Overview

Dataset statistics

Number of variables5
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory49.5 B

Variable types

Numeric4
Text1

Dataset

Description광주광역시 동구 다중이용업소 현황에 대한 데이터로 동부소방서 관할 119안전센터 업종별 수치를 나타내는 자료입니다.
Author광주광역시
URLhttps://www.data.go.kr/data/15045512/fileData.do

Alerts

연번 is highly overall correlated with 대인119안전센터High correlation
대인119안전센터 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
용산119안전센터 is highly overall correlated with 대인119안전센터 and 1 other fieldsHigh correlation
지산119안전센터 is highly overall correlated with 대인119안전센터 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
업종별 has unique valuesUnique
대인119안전센터 has 4 (16.7%) zerosZeros
용산119안전센터 has 12 (50.0%) zerosZeros
지산119안전센터 has 12 (50.0%) zerosZeros

Reproduction

Analysis started2023-12-12 01:16:28.376498
Analysis finished2023-12-12 01:16:30.441037
Duration2.06 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T10:16:30.509382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.15
Q16.75
median12.5
Q318.25
95-th percentile22.85
Maximum24
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.56568542
Kurtosis-1.2
Mean12.5
Median Absolute Deviation (MAD)6
Skewness0
Sum300
Variance50
MonotonicityStrictly increasing
2023-12-12T10:16:30.650526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 1
 
4.2%
14 1
 
4.2%
24 1
 
4.2%
23 1
 
4.2%
22 1
 
4.2%
21 1
 
4.2%
20 1
 
4.2%
19 1
 
4.2%
18 1
 
4.2%
17 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1 1
4.2%
2 1
4.2%
3 1
4.2%
4 1
4.2%
5 1
4.2%
6 1
4.2%
7 1
4.2%
8 1
4.2%
9 1
4.2%
10 1
4.2%
ValueCountFrequency (%)
24 1
4.2%
23 1
4.2%
22 1
4.2%
21 1
4.2%
20 1
4.2%
19 1
4.2%
18 1
4.2%
17 1
4.2%
16 1
4.2%
15 1
4.2%

업종별
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T10:16:30.877241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length8.9583333
Min length3

Characters and Unicode

Total characters215
Distinct characters74
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row유흥주점
2nd row단란주점
3rd row일반음식점_지하 66㎡이상
4th row일반음식점_지상100㎡이상
5th row제과점영업_지하 66㎡이상
ValueCountFrequency (%)
66㎡이상 3
 
9.7%
유흥주점 1
 
3.2%
복합유통제공업 1
 
3.2%
수면방업 1
 
3.2%
화상대화방 1
 
3.2%
및 1
 
3.2%
전화방 1
 
3.2%
고시원업 1
 
3.2%
골프연습장 1
 
3.2%
산후조리원 1
 
3.2%
Other values (19) 19
61.3%
2023-12-12T10:16:31.266320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
상 15
 
7.0%
0 14
 
6.5%
업 10
 
4.7%
이 9
 
4.2%
_ 9
 
4.2%
점 8
 
3.7%
인 7
 
3.3%
7
 
3.3%
원 7
 
3.3%
지 6
 
2.8%
Other values (64) 123
57.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 164
76.3%
Decimal Number 27
 
12.6%
Connector Punctuation 9
 
4.2%
Space Separator 7
 
3.3%
Other Symbol 6
 
2.8%
Uppercase Letter 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 15
 
9.1%
업 10
 
6.1%
이 9
 
5.5%
점 8
 
4.9%
인 7
 
4.3%
원 7
 
4.3%
지 6
 
3.7%
제 4
 
2.4%
화 4
 
2.4%
방 4
 
2.4%
Other values (55) 90
54.9%
Decimal Number
ValueCountFrequency (%)
0 14
51.9%
6 6
22.2%
1 5
 
18.5%
3 2
 
7.4%
Uppercase Letter
ValueCountFrequency (%)
P 1
50.0%
C 1
50.0%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 164
76.3%
Common 49
 
22.8%
Latin 2
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 15
 
9.1%
업 10
 
6.1%
이 9
 
5.5%
점 8
 
4.9%
인 7
 
4.3%
원 7
 
4.3%
지 6
 
3.7%
제 4
 
2.4%
화 4
 
2.4%
방 4
 
2.4%
Other values (55) 90
54.9%
Common
ValueCountFrequency (%)
0 14
28.6%
_ 9
18.4%
7
14.3%
6 6
12.2%
㎡ 6
12.2%
1 5
 
10.2%
3 2
 
4.1%
Latin
ValueCountFrequency (%)
P 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 164
76.3%
ASCII 45
 
20.9%
CJK Compat 6
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
상 15
 
9.1%
업 10
 
6.1%
이 9
 
5.5%
점 8
 
4.9%
인 7
 
4.3%
원 7
 
4.3%
지 6
 
3.7%
제 4
 
2.4%
화 4
 
2.4%
방 4
 
2.4%
Other values (55) 90
54.9%
ASCII
ValueCountFrequency (%)
0 14
31.1%
_ 9
20.0%
7
15.6%
6 6
13.3%
1 5
 
11.1%
3 2
 
4.4%
P 1
 
2.2%
C 1
 
2.2%
CJK Compat
ValueCountFrequency (%)
㎡ 6
100.0%

대인119안전센터
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)62.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.583333
Minimum0
Maximum122
Zeros4
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T10:16:31.420441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.75
median4
Q312
95-th percentile51.85
Maximum122
Range122
Interquartile range (IQR)10.25

Descriptive statistics

Standard deviation26.712506
Coefficient of variation (CV)1.8317147
Kurtosis11.698725
Mean14.583333
Median Absolute Deviation (MAD)3.5
Skewness3.2130981
Sum350
Variance713.55797
MonotonicityNot monotonic
2023-12-12T10:16:31.578372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
4 4
16.7%
0 4
16.7%
1 2
 
8.3%
2 2
 
8.3%
7 2
 
8.3%
55 1
 
4.2%
33 1
 
4.2%
15 1
 
4.2%
122 1
 
4.2%
11 1
 
4.2%
Other values (5) 5
20.8%
ValueCountFrequency (%)
0 4
16.7%
1 2
8.3%
2 2
8.3%
3 1
 
4.2%
4 4
16.7%
5 1
 
4.2%
7 2
8.3%
9 1
 
4.2%
11 1
 
4.2%
15 1
 
4.2%
ValueCountFrequency (%)
122 1
4.2%
55 1
4.2%
34 1
4.2%
33 1
4.2%
27 1
4.2%
15 1
4.2%
11 1
4.2%
9 1
4.2%
7 2
8.3%
5 1
4.2%

용산119안전센터
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8333333
Minimum0
Maximum24
Zeros12
Zeros (%)50.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T10:16:31.790751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.5
Q34.25
95-th percentile17.7
Maximum24
Range24
Interquartile range (IQR)4.25

Descriptive statistics

Standard deviation6.6245044
Coefficient of variation (CV)1.7281316
Kurtosis3.3653484
Mean3.8333333
Median Absolute Deviation (MAD)0.5
Skewness2.0170498
Sum92
Variance43.884058
MonotonicityNot monotonic
2023-12-12T10:16:31.966059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 12
50.0%
1 3
 
12.5%
18 1
 
4.2%
7 1
 
4.2%
24 1
 
4.2%
4 1
 
4.2%
10 1
 
4.2%
5 1
 
4.2%
16 1
 
4.2%
3 1
 
4.2%
ValueCountFrequency (%)
0 12
50.0%
1 3
 
12.5%
2 1
 
4.2%
3 1
 
4.2%
4 1
 
4.2%
5 1
 
4.2%
7 1
 
4.2%
10 1
 
4.2%
16 1
 
4.2%
18 1
 
4.2%
ValueCountFrequency (%)
24 1
 
4.2%
18 1
 
4.2%
16 1
 
4.2%
10 1
 
4.2%
7 1
 
4.2%
5 1
 
4.2%
4 1
 
4.2%
3 1
 
4.2%
2 1
 
4.2%
1 3
12.5%

지산119안전센터
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.75
Minimum0
Maximum45
Zeros12
Zeros (%)50.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T10:16:32.117544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.5
Q35.75
95-th percentile27.2
Maximum45
Range45
Interquartile range (IQR)5.75

Descriptive statistics

Standard deviation11.167694
Coefficient of variation (CV)1.9422077
Kurtosis6.385956
Mean5.75
Median Absolute Deviation (MAD)0.5
Skewness2.4765464
Sum138
Variance124.71739
MonotonicityNot monotonic
2023-12-12T10:16:32.243000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 12
50.0%
1 5
20.8%
11 1
 
4.2%
45 1
 
4.2%
13 1
 
4.2%
14 1
 
4.2%
17 1
 
4.2%
4 1
 
4.2%
29 1
 
4.2%
ValueCountFrequency (%)
0 12
50.0%
1 5
20.8%
4 1
 
4.2%
11 1
 
4.2%
13 1
 
4.2%
14 1
 
4.2%
17 1
 
4.2%
29 1
 
4.2%
45 1
 
4.2%
ValueCountFrequency (%)
45 1
 
4.2%
29 1
 
4.2%
17 1
 
4.2%
14 1
 
4.2%
13 1
 
4.2%
11 1
 
4.2%
4 1
 
4.2%
1 5
20.8%
0 12
50.0%

Interactions

2023-12-12T10:16:29.839049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:16:28.587412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:16:29.028185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:16:29.402649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:16:29.923394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:16:28.693775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:16:29.121712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:16:29.510211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:16:30.039242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:16:28.787198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:16:29.211154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:16:29.626727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:16:30.133055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:16:28.907456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:16:29.304988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:16:29.743376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:16:32.350917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종별대인119안전센터용산119안전센터지산119안전센터
연번1.0001.0000.0000.3820.862
업종별1.0001.0001.0001.0001.000
대인119안전센터0.0001.0001.0000.8610.905
용산119안전센터0.3821.0000.8611.0000.770
지산119안전센터0.8621.0000.9050.7701.000
2023-12-12T10:16:32.457160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번대인119안전센터용산119안전센터지산119안전센터
연번1.000-0.593-0.380-0.142
대인119안전센터-0.5931.0000.7830.500
용산119안전센터-0.3800.7831.0000.603
지산119안전센터-0.1420.5000.6031.000

Missing values

2023-12-12T10:16:30.243295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:16:30.388956image/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

연번업종별대인119안전센터용산119안전센터지산119안전센터
01유흥주점55181
12단란주점3370
23일반음식점_지하 66㎡이상15111
34일반음식점_지상100㎡이상1222445
45제과점영업_지하 66㎡이상100
56제과점영업_지상100㎡이상201
67휴게음식점_지하 66㎡이상1140
78휴게음식점_지상100㎡이상271013
89영화상영관500
910비디오물감상실업400
연번업종별대인119안전센터용산119안전센터지산119안전센터
1415복합유통제공업400
1516학원_수용인원100인이상 300인미만000
1617학원_수용인원 300인이상704
1718목욕장_수용인원100인이상001
1819산후조리원000
1920골프연습장131
2021고시원업4229
2122전화방 및 화상대화방000
2223수면방업300
2324콜라텍업410