Overview

Dataset statistics

Number of variables10
Number of observations82
Missing cells6
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.0 KiB
Average record size in memory87.6 B

Variable types

Numeric6
Text3
DateTime1

Dataset

Description대구광역시 서구 관내 경로당 82개소 등록경로당명, 경로당 주소, 부지면적, 건물면적, 회원수, 전화번호, 경로당 설립 기준일자 등 대구광역시 서구 경로당에 관한 현황자료 등록
Author대구광역시 서구
URLhttps://www.data.go.kr/data/3072024/fileData.do

Alerts

기준일자 has constant value ""Constant
부지(제곱미터) is highly overall correlated with 건물(제곱미터)High correlation
건물(제곱미터) is highly overall correlated with 부지(제곱미터)High correlation
회원총계 is highly overall correlated with 여자회원High correlation
여자회원 is highly overall correlated with 회원총계High correlation
전화번호 has 6 (7.3%) missing valuesMissing
연번 has unique valuesUnique
소재지 has unique valuesUnique
남자회원 has 19 (23.2%) zerosZeros
여자회원 has 2 (2.4%) zerosZeros

Reproduction

Analysis started2024-03-16 04:12:40.074504
Analysis finished2024-03-16 04:12:47.009310
Duration6.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.5
Minimum1
Maximum82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-03-16T13:12:47.089633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.05
Q121.25
median41.5
Q361.75
95-th percentile77.95
Maximum82
Range81
Interquartile range (IQR)40.5

Descriptive statistics

Standard deviation23.815261
Coefficient of variation (CV)0.57386172
Kurtosis-1.2
Mean41.5
Median Absolute Deviation (MAD)20.5
Skewness0
Sum3403
Variance567.16667
MonotonicityStrictly increasing
2024-03-16T13:12:47.248697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
63 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
55 1
 
1.2%
54 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
82 1
1.2%
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%
74 1
1.2%
73 1
1.2%

경로당명칭
Text

Distinct80
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size788.0 B
2024-03-16T13:12:47.517940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length6.7195122
Min length5

Characters and Unicode

Total characters551
Distinct characters111
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

Unique79 ?
Unique (%)96.3%

Sample

1st row내서경로당
2nd row시영내당(아)경로당
3rd row홍실1차경로당
4th row황성정경로당
5th row홍실2차경로당
ValueCountFrequency (%)
경로당 4
 
4.7%
장수경로당 3
 
3.5%
평리 1
 
1.2%
평리5동경로당 1
 
1.2%
평리푸르지오경로당 1
 
1.2%
평리청구타운경로당 1
 
1.2%
평광경로당 1
 
1.2%
청수경로당 1
 
1.2%
만수경로당 1
 
1.2%
평리6동경로당 1
 
1.2%
Other values (71) 71
82.6%
2024-03-16T13:12:47.942878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
당 87
15.8%
경 82
 
14.9%
로 82
 
14.9%
동 19
 
3.4%
리 15
 
2.7%
2 12
 
2.2%
산 11
 
2.0%
평 11
 
2.0%
비 10
 
1.8%
1 9
 
1.6%
Other values (101) 213
38.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 506
91.8%
Decimal Number 32
 
5.8%
Space Separator 7
 
1.3%
Open Punctuation 2
 
0.4%
Close Punctuation 2
 
0.4%
Other Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 87
17.2%
경 82
16.2%
로 82
16.2%
동 19
 
3.8%
리 15
 
3.0%
산 11
 
2.2%
평 11
 
2.2%
비 10
 
2.0%
제 9
 
1.8%
원 6
 
1.2%
Other values (90) 174
34.4%
Decimal Number
ValueCountFrequency (%)
2 12
37.5%
1 9
28.1%
5 3
 
9.4%
6 3
 
9.4%
7 2
 
6.2%
3 2
 
6.2%
4 1
 
3.1%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 506
91.8%
Common 45
 
8.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 87
17.2%
경 82
16.2%
로 82
16.2%
동 19
 
3.8%
리 15
 
3.0%
산 11
 
2.2%
평 11
 
2.2%
비 10
 
2.0%
제 9
 
1.8%
원 6
 
1.2%
Other values (90) 174
34.4%
Common
ValueCountFrequency (%)
2 12
26.7%
1 9
20.0%
7
15.6%
5 3
 
6.7%
6 3
 
6.7%
( 2
 
4.4%
) 2
 
4.4%
, 2
 
4.4%
7 2
 
4.4%
3 2
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 506
91.8%
ASCII 45
 
8.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
당 87
17.2%
경 82
16.2%
로 82
16.2%
동 19
 
3.8%
리 15
 
3.0%
산 11
 
2.2%
평 11
 
2.2%
비 10
 
2.0%
제 9
 
1.8%
원 6
 
1.2%
Other values (90) 174
34.4%
ASCII
ValueCountFrequency (%)
2 12
26.7%
1 9
20.0%
7
15.6%
5 3
 
6.7%
6 3
 
6.7%
( 2
 
4.4%
) 2
 
4.4%
, 2
 
4.4%
7 2
 
4.4%
3 2
 
4.4%

소재지
Text

UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size788.0 B
2024-03-16T13:12:48.218036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length24.609756
Min length20

Characters and Unicode

Total characters2018
Distinct characters66
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

Unique82 ?
Unique (%)100.0%

Sample

1st row대구 서구 달구벌대로 365길 21-5
2nd row대구광역시 서구 서대구로8길 15(내당동)
3rd row대구광역시 서구 서대구로8길 49(내당동)
4th row대구광역시 서구 통학로 46(내당동)
5th row대구광역시 서구 통학로 39(내당동)
ValueCountFrequency (%)
서구 82
24.8%
대구광역시 80
24.2%
평리로 4
 
1.2%
서대구로 3
 
0.9%
북비산로61길 2
 
0.6%
당산로 2
 
0.6%
국채보상로36길 2
 
0.6%
국채보상로38길 2
 
0.6%
서대구로8길 2
 
0.6%
대구 2
 
0.6%
Other values (138) 149
45.2%
2024-03-16T13:12:48.606796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
248
 
12.3%
구 185
 
9.2%
대 110
 
5.5%
서 108
 
5.4%
로 82
 
4.1%
( 80
 
4.0%
시 80
 
4.0%
역 80
 
4.0%
광 80
 
4.0%
) 80
 
4.0%
Other values (56) 885
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1203
59.6%
Decimal Number 360
 
17.8%
Space Separator 248
 
12.3%
Open Punctuation 80
 
4.0%
Close Punctuation 80
 
4.0%
Dash Punctuation 45
 
2.2%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 185
15.4%
대 110
 
9.1%
서 108
 
9.0%
로 82
 
6.8%
시 80
 
6.7%
역 80
 
6.7%
광 80
 
6.7%
동 80
 
6.7%
길 61
 
5.1%
리 40
 
3.3%
Other values (41) 297
24.7%
Decimal Number
ValueCountFrequency (%)
3 64
17.8%
1 58
16.1%
2 52
14.4%
6 41
11.4%
4 38
10.6%
5 31
8.6%
7 27
7.5%
0 20
 
5.6%
8 17
 
4.7%
9 12
 
3.3%
Space Separator
ValueCountFrequency (%)
248
100.0%
Open Punctuation
ValueCountFrequency (%)
( 80
100.0%
Close Punctuation
ValueCountFrequency (%)
) 80
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1203
59.6%
Common 815
40.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 185
15.4%
대 110
 
9.1%
서 108
 
9.0%
로 82
 
6.8%
시 80
 
6.7%
역 80
 
6.7%
광 80
 
6.7%
동 80
 
6.7%
길 61
 
5.1%
리 40
 
3.3%
Other values (41) 297
24.7%
Common
ValueCountFrequency (%)
248
30.4%
( 80
 
9.8%
) 80
 
9.8%
3 64
 
7.9%
1 58
 
7.1%
2 52
 
6.4%
- 45
 
5.5%
6 41
 
5.0%
4 38
 
4.7%
5 31
 
3.8%
Other values (5) 78
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1203
59.6%
ASCII 815
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
248
30.4%
( 80
 
9.8%
) 80
 
9.8%
3 64
 
7.9%
1 58
 
7.1%
2 52
 
6.4%
- 45
 
5.5%
6 41
 
5.0%
4 38
 
4.7%
5 31
 
3.8%
Other values (5) 78
 
9.6%
Hangul
ValueCountFrequency (%)
구 185
15.4%
대 110
 
9.1%
서 108
 
9.0%
로 82
 
6.8%
시 80
 
6.7%
역 80
 
6.7%
광 80
 
6.7%
동 80
 
6.7%
길 61
 
5.1%
리 40
 
3.3%
Other values (41) 297
24.7%

부지(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct80
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1421.4602
Minimum18.54
Maximum69796.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-03-16T13:12:48.817714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18.54
5-th percentile36.261
Q1106
median141.335
Q3202.3725
95-th percentile293.415
Maximum69796.4
Range69777.86
Interquartile range (IQR)96.3725

Descriptive statistics

Standard deviation8554.4331
Coefficient of variation (CV)6.0180601
Kurtosis54.276534
Mean1421.4602
Median Absolute Deviation (MAD)50.915
Skewness7.2183407
Sum116559.74
Variance73178326
MonotonicityNot monotonic
2024-03-16T13:12:49.012053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
106.0 2
 
2.4%
50.7 2
 
2.4%
125.5 1
 
1.2%
202.8 1
 
1.2%
119.46 1
 
1.2%
100.0 1
 
1.2%
165.8 1
 
1.2%
183.9 1
 
1.2%
118.7 1
 
1.2%
26.44 1
 
1.2%
Other values (70) 70
85.4%
ValueCountFrequency (%)
18.54 1
1.2%
26.44 1
1.2%
29.75 1
1.2%
35.07 1
1.2%
36.06 1
1.2%
40.08 1
1.2%
42.69 1
1.2%
49.6 1
1.2%
50.7 2
2.4%
50.8 1
1.2%
ValueCountFrequency (%)
69796.4 1
1.2%
34920.0 1
1.2%
375.4 1
1.2%
324.0 1
1.2%
294.0 1
1.2%
282.3 1
1.2%
268.9 1
1.2%
268.6 1
1.2%
252.56 1
1.2%
251.0 1
1.2%

건물(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct81
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109.07865
Minimum18.54
Maximum253.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-03-16T13:12:49.156849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18.54
5-th percentile26.6055
Q163.735
median110.57
Q3144.96
95-th percentile193.372
Maximum253.9
Range235.36
Interquartile range (IQR)81.225

Descriptive statistics

Standard deviation52.541385
Coefficient of variation (CV)0.48168351
Kurtosis-0.44161987
Mean109.07865
Median Absolute Deviation (MAD)38.3
Skewness0.22250847
Sum8944.449
Variance2760.5971
MonotonicityNot monotonic
2024-03-16T13:12:49.275143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50.7 2
 
2.4%
58.14 1
 
1.2%
94.87 1
 
1.2%
105.36 1
 
1.2%
119.46 1
 
1.2%
100.0 1
 
1.2%
151.46 1
 
1.2%
108.86 1
 
1.2%
120.46 1
 
1.2%
26.44 1
 
1.2%
Other values (71) 71
86.6%
ValueCountFrequency (%)
18.54 1
1.2%
23.0 1
1.2%
25.07 1
1.2%
26.38 1
1.2%
26.44 1
1.2%
29.75 1
1.2%
35.07 1
1.2%
36.06 1
1.2%
39.54 1
1.2%
40.08 1
1.2%
ValueCountFrequency (%)
253.9 1
1.2%
225.88 1
1.2%
200.28 1
1.2%
194.629 1
1.2%
193.46 1
1.2%
191.7 1
1.2%
183.68 1
1.2%
177.84 1
1.2%
174.8 1
1.2%
172.84 1
1.2%

회원총계
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)40.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.073171
Minimum12
Maximum69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-03-16T13:12:49.380819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile19
Q125
median30
Q335
95-th percentile49.8
Maximum69
Range57
Interquartile range (IQR)10

Descriptive statistics

Standard deviation10.284569
Coefficient of variation (CV)0.33097906
Kurtosis2.5935945
Mean31.073171
Median Absolute Deviation (MAD)5
Skewness1.1793149
Sum2548
Variance105.77236
MonotonicityNot monotonic
2024-03-16T13:12:49.488987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
30 13
 
15.9%
25 7
 
8.5%
28 6
 
7.3%
21 5
 
6.1%
31 4
 
4.9%
23 3
 
3.7%
39 3
 
3.7%
35 3
 
3.7%
38 3
 
3.7%
33 2
 
2.4%
Other values (23) 33
40.2%
ValueCountFrequency (%)
12 2
 
2.4%
13 1
 
1.2%
16 1
 
1.2%
19 2
 
2.4%
20 1
 
1.2%
21 5
6.1%
22 2
 
2.4%
23 3
3.7%
24 2
 
2.4%
25 7
8.5%
ValueCountFrequency (%)
69 1
1.2%
64 1
1.2%
58 1
1.2%
50 2
2.4%
46 1
1.2%
45 2
2.4%
43 1
1.2%
42 1
1.2%
41 1
1.2%
40 2
2.4%

남자회원
Real number (ℝ)

ZEROS 

Distinct20
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.9878049
Minimum0
Maximum28
Zeros19
Zeros (%)23.2%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-03-16T13:12:49.626162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q38
95-th percentile18.95
Maximum28
Range28
Interquartile range (IQR)7

Descriptive statistics

Standard deviation6.1393165
Coefficient of variation (CV)1.0253034
Kurtosis2.3494505
Mean5.9878049
Median Absolute Deviation (MAD)4
Skewness1.4609286
Sum491
Variance37.691207
MonotonicityNot monotonic
2024-03-16T13:12:49.754640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 19
23.2%
7 8
9.8%
8 8
9.8%
5 7
 
8.5%
1 6
 
7.3%
9 5
 
6.1%
4 5
 
6.1%
3 4
 
4.9%
2 4
 
4.9%
10 3
 
3.7%
Other values (10) 13
15.9%
ValueCountFrequency (%)
0 19
23.2%
1 6
 
7.3%
2 4
 
4.9%
3 4
 
4.9%
4 5
 
6.1%
5 7
 
8.5%
6 2
 
2.4%
7 8
9.8%
8 8
9.8%
9 5
 
6.1%
ValueCountFrequency (%)
28 1
 
1.2%
25 1
 
1.2%
23 1
 
1.2%
19 2
2.4%
18 1
 
1.2%
16 1
 
1.2%
15 1
 
1.2%
14 1
 
1.2%
13 2
2.4%
10 3
3.7%

여자회원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)40.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.085366
Minimum0
Maximum69
Zeros2
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size870.0 B
2024-03-16T13:12:49.879030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12.05
Q119.25
median23
Q330
95-th percentile44.85
Maximum69
Range69
Interquartile range (IQR)10.75

Descriptive statistics

Standard deviation10.699257
Coefficient of variation (CV)0.4265139
Kurtosis3.6133583
Mean25.085366
Median Absolute Deviation (MAD)5
Skewness1.1761807
Sum2057
Variance114.4741
MonotonicityNot monotonic
2024-03-16T13:12:50.069481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
21 8
 
9.8%
23 6
 
7.3%
27 5
 
6.1%
15 4
 
4.9%
30 4
 
4.9%
25 4
 
4.9%
20 4
 
4.9%
18 4
 
4.9%
22 4
 
4.9%
28 4
 
4.9%
Other values (23) 35
42.7%
ValueCountFrequency (%)
0 2
2.4%
11 1
 
1.2%
12 2
2.4%
13 1
 
1.2%
14 1
 
1.2%
15 4
4.9%
16 3
3.7%
17 1
 
1.2%
18 4
4.9%
19 2
2.4%
ValueCountFrequency (%)
69 1
1.2%
54 1
1.2%
51 1
1.2%
50 1
1.2%
45 1
1.2%
42 1
1.2%
40 1
1.2%
38 1
1.2%
36 2
2.4%
33 2
2.4%

전화번호
Text

MISSING 

Distinct76
Distinct (%)100.0%
Missing6
Missing (%)7.3%
Memory size788.0 B
2024-03-16T13:12:50.340364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters912
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)100.0%

Sample

1st row053-554-0739
2nd row053-567-9772
3rd row053-551-8286
4th row053-553-9874
5th row053-556-8220
ValueCountFrequency (%)
053-565-5084 1
 
1.3%
053-555-0977 1
 
1.3%
053-564-7227 1
 
1.3%
053-522-0095 1
 
1.3%
053-564-6240 1
 
1.3%
053-559-1369 1
 
1.3%
053-561-0608 1
 
1.3%
053-554-2867 1
 
1.3%
053-562-1842 1
 
1.3%
053-551-9076 1
 
1.3%
Other values (66) 66
86.8%
2024-03-16T13:12:50.720883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 225
24.7%
- 152
16.7%
3 123
13.5%
0 109
12.0%
6 66
 
7.2%
2 47
 
5.2%
1 43
 
4.7%
7 43
 
4.7%
9 36
 
3.9%
8 34
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 760
83.3%
Dash Punctuation 152
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 225
29.6%
3 123
16.2%
0 109
14.3%
6 66
 
8.7%
2 47
 
6.2%
1 43
 
5.7%
7 43
 
5.7%
9 36
 
4.7%
8 34
 
4.5%
4 34
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 152
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 912
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 225
24.7%
- 152
16.7%
3 123
13.5%
0 109
12.0%
6 66
 
7.2%
2 47
 
5.2%
1 43
 
4.7%
7 43
 
4.7%
9 36
 
3.9%
8 34
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 912
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 225
24.7%
- 152
16.7%
3 123
13.5%
0 109
12.0%
6 66
 
7.2%
2 47
 
5.2%
1 43
 
4.7%
7 43
 
4.7%
9 36
 
3.9%
8 34
 
3.7%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
Minimum2024-03-06 00:00:00
Maximum2024-03-06 00:00:00
2024-03-16T13:12:50.879141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:51.029805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-16T13:12:45.702902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:40.622368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:41.551426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:42.553098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:43.567038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:44.823623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:45.835531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:40.758518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:41.795340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:42.744773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:44.163548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:44.987669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:46.021569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:40.900122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:41.988904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:42.934768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:44.353948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:45.137127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:46.169446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:41.054478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:42.127358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:43.070980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:44.482858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:45.266936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:46.341342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:41.242547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:42.300228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:43.232054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:44.596488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:45.391480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:46.561818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:41.384004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:42.425844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:43.403487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:44.703864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:12:45.525906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T13:12:51.173780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번경로당명칭소재지부지(제곱미터)건물(제곱미터)회원총계남자회원여자회원전화번호
연번1.0000.8841.0000.0000.5140.3880.3710.0001.000
경로당명칭0.8841.0001.0001.0000.9500.9830.7800.9761.000
소재지1.0001.0001.0001.0001.0001.0001.0001.0001.000
부지(제곱미터)0.0001.0001.0001.0000.8230.0000.3060.399NaN
건물(제곱미터)0.5140.9501.0000.8231.0000.3090.0460.1041.000
회원총계0.3880.9831.0000.0000.3091.0000.3830.8871.000
남자회원0.3710.7801.0000.3060.0460.3831.0000.6621.000
여자회원0.0000.9761.0000.3990.1040.8870.6621.0001.000
전화번호1.0001.0001.000NaN1.0001.0001.0001.0001.000
2024-03-16T13:12:51.622840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번부지(제곱미터)건물(제곱미터)회원총계남자회원여자회원
연번1.0000.1160.0510.0030.258-0.126
부지(제곱미터)0.1161.0000.6320.3440.0990.277
건물(제곱미터)0.0510.6321.0000.4840.2390.321
회원총계0.0030.3440.4841.0000.3170.742
남자회원0.2580.0990.2390.3171.000-0.278
여자회원-0.1260.2770.3210.742-0.2781.000

Missing values

2024-03-16T13:12:46.776092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:12:46.950479image/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

연번경로당명칭소재지부지(제곱미터)건물(제곱미터)회원총계남자회원여자회원전화번호기준일자
01내서경로당대구 서구 달구벌대로 365길 21-5125.558.1431031053-554-07392024-03-06
12시영내당(아)경로당대구광역시 서구 서대구로8길 15(내당동)119.0119.028721053-567-97722024-03-06
23홍실1차경로당대구광역시 서구 서대구로8길 49(내당동)90.090.021516053-551-82862024-03-06
34황성정경로당대구광역시 서구 통학로 46(내당동)137.74134.7428523053-553-98742024-03-06
45홍실2차경로당대구광역시 서구 통학로 39(내당동)154.11154.1130228053-556-82202024-03-06
56이편한세상경로당대구광역시 서구 달구벌대로361길 41(내당동,이편한세상)34920.0177.84231013<NA>2024-03-06
67장수경로당대구광역시 서구 큰장로9길 9-3(내당동)144.515112.034133053-572-81232024-03-06
78내당2동경로당대구광역시 서구 큰장로15길 14-2090.8448.0630426053-571-16372024-03-06
89내당경로당대구광역시 서구 평리로 408-13(내당동)216.0183.6840040053-565-04372024-03-06
910천일경로당대구광역시 서구 달구벌대로373길 2-24(내당동)165.0172.8416016053-566-30772024-03-06
연번경로당명칭소재지부지(제곱미터)건물(제곱미터)회원총계남자회원여자회원전화번호기준일자
7273중리시영(아)경로당대구광역시 서구 당산로 324(중리동)52.8952.8923419053-551-63862024-03-06
7374중리일송경로당대구광역시 서구 당산로53길 110-4(중리동)122.47119.825520053-565-32332024-03-06
7475중리상록경로당대구광역시 서구 국채보상로36길 16-2(중리동)196.3129.8124123053-554-26322024-03-06
7576중리롯데캐슬경로당대구광역시 서구 국채보상로34길 12(중리동)194.629194.629431627053-294-02212024-03-06
7677원대1,2가제1경로당대구광역시 서구 달서천로 405-3(원대동1가)268.9200.2828280053-354-86952024-03-06
7778원대1,2가제2경로당대구광역시 서구 달서천로86길 6-10(원대동1가)268.6131.845045053-357-85612024-03-06
7879원대3가제1경로당대구광역시 서구 고성로21길6(원대동3가)201.09122.8526818053-354-76652024-03-06
7980원대3가제2경로당대구광역시 서구 옥산로2길 7-13(원대동3가)132.078.9931625053-355-15772024-03-06
8081금류타운경로당대구광역시 서구 원대로13길 2(원대동2가)84.3984.3921714053-359-17692024-03-06
8182센트럴자이경로당대구광역시 서구 고성로 33(원대동3가)69796.4225.88311021<NA>2024-03-06