0.0050802

Descriptive statistics

Standard deviation0.0082538568
Coefficient of variation (CV)0.00023481127
Kurtosis2.3759218
Mean35.151025
Median Absolute Deviation (MAD)0.002506
Skewness-1.4466419
Sum5378.1068
Variance6.8126152 × 10-5
MonotonicityNot monotonic
2023-12-13T06:00:58.630056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.1502169 2
 
1.3%
35.1545171 2
 
1.3%
35.1542918 2
 
1.3%
35.1531511 2
 
1.3%
35.149343 1
 
0.7%
35.1264124 1
 
0.7%
35.15223 1
 
0.7%
35.1261342 1
 
0.7%
35.1496394 1
 
0.7%
35.1507687 1
 
0.7%
Other values (139) 139
90.8%
ValueCountFrequency (%)
35.1261342 1
0.7%
35.126191 1
0.7%
35.1262222 1
0.7%
35.1264037 1
0.7%
35.1264124 1
0.7%
35.1264914 1
0.7%
35.1313061 1
0.7%
35.131682 1
0.7%
35.131695 1
0.7%
35.1327565 1
0.7%
ValueCountFrequency (%)
35.1630345 1
0.7%
35.162561 1
0.7%
35.1623815 1
0.7%
35.162365 1
0.7%
35.162355 1
0.7%
35.1623437 1
0.7%
35.1623385 1
0.7%
35.1622322 1
0.7%
35.162232 1
0.7%
35.1621069 1
0.7%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct147
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.86691
Minimum126.8144
Maximum126.9087
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T06:00:58.767156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.8144
5-th percentile126.84738
Q1126.85023
median126.85789
Q3126.88253
95-th percentile126.90499
Maximum126.9087
Range0.0942981
Interquartile range (IQR)0.0322976

Descriptive statistics

Standard deviation0.019589502
Coefficient of variation (CV)0.00015440986
Kurtosis-0.71958944
Mean126.86691
Median Absolute Deviation (MAD)0.0102122
Skewness0.44307456
Sum19410.637
Variance0.0003837486
MonotonicityNot monotonic
2023-12-13T06:00:58.904776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8486281 2
 
1.3%
126.8505821 2
 
1.3%
126.8505801 2
 
1.3%
126.8483578 2
 
1.3%
126.8473259 2
 
1.3%
126.8529934 2
 
1.3%
126.8522396 1
 
0.7%
126.8522383 1
 
0.7%
126.8572436 1
 
0.7%
126.8769065 1
 
0.7%
Other values (137) 137
89.5%
ValueCountFrequency (%)
126.8144009 1
0.7%
126.8359267 1
0.7%
126.8389248 1
0.7%
126.8448335 1
0.7%
126.8472348 1
0.7%
126.8473228 1
0.7%
126.8473259 2
1.3%
126.8474161 1
0.7%
126.8474243 1
0.7%
126.8476731 1
0.7%
ValueCountFrequency (%)
126.908699 1
0.7%
126.907414 1
0.7%
126.907124 1
0.7%
126.907042 1
0.7%
126.9065857 1
0.7%
126.9059106 1
0.7%
126.9054529 1
0.7%
126.9054369 1
0.7%
126.9046979 1
0.7%
126.9041825 1
0.7%

행정동명(지번)
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
치평동
42 
광천동
17 
양동
16 
상무1동
16 
화정1동
12 
Other values (7)
50 

Length

Max length4
Median length3
Mean length3.2941176
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row양동
2nd row양동
3rd row양동
4th row농성2동
5th row광천동

Common Values

ValueCountFrequency (%)
치평동 42
27.5%
광천동 17
11.1%
양동 16
 
10.5%
상무1동 16
 
10.5%
화정1동 12
 
7.8%
유덕동 11
 
7.2%
농성2동 8
 
5.2%
농성1동 8
 
5.2%
금호1동 7
 
4.6%
상무2동 7
 
4.6%
Other values (2) 9
 
5.9%

Length

2023-12-13T06:00:59.074863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
치평동 42
27.5%
광천동 17
11.1%
양동 16
 
10.5%
상무1동 16
 
10.5%
화정1동 12
 
7.8%
유덕동 11
 
7.2%
농성2동 8
 
5.2%
농성1동 8
 
5.2%
금호1동 7
 
4.6%
상무2동 7
 
4.6%
Other values (2) 9
 
5.9%

Interactions

2023-12-13T06:00:56.579097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:00:56.348760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:00:56.686499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:00:56.465860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:00:59.181899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명위도경도행정동명(지번)
업종명1.0000.0000.0000.000
위도0.0001.0000.7830.919
경도0.0000.7831.0000.889
행정동명(지번)0.0000.9190.8891.000
2023-12-13T06:00:59.285258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동명(지번)업종명
행정동명(지번)1.0000.000
업종명0.0001.000
2023-12-13T06:00:59.382099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도업종명행정동명(지번)
위도1.0000.2380.0000.689
경도0.2381.0000.0000.642
업종명0.0000.0001.0000.000
행정동명(지번)0.6890.6420.0001.000

Missing values

2023-12-13T06:00:56.812749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:00:56.928816image/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

업종명업소명영업소 주소(도로명)위도경도행정동명(지번)
0숙박업(일반)온천광주광역시 서구 독립로204번길 25-1 (양동)35.149343126.908699양동
1숙박업(일반)미광여인숙광주광역시 서구 천변좌로 216-10 (양동)35.15606126.900345양동
2숙박업(일반)광전광주광역시 서구 독립로194번길 17-3 (양동)35.149407126.907414양동
3숙박업(일반)순천장광주광역시 서구 경열로 12, 3-5층 (농성동)35.152742126.888064농성2동
4숙박업(일반)백림장광주광역시 서구 죽봉대로97번길 1 (광천동)35.162232126.883224광천동
5숙박업(일반)명승장 여관광주광역시 서구 독립로200번길 9, 2,3층 (양동)35.15015126.907042양동
6숙박업(일반)월드모텔광주광역시 서구 금화로85번길 4-33 (금호동)35.133828126.858544금호1동
7숙박업(일반)드림모텔광주광역시 서구 풍금로177번길 7 (금호동)35.131695126.858551금호2동
8숙박업(일반)SHH 삼화호텔광주광역시 서구 풍금로177번길 3 (금호동)35.131682126.858937금호2동
9숙박업(일반)제이광주광역시 서구 풍암1로21번길 15-7, 2~5 (풍암동)35.126191126.879539풍암동
업종명업소명영업소 주소(도로명)위도경도행정동명(지번)
143숙박업(일반)두바이호텔광주광역시 서구 상무번영로 47 (치평동)35.154046126.85063상무1동
144숙박업(일반)주식회사 씨에스호텔광주광역시 서구 상무평화로 128 (치평동)35.149216126.85039상무1동
145숙박업(생활)WIBILL광주광역시 서구 내방로398번길 26, 2층-5층(농성동,외1필지)35.155576126.88207농성1동
146숙박업(생활)늘푸른하우스광주광역시 서구 죽봉대로22번길 11, 2~4층(농성동)35.155594126.882541농성2동
147숙박업(생활)효원광주광역시 서구 상무대로876번길 5, 1~4층(쌍촌동)35.14979126.856039상무1동
148숙박업(생활)쿠바하우스광주광역시 서구 죽봉대로94번길 7, 2~3층(광천동)35.161968126.882223광천동
149숙박업(생활)엘림하우스광주광역시 서구 독립로200번길 10, 엘림하우스 1~5층(양동)35.149762126.904698양동
150숙박업(생활)축복광주광역시 서구 독립로190번길 9, 1~4층(양동)35.149486126.904183양동
151숙박업(생활)에스엠 시티(SM CITY)광주광역시 서구 쌍촌로65번길 42, 1~5층(쌍촌동)35.150107126.857885상무1동
152숙박업(생활)유탑 부티크 호텔광주광역시 서구 시청로 53, 1, 4~30층(치평동)35.153122126.849085치평동