Overview

Dataset statistics

Number of variables5
Number of observations26
Missing cells15
Missing cells (%)11.5%
Duplicate rows1
Duplicate rows (%)3.8%
Total size in memory1.2 KiB
Average record size in memory47.9 B

Variable types

Numeric3
Text2

Dataset

Description대구광역시 서구 한파쉼터 현황 데이터 입니다. 쉼터명, 도로명주소, 연면적, 수용인원 등의 데이터를 포함하고 있습니다.
Author대구광역시 서구
URLhttps://www.data.go.kr/data/15092270/fileData.do

Alerts

Dataset has 1 (3.8%) duplicate rowsDuplicates
연면적(제곱미터) is highly overall correlated with 수용인원(명)High correlation
수용인원(명) is highly overall correlated with 연면적(제곱미터)High correlation
연번 has 3 (11.5%) missing valuesMissing
쉼터명 has 3 (11.5%) missing valuesMissing
도로명주소 has 3 (11.5%) missing valuesMissing
연면적(제곱미터) has 3 (11.5%) missing valuesMissing
수용인원(명) has 3 (11.5%) missing valuesMissing

Reproduction

Analysis started2024-03-14 13:27:21.128363
Analysis finished2024-03-14 13:27:24.369686
Duration3.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)100.0%
Missing3
Missing (%)11.5%
Infinite0
Infinite (%)0.0%
Mean12
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size362.0 B
2024-03-14T22:27:24.477026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.1
Q16.5
median12
Q317.5
95-th percentile21.9
Maximum23
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.78233
Coefficient of variation (CV)0.56519417
Kurtosis-1.2
Mean12
Median Absolute Deviation (MAD)6
Skewness0
Sum276
Variance46
MonotonicityStrictly increasing
2024-03-14T22:27:24.690750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
2 1
 
3.8%
23 1
 
3.8%
22 1
 
3.8%
21 1
 
3.8%
20 1
 
3.8%
19 1
 
3.8%
18 1
 
3.8%
17 1
 
3.8%
16 1
 
3.8%
15 1
 
3.8%
Other values (13) 13
50.0%
(Missing) 3
 
11.5%
ValueCountFrequency (%)
1 1
3.8%
2 1
3.8%
3 1
3.8%
4 1
3.8%
5 1
3.8%
6 1
3.8%
7 1
3.8%
8 1
3.8%
9 1
3.8%
10 1
3.8%
ValueCountFrequency (%)
23 1
3.8%
22 1
3.8%
21 1
3.8%
20 1
3.8%
19 1
3.8%
18 1
3.8%
17 1
3.8%
16 1
3.8%
15 1
3.8%
14 1
3.8%

쉼터명
Text

MISSING 

Distinct23
Distinct (%)100.0%
Missing3
Missing (%)11.5%
Memory size336.0 B
2024-03-14T22:27:25.339829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length9.2608696
Min length5

Characters and Unicode

Total characters213
Distinct characters46
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

Unique23 ?
Unique (%)100.0%

Sample

1st row내당1동행정복지센터
2nd row내당2.3동 주민센터
3rd row내당4동행정복지센터
4th row비산1동 행정복지센터
5th row비산2,3동 행정복지센터
ValueCountFrequency (%)
행정복지센터 4
 
12.1%
주민센터 2
 
6.1%
내당2.3동 1
 
3.0%
평리6동 1
 
3.0%
쉘터 1
 
3.0%
버스 1
 
3.0%
스마트 1
 
3.0%
앞 1
 
3.0%
서구청 1
 
3.0%
원고개도서관 1
 
3.0%
Other values (19) 19
57.6%
2024-03-14T22:27:26.197140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 18
 
8.5%
센 17
 
8.0%
동 17
 
8.0%
지 12
 
5.6%
복 12
 
5.6%
정 12
 
5.6%
행 12
 
5.6%
10
 
4.7%
비 8
 
3.8%
산 7
 
3.3%
Other values (36) 88
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 184
86.4%
Decimal Number 17
 
8.0%
Space Separator 10
 
4.7%
Other Punctuation 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 18
 
9.8%
센 17
 
9.2%
동 17
 
9.2%
지 12
 
6.5%
복 12
 
6.5%
정 12
 
6.5%
행 12
 
6.5%
비 8
 
4.3%
산 7
 
3.8%
서 7
 
3.8%
Other values (26) 62
33.7%
Decimal Number
ValueCountFrequency (%)
2 3
17.6%
1 3
17.6%
4 3
17.6%
3 3
17.6%
5 2
11.8%
6 2
11.8%
7 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 184
86.4%
Common 29
 
13.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 18
 
9.8%
센 17
 
9.2%
동 17
 
9.2%
지 12
 
6.5%
복 12
 
6.5%
정 12
 
6.5%
행 12
 
6.5%
비 8
 
4.3%
산 7
 
3.8%
서 7
 
3.8%
Other values (26) 62
33.7%
Common
ValueCountFrequency (%)
10
34.5%
2 3
 
10.3%
1 3
 
10.3%
4 3
 
10.3%
3 3
 
10.3%
5 2
 
6.9%
6 2
 
6.9%
7 1
 
3.4%
, 1
 
3.4%
. 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 184
86.4%
ASCII 29
 
13.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 18
 
9.8%
센 17
 
9.2%
동 17
 
9.2%
지 12
 
6.5%
복 12
 
6.5%
정 12
 
6.5%
행 12
 
6.5%
비 8
 
4.3%
산 7
 
3.8%
서 7
 
3.8%
Other values (26) 62
33.7%
ASCII
ValueCountFrequency (%)
10
34.5%
2 3
 
10.3%
1 3
 
10.3%
4 3
 
10.3%
3 3
 
10.3%
5 2
 
6.9%
6 2
 
6.9%
7 1
 
3.4%
, 1
 
3.4%
. 1
 
3.4%

도로명주소
Text

MISSING 

Distinct23
Distinct (%)100.0%
Missing3
Missing (%)11.5%
Memory size336.0 B
2024-03-14T22:27:26.946337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length18.869565
Min length14

Characters and Unicode

Total characters434
Distinct characters48
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row대구광역시 서구 통학로35
2nd row대구광역시 서구 큰장로15길 11-1
3rd row대구광역시 서구 서대구로3길 46
4th row대구광역시 서구 북비산로65길 18
5th row대구광역시 서구 국채보상로81길33
ValueCountFrequency (%)
대구광역시 23
25.3%
서구 22
24.2%
문화로 3
 
3.3%
261 1
 
1.1%
257 1
 
1.1%
서대구로37길 1
 
1.1%
48 1
 
1.1%
서대구로45길 1
 
1.1%
22 1
 
1.1%
당산로 1
 
1.1%
Other values (36) 36
39.6%
2024-03-14T22:27:28.173694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
68
15.7%
구 48
 
11.1%
서 30
 
6.9%
대 26
 
6.0%
광 23
 
5.3%
역 23
 
5.3%
시 23
 
5.3%
로 23
 
5.3%
길 17
 
3.9%
3 14
 
3.2%
Other values (38) 139
32.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 273
62.9%
Decimal Number 83
 
19.1%
Space Separator 68
 
15.7%
Dash Punctuation 4
 
0.9%
Close Punctuation 3
 
0.7%
Open Punctuation 3
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 48
17.6%
서 30
11.0%
대 26
9.5%
광 23
8.4%
역 23
8.4%
시 23
8.4%
로 23
8.4%
길 17
 
6.2%
국 5
 
1.8%
달 5
 
1.8%
Other values (24) 50
18.3%
Decimal Number
ValueCountFrequency (%)
3 14
16.9%
1 14
16.9%
5 11
13.3%
6 10
12.0%
4 9
10.8%
2 8
9.6%
7 6
7.2%
8 5
 
6.0%
0 4
 
4.8%
9 2
 
2.4%
Space Separator
ValueCountFrequency (%)
68
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 273
62.9%
Common 161
37.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 48
17.6%
서 30
11.0%
대 26
9.5%
광 23
8.4%
역 23
8.4%
시 23
8.4%
로 23
8.4%
길 17
 
6.2%
국 5
 
1.8%
달 5
 
1.8%
Other values (24) 50
18.3%
Common
ValueCountFrequency (%)
68
42.2%
3 14
 
8.7%
1 14
 
8.7%
5 11
 
6.8%
6 10
 
6.2%
4 9
 
5.6%
2 8
 
5.0%
7 6
 
3.7%
8 5
 
3.1%
- 4
 
2.5%
Other values (4) 12
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 273
62.9%
ASCII 161
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
68
42.2%
3 14
 
8.7%
1 14
 
8.7%
5 11
 
6.8%
6 10
 
6.2%
4 9
 
5.6%
2 8
 
5.0%
7 6
 
3.7%
8 5
 
3.1%
- 4
 
2.5%
Other values (4) 12
 
7.5%
Hangul
ValueCountFrequency (%)
구 48
17.6%
서 30
11.0%
대 26
9.5%
광 23
8.4%
역 23
8.4%
시 23
8.4%
로 23
8.4%
길 17
 
6.2%
국 5
 
1.8%
달 5
 
1.8%
Other values (24) 50
18.3%

연면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct23
Distinct (%)100.0%
Missing3
Missing (%)11.5%
Infinite0
Infinite (%)0.0%
Mean376.7813
Minimum21.6
Maximum1206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size362.0 B
2024-03-14T22:27:28.550460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21.6
5-th percentile81.2
Q1209.32
median273.84
Q3433
95-th percentile980.869
Maximum1206
Range1184.4
Interquartile range (IQR)223.68

Descriptive statistics

Standard deviation290.22541
Coefficient of variation (CV)0.77027551
Kurtosis2.4389983
Mean376.7813
Median Absolute Deviation (MAD)92.84
Skewness1.6461091
Sum8665.97
Variance84230.79
MonotonicityNot monotonic
2024-03-14T22:27:28.854468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
217.0 1
 
3.8%
21.6 1
 
3.8%
71.0 1
 
3.8%
201.64 1
 
3.8%
297.0 1
 
3.8%
273.84 1
 
3.8%
173.0 1
 
3.8%
998.41 1
 
3.8%
1206.0 1
 
3.8%
181.0 1
 
3.8%
Other values (13) 13
50.0%
(Missing) 3
 
11.5%
ValueCountFrequency (%)
21.6 1
3.8%
71.0 1
3.8%
173.0 1
3.8%
181.0 1
3.8%
197.0 1
3.8%
201.64 1
3.8%
217.0 1
3.8%
234.48 1
3.8%
248.0 1
3.8%
250.0 1
3.8%
ValueCountFrequency (%)
1206.0 1
3.8%
998.41 1
3.8%
823.0 1
3.8%
660.6 1
3.8%
486.67 1
3.8%
443.0 1
3.8%
423.0 1
3.8%
380.13 1
3.8%
326.4 1
3.8%
297.0 1
3.8%

수용인원(명)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct18
Distinct (%)78.3%
Missing3
Missing (%)11.5%
Infinite0
Infinite (%)0.0%
Mean71
Minimum6
Maximum302
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size362.0 B
2024-03-14T22:27:29.055428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile20
Q127.5
median52
Q381
95-th percentile178.5
Maximum302
Range296
Interquartile range (IQR)53.5

Descriptive statistics

Standard deviation66.776425
Coefficient of variation (CV)0.94051303
Kurtosis5.9222614
Mean71
Median Absolute Deviation (MAD)27
Skewness2.243559
Sum1633
Variance4459.0909
MonotonicityNot monotonic
2024-03-14T22:27:29.258667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
30 3
 
11.5%
25 3
 
11.5%
20 2
 
7.7%
62 1
 
3.8%
6 1
 
3.8%
80 1
 
3.8%
52 1
 
3.8%
302 1
 
3.8%
45 1
 
3.8%
50 1
 
3.8%
Other values (8) 8
30.8%
(Missing) 3
 
11.5%
ValueCountFrequency (%)
6 1
 
3.8%
20 2
7.7%
25 3
11.5%
30 3
11.5%
45 1
 
3.8%
50 1
 
3.8%
52 1
 
3.8%
62 1
 
3.8%
66 1
 
3.8%
71 1
 
3.8%
ValueCountFrequency (%)
302 1
3.8%
180 1
3.8%
165 1
3.8%
100 1
3.8%
95 1
3.8%
82 1
3.8%
80 1
3.8%
72 1
3.8%
71 1
3.8%
66 1
3.8%

Interactions

2024-03-14T22:27:22.822070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:27:21.362590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:27:22.080739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:27:23.060882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:27:21.593747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:27:22.320873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:27:23.310708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:27:21.838478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:27:22.569669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T22:27:29.418054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번쉼터명도로명주소연면적(제곱미터)수용인원(명)
연번1.0001.0001.0000.6330.584
쉼터명1.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.000
연면적(제곱미터)0.6331.0001.0001.0000.808
수용인원(명)0.5841.0001.0000.8081.000
2024-03-14T22:27:29.588063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연면적(제곱미터)수용인원(명)
연번1.000-0.249-0.270
연면적(제곱미터)-0.2491.0000.611
수용인원(명)-0.2700.6111.000

Missing values

2024-03-14T22:27:23.637208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T22:27:23.952963image/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.
2024-03-14T22:27:24.253737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번쉼터명도로명주소연면적(제곱미터)수용인원(명)
01내당1동행정복지센터대구광역시 서구 통학로35380.1395
12내당2.3동 주민센터대구광역시 서구 큰장로15길 11-1217.025
23내당4동행정복지센터대구광역시 서구 서대구로3길 46326.482
34비산1동 행정복지센터대구광역시 서구 북비산로65길 18234.4871
45비산2,3동 행정복지센터대구광역시 서구 국채보상로81길33265.266
56비산4동주민센터대구광역시 서구 국채보상로78길 29-4423.025
67비산5동행정복지센터대구광역시 서구 달서천로65길 17197.020
78비원도서관대구광역시 서구 달서천로61안길 10823.0100
89비산6동주민센터대구광역시 서구 문화로67길3248.030
910비산7동행정복지센터대구광역시 서구 염색공단로5길 4660.6165
연번쉼터명도로명주소연면적(제곱미터)수용인원(명)
1617상중이동 주민센터대구광역시 서구 당산로 343998.41302
1718영어도서관대구광역시 서구 평리로 35길 90-6173.052
1819원대동 행정복지센터대구광역시 서구 달서로55길 5273.8420
1920서구어린이도서관대구광역시 서구 문화로 123(이현동)297.080
2021비산도서관대구광역시 서구 달서로 14길 13201.6430
2122원고개도서관대구광역시 서구 달서로43길 1271.025
2223서구청 앞 스마트 버스 쉘터대구광역시 서구 국채보상로 25721.66
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Duplicate rows

Most frequently occurring

연번쉼터명도로명주소연면적(제곱미터)수용인원(명)# duplicates
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