Overview

Dataset statistics

Number of variables6
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory55.6 B

Variable types

Numeric3
Text2
Categorical1

Dataset

Description광주광역시 광산구에서 활동하는 상설공연단체들의 현황( 단체명, 주소, 위도, 경도, 데이터기준일자 등)에 대한 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15044864/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
연번 has unique valuesUnique
단체명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:20:29.507474
Analysis finished2023-12-12 08:20:30.964474
Duration1.46 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15
Minimum1
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T17:20:31.028803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.4
Q18
median15
Q322
95-th percentile27.6
Maximum29
Range28
Interquartile range (IQR)14

Descriptive statistics

Standard deviation8.5146932
Coefficient of variation (CV)0.56764621
Kurtosis-1.2
Mean15
Median Absolute Deviation (MAD)7
Skewness0
Sum435
Variance72.5
MonotonicityStrictly increasing
2023-12-12T17:20:31.147150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 1
 
3.4%
2 1
 
3.4%
29 1
 
3.4%
28 1
 
3.4%
27 1
 
3.4%
26 1
 
3.4%
25 1
 
3.4%
24 1
 
3.4%
23 1
 
3.4%
22 1
 
3.4%
Other values (19) 19
65.5%
ValueCountFrequency (%)
1 1
3.4%
2 1
3.4%
3 1
3.4%
4 1
3.4%
5 1
3.4%
6 1
3.4%
7 1
3.4%
8 1
3.4%
9 1
3.4%
10 1
3.4%
ValueCountFrequency (%)
29 1
3.4%
28 1
3.4%
27 1
3.4%
26 1
3.4%
25 1
3.4%
24 1
3.4%
23 1
3.4%
22 1
3.4%
21 1
3.4%
20 1
3.4%

단체명
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T17:20:31.347222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length7.0344828
Min length2

Characters and Unicode

Total characters204
Distinct characters105
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row앙상블 사분쉼표
2nd row엔젤스 뮤직
3rd row앙상블 앙코라
4th row울림 음악회
5th row그라지오 색소폰 연주단
ValueCountFrequency (%)
앙상블 2
 
4.9%
음악회 2
 
4.9%
희여재시문학회 1
 
2.4%
공감문화예술단 1
 
2.4%
첨단골열린음악회운영위원회 1
 
2.4%
뮤직스페이스공감 1
 
2.4%
광산문학회 1
 
2.4%
딩기리닷컴 1
 
2.4%
어등산힐링공연단 1
 
2.4%
무등문화예술단 1
 
2.4%
Other values (29) 29
70.7%
2023-12-12T17:20:31.730753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
5.9%
회 8
 
3.9%
리 6
 
2.9%
단 6
 
2.9%
악 5
 
2.5%
스 5
 
2.5%
음 4
 
2.0%
문 4
 
2.0%
드 4
 
2.0%
주 3
 
1.5%
Other values (95) 147
72.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 190
93.1%
Space Separator 12
 
5.9%
Other Punctuation 1
 
0.5%
Uppercase Letter 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 8
 
4.2%
리 6
 
3.2%
단 6
 
3.2%
악 5
 
2.6%
스 5
 
2.6%
음 4
 
2.1%
문 4
 
2.1%
드 4
 
2.1%
주 3
 
1.6%
술 3
 
1.6%
Other values (92) 142
74.7%
Space Separator
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 190
93.1%
Common 13
 
6.4%
Latin 1
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 8
 
4.2%
리 6
 
3.2%
단 6
 
3.2%
악 5
 
2.6%
스 5
 
2.6%
음 4
 
2.1%
문 4
 
2.1%
드 4
 
2.1%
주 3
 
1.6%
술 3
 
1.6%
Other values (92) 142
74.7%
Common
ValueCountFrequency (%)
12
92.3%
. 1
 
7.7%
Latin
ValueCountFrequency (%)
M 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 190
93.1%
ASCII 14
 
6.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
85.7%
. 1
 
7.1%
M 1
 
7.1%
Hangul
ValueCountFrequency (%)
회 8
 
4.2%
리 6
 
3.2%
단 6
 
3.2%
악 5
 
2.6%
스 5
 
2.6%
음 4
 
2.1%
문 4
 
2.1%
드 4
 
2.1%
주 3
 
1.6%
술 3
 
1.6%
Other values (92) 142
74.7%

주소
Text

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T17:20:31.990377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length27
Mean length22.413793
Min length16

Characters and Unicode

Total characters650
Distinct characters64
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)89.7%

Sample

1st row광주광역시 광산구 목련로382번길 114
2nd row광주광역시 광산구 월계로 117-21
3rd row광주광역시 광산구 목련로382번길 114
4th row광주광역시 광산구 월곡로 51
5th row광주광역시 광산구 하림길 20(임곡동)
ValueCountFrequency (%)
광주광역시 29
23.6%
광산구 28
22.8%
월계로 4
 
3.3%
목련로382번길 3
 
2.4%
114 3
 
2.4%
목련로153번길 2
 
1.6%
첨단내촌로57번길 1
 
0.8%
41-47 1
 
0.8%
도천남길 1
 
0.8%
101호 1
 
0.8%
Other values (50) 50
40.7%
2023-12-12T17:20:32.470998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
94
 
14.5%
광 86
 
13.2%
1 38
 
5.8%
시 30
 
4.6%
산 30
 
4.6%
역 29
 
4.5%
구 29
 
4.5%
주 29
 
4.5%
로 27
 
4.2%
길 18
 
2.8%
Other values (54) 240
36.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 398
61.2%
Decimal Number 133
 
20.5%
Space Separator 94
 
14.5%
Close Punctuation 7
 
1.1%
Open Punctuation 7
 
1.1%
Dash Punctuation 6
 
0.9%
Other Punctuation 5
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 86
21.6%
시 30
 
7.5%
산 30
 
7.5%
역 29
 
7.3%
구 29
 
7.3%
주 29
 
7.3%
로 27
 
6.8%
길 18
 
4.5%
번 15
 
3.8%
동 7
 
1.8%
Other values (39) 98
24.6%
Decimal Number
ValueCountFrequency (%)
1 38
28.6%
4 15
 
11.3%
2 15
 
11.3%
0 13
 
9.8%
3 13
 
9.8%
8 9
 
6.8%
5 8
 
6.0%
7 8
 
6.0%
6 7
 
5.3%
9 7
 
5.3%
Space Separator
ValueCountFrequency (%)
94
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 398
61.2%
Common 252
38.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 86
21.6%
시 30
 
7.5%
산 30
 
7.5%
역 29
 
7.3%
구 29
 
7.3%
주 29
 
7.3%
로 27
 
6.8%
길 18
 
4.5%
번 15
 
3.8%
동 7
 
1.8%
Other values (39) 98
24.6%
Common
ValueCountFrequency (%)
94
37.3%
1 38
15.1%
4 15
 
6.0%
2 15
 
6.0%
0 13
 
5.2%
3 13
 
5.2%
8 9
 
3.6%
5 8
 
3.2%
7 8
 
3.2%
) 7
 
2.8%
Other values (5) 32
 
12.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 398
61.2%
ASCII 252
38.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
94
37.3%
1 38
15.1%
4 15
 
6.0%
2 15
 
6.0%
0 13
 
5.2%
3 13
 
5.2%
8 9
 
3.6%
5 8
 
3.2%
7 8
 
3.2%
) 7
 
2.8%
Other values (5) 32
 
12.7%
Hangul
ValueCountFrequency (%)
광 86
21.6%
시 30
 
7.5%
산 30
 
7.5%
역 29
 
7.3%
구 29
 
7.3%
주 29
 
7.3%
로 27
 
6.8%
길 18
 
4.5%
번 15
 
3.8%
동 7
 
1.8%
Other values (39) 98
24.6%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.191209
Minimum35.128468
Maximum35.221907
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T17:20:32.641849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.128468
5-th percentile35.146509
Q135.178698
median35.194282
Q335.211807
95-th percentile35.220851
Maximum35.221907
Range0.093438646
Interquartile range (IQR)0.03310834

Descriptive statistics

Standard deviation0.025516869
Coefficient of variation (CV)0.00072509213
Kurtosis-0.22217238
Mean35.191209
Median Absolute Deviation (MAD)0.017524482
Skewness-0.69924996
Sum1020.5451
Variance0.0006511106
MonotonicityNot monotonic
2023-12-12T17:20:32.776487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
35.1803225545013 3
 
10.3%
35.2153685185787 1
 
3.4%
35.2184701362169 1
 
3.4%
35.2219069047465 1
 
3.4%
35.1540099346421 1
 
3.4%
35.1893537292302 1
 
3.4%
35.2115247300575 1
 
3.4%
35.1942821779985 1
 
3.4%
35.2065540808764 1
 
3.4%
35.2110876549572 1
 
3.4%
Other values (17) 17
58.6%
ValueCountFrequency (%)
35.1284682589626 1
3.4%
35.1415086997687 1
3.4%
35.1540099346421 1
3.4%
35.1595421534054 1
3.4%
35.1687973467251 1
3.4%
35.1704665344627 1
3.4%
35.1733824313746 1
3.4%
35.1786983203958 1
3.4%
35.1793649899228 1
3.4%
35.1796071192302 1
3.4%
ValueCountFrequency (%)
35.2219069047465 1
3.4%
35.2216837633929 1
3.4%
35.2196023907355 1
3.4%
35.2184701362169 1
3.4%
35.2170858250037 1
3.4%
35.2153685185787 1
3.4%
35.2132944381754 1
3.4%
35.2118066600981 1
3.4%
35.2116068745723 1
3.4%
35.2115247300575 1
3.4%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.82354
Minimum126.74575
Maximum126.8965
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T17:20:32.950604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.74575
5-th percentile126.77655
Q1126.81369
median126.82407
Q3126.83758
95-th percentile126.85218
Maximum126.8965
Range0.15075265
Interquartile range (IQR)0.023893495

Descriptive statistics

Standard deviation0.027422838
Coefficient of variation (CV)0.00021622829
Kurtosis2.8560581
Mean126.82354
Median Absolute Deviation (MAD)0.013513728
Skewness-0.47683051
Sum3677.8828
Variance0.00075201205
MonotonicityNot monotonic
2023-12-12T17:20:33.084258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
126.837578796259 3
 
10.3%
126.838129347507 1
 
3.4%
126.830992759822 1
 
3.4%
126.820482475487 1
 
3.4%
126.81317648767 1
 
3.4%
126.824065068523 1
 
3.4%
126.833426191668 1
 
3.4%
126.819732809155 1
 
3.4%
126.819547222024 1
 
3.4%
126.835661381538 1
 
3.4%
Other values (17) 17
58.6%
ValueCountFrequency (%)
126.745747943479 1
3.4%
126.766267539813 1
3.4%
126.791985504401 1
3.4%
126.7959150929 1
3.4%
126.805976656327 1
3.4%
126.809397523035 1
3.4%
126.81317648767 1
3.4%
126.813685301152 1
3.4%
126.814942333422 1
3.4%
126.815611304865 1
3.4%
ValueCountFrequency (%)
126.896500593936 1
 
3.4%
126.8538302163 1
 
3.4%
126.849706494095 1
 
3.4%
126.844126382428 1
 
3.4%
126.841962756798 1
 
3.4%
126.838129347507 1
 
3.4%
126.837578796259 3
10.3%
126.83596891507 1
 
3.4%
126.835661381538 1
 
3.4%
126.834007807778 1
 
3.4%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-05-12
29 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-12
2nd row2023-05-12
3rd row2023-05-12
4th row2023-05-12
5th row2023-05-12

Common Values

ValueCountFrequency (%)
2023-05-12 29
100.0%

Length

2023-12-12T17:20:33.247999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:20:33.373397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-12 29
100.0%

Interactions

2023-12-12T17:20:30.399897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:29.744567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:30.068749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:30.533450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:29.836669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:30.156456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:30.644577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:29.937596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:20:30.245500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:20:33.435428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번단체명주소위도경도
연번1.0001.0000.9420.0870.600
단체명1.0001.0001.0001.0001.000
주소0.9421.0001.0001.0001.000
위도0.0871.0001.0001.0000.681
경도0.6001.0001.0000.6811.000
2023-12-12T17:20:33.535841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.0000.2060.121
위도0.2061.0000.507
경도0.1210.5071.000

Missing values

2023-12-12T17:20:30.794405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:20:30.920613image/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

연번단체명주소위도경도데이터기준일자
01앙상블 사분쉼표광주광역시 광산구 목련로382번길 11435.180323126.8375792023-05-12
12엔젤스 뮤직광주광역시 광산구 월계로 117-2135.215369126.8381292023-05-12
23앙상블 앙코라광주광역시 광산구 목련로382번길 11435.180323126.8375792023-05-12
34울림 음악회광주광역시 광산구 월곡로 5135.168797126.8149422023-05-12
45그라지오 색소폰 연주단광주광역시 광산구 하림길 20(임곡동)35.219602126.7457482023-05-12
56써니빌리지광주광역시 광산구 목련로153번길 13435.178698126.8156112023-05-12
67위드폴리광주광역시 광산구 하남대로 3035.179607126.7959152023-05-12
78뮤직밴드 네시봉광주광역시 광산구 장덕로95번길 4535.19834126.8191892023-05-12
89리버힐 동호회광주광역시 광산구 우산로 47(우산동)35.159542126.8059772023-05-12
910럼피우스.M광주광역시 광산구 목련로153번길 143(운남동)35.179365126.8136852023-05-12
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