Overview

Dataset statistics

Number of variables7
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory64.5 B

Variable types

Numeric3
Text2
Categorical2

Dataset

Description광주광역시 광산구 관내에 위치한 문화재 목록현황 (명칭, 전체주소, 전화번호, 위도, 경도)에 대한 정보를 제공합니다.
Author광주광역시 광산구
URLhttps://www.data.go.kr/data/3034756/fileData.do

Alerts

전화번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique
명칭 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:27:45.155719
Analysis finished2023-12-12 22:27:46.371506
Duration1.22 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

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
2023-12-13T07:27:46.439470image/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
2023-12-13T07:27:46.550611image/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%

명칭
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T07:27:46.737036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length6.4583333
Min length3

Characters and Unicode

Total characters155
Distinct characters87
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
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 row광주 신창동 유적
2nd row광주 장덕동 근대 한옥
3rd row신룡동 오층석탑
4th row취병 조형 유허비
5th row고봉문집 목판
ValueCountFrequency (%)
광주 2
 
4.4%
장고분 2
 
4.4%
범세동 1
 
2.2%
입석마을 1
 
2.2%
입석 1
 
2.2%
무양서원 1
 
2.2%
풍영정 1
 
2.2%
용진정사 1
 
2.2%
고내상 1
 
2.2%
성지 1
 
2.2%
Other values (33) 33
73.3%
2023-12-13T07:27:47.078241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
 
13.5%
동 8
 
5.2%
정 5
 
3.2%
고 5
 
3.2%
가 3
 
1.9%
석 3
 
1.9%
양 3
 
1.9%
장 3
 
1.9%
삼 3
 
1.9%
용 3
 
1.9%
Other values (77) 98
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 134
86.5%
Space Separator 21
 
13.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 8
 
6.0%
정 5
 
3.7%
고 5
 
3.7%
가 3
 
2.2%
석 3
 
2.2%
양 3
 
2.2%
장 3
 
2.2%
삼 3
 
2.2%
용 3
 
2.2%
봉 2
 
1.5%
Other values (76) 96
71.6%
Space Separator
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 134
86.5%
Common 21
 
13.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 8
 
6.0%
정 5
 
3.7%
고 5
 
3.7%
가 3
 
2.2%
석 3
 
2.2%
양 3
 
2.2%
장 3
 
2.2%
삼 3
 
2.2%
용 3
 
2.2%
봉 2
 
1.5%
Other values (76) 96
71.6%
Common
ValueCountFrequency (%)
21
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 134
86.5%
ASCII 21
 
13.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21
100.0%
Hangul
ValueCountFrequency (%)
동 8
 
6.0%
정 5
 
3.7%
고 5
 
3.7%
가 3
 
2.2%
석 3
 
2.2%
양 3
 
2.2%
장 3
 
2.2%
삼 3
 
2.2%
용 3
 
2.2%
봉 2
 
1.5%
Other values (76) 96
71.6%

주소
Text

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T07:27:47.266700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length18.875
Min length17

Characters and Unicode

Total characters453
Distinct characters62
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)91.7%

Sample

1st row광주광역시 광산구 신창동 632-4
2nd row광주광역시 광산구 장덕로96번길 15
3rd row광주광역시 광산구 신룡동 산57-1
4th row광주광역시 광산구 비아안길 19
5th row광주광역시 광산구 광곡길 133
ValueCountFrequency (%)
광주광역시 24
25.0%
광산구 24
25.0%
광곡길 2
 
2.1%
133 2
 
2.1%
삼거동 1
 
1.0%
632-4 1
 
1.0%
본량동서로 1
 
1.0%
180-68 1
 
1.0%
송정동 1
 
1.0%
250-4 1
 
1.0%
Other values (38) 38
39.6%
2023-12-13T07:27:47.948785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
광 74
16.3%
72
15.9%
산 30
 
6.6%
주 24
 
5.3%
역 24
 
5.3%
시 24
 
5.3%
구 24
 
5.3%
1 19
 
4.2%
동 12
 
2.6%
길 12
 
2.6%
Other values (52) 138
30.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 290
64.0%
Decimal Number 81
 
17.9%
Space Separator 72
 
15.9%
Dash Punctuation 10
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 74
25.5%
산 30
10.3%
주 24
 
8.3%
역 24
 
8.3%
시 24
 
8.3%
구 24
 
8.3%
동 12
 
4.1%
길 12
 
4.1%
로 7
 
2.4%
번 4
 
1.4%
Other values (40) 55
19.0%
Decimal Number
ValueCountFrequency (%)
1 19
23.5%
5 11
13.6%
2 10
12.3%
3 8
9.9%
4 8
9.9%
6 7
 
8.6%
9 7
 
8.6%
0 5
 
6.2%
7 3
 
3.7%
8 3
 
3.7%
Space Separator
ValueCountFrequency (%)
72
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 290
64.0%
Common 163
36.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 74
25.5%
산 30
10.3%
주 24
 
8.3%
역 24
 
8.3%
시 24
 
8.3%
구 24
 
8.3%
동 12
 
4.1%
길 12
 
4.1%
로 7
 
2.4%
번 4
 
1.4%
Other values (40) 55
19.0%
Common
ValueCountFrequency (%)
72
44.2%
1 19
 
11.7%
5 11
 
6.7%
2 10
 
6.1%
- 10
 
6.1%
3 8
 
4.9%
4 8
 
4.9%
6 7
 
4.3%
9 7
 
4.3%
0 5
 
3.1%
Other values (2) 6
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 290
64.0%
ASCII 163
36.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
광 74
25.5%
산 30
10.3%
주 24
 
8.3%
역 24
 
8.3%
시 24
 
8.3%
구 24
 
8.3%
동 12
 
4.1%
길 12
 
4.1%
로 7
 
2.4%
번 4
 
1.4%
Other values (40) 55
19.0%
ASCII
ValueCountFrequency (%)
72
44.2%
1 19
 
11.7%
5 11
 
6.7%
2 10
 
6.1%
- 10
 
6.1%
3 8
 
4.9%
4 8
 
4.9%
6 7
 
4.3%
9 7
 
4.3%
0 5
 
3.1%
Other values (2) 6
 
3.7%

전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
062-960-6854
24 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row062-960-6854
2nd row062-960-6854
3rd row062-960-6854
4th row062-960-6854
5th row062-960-6854

Common Values

ValueCountFrequency (%)
062-960-6854 24
100.0%

Length

2023-12-13T07:27:48.069060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:27:48.155037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
062-960-6854 24
100.0%

위도
Real number (ℝ)

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.184102
Minimum35.082433
Maximum35.235837
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T07:27:48.249394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.082433
5-th percentile35.127333
Q135.173709
median35.183019
Q335.210901
95-th percentile35.234914
Maximum35.235837
Range0.15340367
Interquartile range (IQR)0.037191848

Descriptive statistics

Standard deviation0.036545804
Coefficient of variation (CV)0.0010387022
Kurtosis1.2922468
Mean35.184102
Median Absolute Deviation (MAD)0.022910095
Skewness-0.91826738
Sum844.41846
Variance0.0013355958
MonotonicityNot monotonic
2023-12-13T07:27:48.388702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
35.23583653 2
 
8.3%
35.19682512 1
 
4.2%
35.17931454 1
 
4.2%
35.17688983 1
 
4.2%
35.18005912 1
 
4.2%
35.17785011 1
 
4.2%
35.2018448 1
 
4.2%
35.15231234 1
 
4.2%
35.08243286 1
 
4.2%
35.21370544 1
 
4.2%
Other values (13) 13
54.2%
ValueCountFrequency (%)
35.08243286 1
4.2%
35.12605963 1
4.2%
35.13454646 1
4.2%
35.14942906 1
4.2%
35.15231234 1
4.2%
35.17047383 1
4.2%
35.174787 1
4.2%
35.17688983 1
4.2%
35.17785011 1
4.2%
35.17931454 1
4.2%
ValueCountFrequency (%)
35.23583653 2
8.3%
35.22968622 1
4.2%
35.22077248 1
4.2%
35.21370544 1
4.2%
35.21356307 1
4.2%
35.21001305 1
4.2%
35.2018448 1
4.2%
35.19894742 1
4.2%
35.19682512 1
4.2%
35.19123284 1
4.2%

경도
Real number (ℝ)

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.76596
Minimum126.67256
Maximum126.84574
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T07:27:48.528104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.67256
5-th percentile126.67959
Q1126.72441
median126.75951
Q3126.81659
95-th percentile126.84217
Maximum126.84574
Range0.1731777
Interquartile range (IQR)0.09217975

Descriptive statistics

Standard deviation0.056673451
Coefficient of variation (CV)0.00044707152
Kurtosis-1.2660744
Mean126.76596
Median Absolute Deviation (MAD)0.0450732
Skewness-0.13842165
Sum3042.383
Variance0.00321188
MonotonicityNot monotonic
2023-12-13T07:27:48.672441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
126.7451862 2
 
8.3%
126.8457374 1
 
4.2%
126.8385045 1
 
4.2%
126.7123166 1
 
4.2%
126.6837008 1
 
4.2%
126.8015055 1
 
4.2%
126.8253965 1
 
4.2%
126.6725597 1
 
4.2%
126.7871342 1
 
4.2%
126.7364894 1
 
4.2%
Other values (13) 13
54.2%
ValueCountFrequency (%)
126.6725597 1
4.2%
126.6788627 1
4.2%
126.6837008 1
4.2%
126.6875083 1
4.2%
126.7123166 1
4.2%
126.7237198 1
4.2%
126.7246398 1
4.2%
126.7364894 1
4.2%
126.7415952 1
4.2%
126.7451862 2
8.3%
ValueCountFrequency (%)
126.8457374 1
4.2%
126.8425376 1
4.2%
126.8400956 1
4.2%
126.8385045 1
4.2%
126.8253965 1
4.2%
126.8173586 1
4.2%
126.8163332 1
4.2%
126.802463 1
4.2%
126.8015055 1
4.2%
126.7951682 1
4.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
2021-12-31
24 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-12-31
2nd row2021-12-31
3rd row2021-12-31
4th row2021-12-31
5th row2021-12-31

Common Values

ValueCountFrequency (%)
2021-12-31 24
100.0%

Length

2023-12-13T07:27:48.833733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:27:48.914143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-12-31 24
100.0%

Interactions

2023-12-13T07:27:45.943752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:45.377598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:45.636861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:46.024573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:45.462963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:45.737519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:46.116618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:45.551328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:45.830680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:27:48.963410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번명칭주소위도경도
연번1.0001.0000.8790.5750.000
명칭1.0001.0001.0001.0001.000
주소0.8791.0001.0001.0001.000
위도0.5751.0001.0001.0000.834
경도0.0001.0001.0000.8341.000
2023-12-13T07:27:49.045446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.000-0.411-0.284
위도-0.4111.0000.277
경도-0.2840.2771.000

Missing values

2023-12-13T07:27:46.217466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:27:46.319975image/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

연번명칭주소전화번호위도경도데이터기준일자
01광주 신창동 유적광주광역시 광산구 신창동 632-4062-960-685435.196825126.8457372021-12-31
12광주 장덕동 근대 한옥광주광역시 광산구 장덕로96번길 15062-960-685435.191233126.8163332021-12-31
23신룡동 오층석탑광주광역시 광산구 신룡동 산57-1062-960-685435.229686126.771092021-12-31
34취병 조형 유허비광주광역시 광산구 비아안길 19062-960-685435.220772126.8173592021-12-31
45고봉문집 목판광주광역시 광산구 광곡길 133062-960-685435.235837126.7451862021-12-31
56양송천 묘역광주광역시 광산구 동호동 산32-9062-960-685435.183355126.6875082021-12-31
67빙월당광주광역시 광산구 광곡길 133062-960-685435.235837126.7451862021-12-31
78양씨 삼강문광주광역시 광산구 박호동 산131-1062-960-685435.170474126.7415952021-12-31
89용아생가광주광역시 광산구 소촌로46번길 24062-960-685435.149429126.7951682021-12-31
910월계동 장고분광주광역시 광산구 월계로 155062-960-685435.213563126.8425382021-12-31
연번명칭주소전화번호위도경도데이터기준일자
1415풍영정광주광역시 광산구 풍영정길 21062-960-685435.179315126.8385042021-12-31
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