Overview

Dataset statistics

Number of variables10
Number of observations371
Missing cells113
Missing cells (%)3.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.2 KiB
Average record size in memory83.4 B

Variable types

Numeric3
Categorical1
Text5
DateTime1

Dataset

Description예천군 관내 마을회관 현황 자료(읍면, 마을명, 회관(경로당)명, 소재지주소, 건축년도, 규모, 사용인원, 전화번호, 기준일자)
Author경상북도 예천군
URLhttps://www.data.go.kr/data/15007497/fileData.do

Alerts

기준일자 has constant value ""Constant
연번 is highly overall correlated with 읍면High correlation
읍면 is highly overall correlated with 연번High correlation
전화번호 has 113 (30.5%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:13:54.796155
Analysis finished2023-12-12 15:13:56.738277
Duration1.94 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct371
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean186
Minimum1
Maximum371
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-13T00:13:56.812368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19.5
Q193.5
median186
Q3278.5
95-th percentile352.5
Maximum371
Range370
Interquartile range (IQR)185

Descriptive statistics

Standard deviation107.24272
Coefficient of variation (CV)0.57657374
Kurtosis-1.2
Mean186
Median Absolute Deviation (MAD)93
Skewness0
Sum69006
Variance11501
MonotonicityStrictly increasing
2023-12-13T00:13:56.995781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
246 1
 
0.3%
255 1
 
0.3%
254 1
 
0.3%
253 1
 
0.3%
252 1
 
0.3%
251 1
 
0.3%
250 1
 
0.3%
249 1
 
0.3%
248 1
 
0.3%
Other values (361) 361
97.3%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
371 1
0.3%
370 1
0.3%
369 1
0.3%
368 1
0.3%
367 1
0.3%
366 1
0.3%
365 1
0.3%
364 1
0.3%
363 1
0.3%
362 1
0.3%

읍면
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
예천읍
44 
호명면
41 
지보면
39 
풍양면
39 
감천면
35 
Other values (7)
173 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row예천읍
2nd row예천읍
3rd row예천읍
4th row예천읍
5th row예천읍

Common Values

ValueCountFrequency (%)
예천읍 44
11.9%
호명면 41
11.1%
지보면 39
10.5%
풍양면 39
10.5%
감천면 35
9.4%
유천면 33
8.9%
용문면 32
8.6%
보문면 29
7.8%
은풍면 25
6.7%
용궁면 22
5.9%
Other values (2) 32
8.6%

Length

2023-12-13T00:13:57.189646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
예천읍 44
11.9%
호명면 41
11.1%
지보면 39
10.5%
풍양면 39
10.5%
감천면 35
9.4%
유천면 33
8.9%
용문면 32
8.6%
보문면 29
7.8%
은풍면 25
6.7%
용궁면 22
5.9%
Other values (2) 32
8.6%

마을명
Text

Distinct267
Distinct (%)72.0%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-13T00:13:57.546144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length3.638814
Min length2

Characters and Unicode

Total characters1350
Distinct characters138
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique183 ?
Unique (%)49.3%

Sample

1st row노하리
2nd row노상리
3rd row백전1리
4th row백전1리
5th row백전2리
ValueCountFrequency (%)
가2리 5
 
1.3%
우곡1리 4
 
1.1%
산합2리 3
 
0.8%
어신2리 3
 
0.8%
신풍2리 3
 
0.8%
장산2리 3
 
0.8%
생천리 3
 
0.8%
풍신1리 3
 
0.8%
낙상2리 3
 
0.8%
독양1리 3
 
0.8%
Other values (257) 338
91.1%
2023-12-13T00:13:57.990805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 371
27.5%
2 115
 
8.5%
1 111
 
8.2%
산 40
 
3.0%
곡 38
 
2.8%
신 27
 
2.0%
3 16
 
1.2%
금 16
 
1.2%
천 15
 
1.1%
상 15
 
1.1%
Other values (128) 586
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1099
81.4%
Decimal Number 248
 
18.4%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 371
33.8%
산 40
 
3.6%
곡 38
 
3.5%
신 27
 
2.5%
금 16
 
1.5%
천 15
 
1.4%
상 15
 
1.4%
송 15
 
1.4%
본 15
 
1.4%
우 15
 
1.4%
Other values (120) 532
48.4%
Decimal Number
ValueCountFrequency (%)
2 115
46.4%
1 111
44.8%
3 16
 
6.5%
4 3
 
1.2%
8 1
 
0.4%
9 1
 
0.4%
0 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1099
81.4%
Common 251
 
18.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 371
33.8%
산 40
 
3.6%
곡 38
 
3.5%
신 27
 
2.5%
금 16
 
1.5%
천 15
 
1.4%
상 15
 
1.4%
송 15
 
1.4%
본 15
 
1.4%
우 15
 
1.4%
Other values (120) 532
48.4%
Common
ValueCountFrequency (%)
2 115
45.8%
1 111
44.2%
3 16
 
6.4%
, 3
 
1.2%
4 3
 
1.2%
8 1
 
0.4%
9 1
 
0.4%
0 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1099
81.4%
ASCII 251
 
18.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 371
33.8%
산 40
 
3.6%
곡 38
 
3.5%
신 27
 
2.5%
금 16
 
1.5%
천 15
 
1.4%
상 15
 
1.4%
송 15
 
1.4%
본 15
 
1.4%
우 15
 
1.4%
Other values (120) 532
48.4%
ASCII
ValueCountFrequency (%)
2 115
45.8%
1 111
44.2%
3 16
 
6.4%
, 3
 
1.2%
4 3
 
1.2%
8 1
 
0.4%
9 1
 
0.4%
0 1
 
0.4%

회관(경로당)명
Text

Distinct370
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-13T00:13:58.215703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length7.6091644
Min length5

Characters and Unicode

Total characters2823
Distinct characters225
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique369 ?
Unique (%)99.5%

Sample

1st row노하리경로당
2nd row노상리경로당
3rd row백전1(남)경로당
4th row백전1(여)경로당
5th row백전2리경로당
ValueCountFrequency (%)
사곡리경로당 2
 
0.5%
가1리경로당 1
 
0.3%
금남1리경로당 1
 
0.3%
읍부2리경로당 1
 
0.3%
읍부1리경로당 1
 
0.3%
용궁경로당 1
 
0.3%
연천1리경로당 1
 
0.3%
가2리(여)경로당 1
 
0.3%
가2리새경로당 1
 
0.3%
가2리토치경로당 1
 
0.3%
Other values (360) 360
97.0%
2023-12-13T00:13:58.598499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
당 377
 
13.4%
경 373
 
13.2%
로 368
 
13.0%
리 319
 
11.3%
2 101
 
3.6%
1 93
 
3.3%
) 44
 
1.6%
( 44
 
1.6%
산 36
 
1.3%
신 33
 
1.2%
Other values (215) 1035
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2526
89.5%
Decimal Number 208
 
7.4%
Close Punctuation 44
 
1.6%
Open Punctuation 44
 
1.6%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 377
14.9%
경 373
14.8%
로 368
 
14.6%
리 319
 
12.6%
산 36
 
1.4%
신 33
 
1.3%
곡 28
 
1.1%
마 24
 
1.0%
지 19
 
0.8%
천 19
 
0.8%
Other values (209) 930
36.8%
Decimal Number
ValueCountFrequency (%)
2 101
48.6%
1 93
44.7%
3 14
 
6.7%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2526
89.5%
Common 297
 
10.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 377
14.9%
경 373
14.8%
로 368
 
14.6%
리 319
 
12.6%
산 36
 
1.4%
신 33
 
1.3%
곡 28
 
1.1%
마 24
 
1.0%
지 19
 
0.8%
천 19
 
0.8%
Other values (209) 930
36.8%
Common
ValueCountFrequency (%)
2 101
34.0%
1 93
31.3%
) 44
14.8%
( 44
14.8%
3 14
 
4.7%
@ 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2526
89.5%
ASCII 297
 
10.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
당 377
14.9%
경 373
14.8%
로 368
 
14.6%
리 319
 
12.6%
산 36
 
1.4%
신 33
 
1.3%
곡 28
 
1.1%
마 24
 
1.0%
지 19
 
0.8%
천 19
 
0.8%
Other values (209) 930
36.8%
ASCII
ValueCountFrequency (%)
2 101
34.0%
1 93
31.3%
) 44
14.8%
( 44
14.8%
3 14
 
4.7%
@ 1
 
0.3%

소재지 주소
Text

Distinct370
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-13T00:13:58.978890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length33
Mean length20.638814
Min length18

Characters and Unicode

Total characters7657
Distinct characters220
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

Unique369 ?
Unique (%)99.5%

Sample

1st row경상북도 예천군 예천읍 맛고을길 61
2nd row경상북도 예천군 예천읍 중앙로 6
3rd row경상북도 예천군 예천읍 군청길 74
4th row경상북도 예천군 예천읍 군청길 74
5th row경상북도 예천군 예천읍 밤나무골길 22
ValueCountFrequency (%)
경상북도 371
19.9%
예천군 371
19.9%
예천읍 44
 
2.4%
호명면 41
 
2.2%
풍양면 39
 
2.1%
지보면 39
 
2.1%
감천면 35
 
1.9%
유천면 33
 
1.8%
용문면 32
 
1.7%
보문면 29
 
1.6%
Other values (558) 832
44.6%
2023-12-13T00:13:59.425577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1495
19.5%
천 499
 
6.5%
예 419
 
5.5%
상 384
 
5.0%
도 381
 
5.0%
경 376
 
4.9%
군 374
 
4.9%
북 372
 
4.9%
면 327
 
4.3%
길 309
 
4.0%
Other values (210) 2721
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4955
64.7%
Space Separator 1495
 
19.5%
Decimal Number 1092
 
14.3%
Dash Punctuation 107
 
1.4%
Other Punctuation 6
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 499
 
10.1%
예 419
 
8.5%
상 384
 
7.7%
도 381
 
7.7%
경 376
 
7.6%
군 374
 
7.5%
북 372
 
7.5%
면 327
 
6.6%
길 309
 
6.2%
풍 87
 
1.8%
Other values (195) 1427
28.8%
Decimal Number
ValueCountFrequency (%)
1 255
23.4%
2 150
13.7%
3 116
10.6%
4 114
10.4%
6 93
 
8.5%
7 89
 
8.2%
5 88
 
8.1%
9 67
 
6.1%
8 67
 
6.1%
0 53
 
4.9%
Space Separator
ValueCountFrequency (%)
1495
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 107
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4955
64.7%
Common 2702
35.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 499
 
10.1%
예 419
 
8.5%
상 384
 
7.7%
도 381
 
7.7%
경 376
 
7.6%
군 374
 
7.5%
북 372
 
7.5%
면 327
 
6.6%
길 309
 
6.2%
풍 87
 
1.8%
Other values (195) 1427
28.8%
Common
ValueCountFrequency (%)
1495
55.3%
1 255
 
9.4%
2 150
 
5.6%
3 116
 
4.3%
4 114
 
4.2%
- 107
 
4.0%
6 93
 
3.4%
7 89
 
3.3%
5 88
 
3.3%
9 67
 
2.5%
Other values (5) 128
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4955
64.7%
ASCII 2702
35.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1495
55.3%
1 255
 
9.4%
2 150
 
5.6%
3 116
 
4.3%
4 114
 
4.2%
- 107
 
4.0%
6 93
 
3.4%
7 89
 
3.3%
5 88
 
3.3%
9 67
 
2.5%
Other values (5) 128
 
4.7%
Hangul
ValueCountFrequency (%)
천 499
 
10.1%
예 419
 
8.5%
상 384
 
7.7%
도 381
 
7.7%
경 376
 
7.6%
군 374
 
7.5%
북 372
 
7.5%
면 327
 
6.6%
길 309
 
6.2%
풍 87
 
1.8%
Other values (195) 1427
28.8%

건축년도
Real number (ℝ)

Distinct43
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2003.5229
Minimum1970
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-13T00:13:59.547365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1970
5-th percentile1981.5
Q12000
median2005
Q32008
95-th percentile2018
Maximum2022
Range52
Interquartile range (IQR)8

Descriptive statistics

Standard deviation8.9213614
Coefficient of variation (CV)0.0044528372
Kurtosis2.9975126
Mean2003.5229
Median Absolute Deviation (MAD)4
Skewness-1.1919637
Sum743307
Variance79.59069
MonotonicityNot monotonic
2023-12-13T00:13:59.668528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
2005 32
 
8.6%
2006 30
 
8.1%
2008 29
 
7.8%
2000 24
 
6.5%
2002 24
 
6.5%
2001 23
 
6.2%
2004 20
 
5.4%
2007 20
 
5.4%
2003 19
 
5.1%
2009 17
 
4.6%
Other values (33) 133
35.8%
ValueCountFrequency (%)
1970 2
0.5%
1973 1
 
0.3%
1975 4
1.1%
1976 2
0.5%
1977 3
0.8%
1978 3
0.8%
1979 2
0.5%
1980 1
 
0.3%
1981 1
 
0.3%
1982 2
0.5%
ValueCountFrequency (%)
2022 3
 
0.8%
2021 2
 
0.5%
2020 1
 
0.3%
2019 6
1.6%
2018 13
3.5%
2017 4
 
1.1%
2016 2
 
0.5%
2015 3
 
0.8%
2014 5
 
1.3%
2013 4
 
1.1%

규모(면적)
Text

Distinct333
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-13T00:14:00.071462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.690027
Min length2

Characters and Unicode

Total characters1740
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique302 ?
Unique (%)81.4%

Sample

1st row86.78
2nd row99.1
3rd row82.97
4th row89.25
5th row164.95
ValueCountFrequency (%)
82.5 3
 
0.8%
64.8 3
 
0.8%
83.96 3
 
0.8%
66.01 3
 
0.8%
72.9 3
 
0.8%
99.1 3
 
0.8%
90.2 3
 
0.8%
75.24 2
 
0.5%
81.17 2
 
0.5%
75.6 2
 
0.5%
Other values (323) 344
92.7%
2023-12-13T00:14:00.604891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 334
19.2%
9 180
10.3%
1 179
10.3%
8 173
9.9%
6 165
9.5%
2 149
8.6%
7 141
8.1%
5 125
 
7.2%
4 98
 
5.6%
0 97
 
5.6%
Other values (8) 99
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1399
80.4%
Other Punctuation 336
 
19.3%
Uppercase Letter 5
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 180
12.9%
1 179
12.8%
8 173
12.4%
6 165
11.8%
2 149
10.7%
7 141
10.1%
5 125
8.9%
4 98
7.0%
0 97
6.9%
3 92
6.6%
Uppercase Letter
ValueCountFrequency (%)
V 1
20.0%
A 1
20.0%
L 1
20.0%
U 1
20.0%
E 1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 334
99.4%
# 1
 
0.3%
! 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1735
99.7%
Latin 5
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
. 334
19.3%
9 180
10.4%
1 179
10.3%
8 173
10.0%
6 165
9.5%
2 149
8.6%
7 141
8.1%
5 125
 
7.2%
4 98
 
5.6%
0 97
 
5.6%
Other values (3) 94
 
5.4%
Latin
ValueCountFrequency (%)
V 1
20.0%
A 1
20.0%
L 1
20.0%
U 1
20.0%
E 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1740
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 334
19.2%
9 180
10.3%
1 179
10.3%
8 173
9.9%
6 165
9.5%
2 149
8.6%
7 141
8.1%
5 125
 
7.2%
4 98
 
5.6%
0 97
 
5.6%
Other values (8) 99
 
5.7%

사용인원
Real number (ℝ)

Distinct76
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.892183
Minimum0
Maximum143
Zeros3
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-13T00:14:00.747562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12
Q120
median29
Q338
95-th percentile66
Maximum143
Range143
Interquartile range (IQR)18

Descriptive statistics

Standard deviation18.787121
Coefficient of variation (CV)0.58908231
Kurtosis7.7085776
Mean31.892183
Median Absolute Deviation (MAD)9
Skewness2.1448255
Sum11832
Variance352.95591
MonotonicityNot monotonic
2023-12-13T00:14:00.909095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 24
 
6.5%
31 22
 
5.9%
32 15
 
4.0%
19 14
 
3.8%
16 13
 
3.5%
17 12
 
3.2%
30 11
 
3.0%
18 11
 
3.0%
34 10
 
2.7%
22 10
 
2.7%
Other values (66) 229
61.7%
ValueCountFrequency (%)
0 3
0.8%
6 1
 
0.3%
7 2
 
0.5%
9 3
0.8%
10 4
1.1%
11 5
1.3%
12 4
1.1%
13 6
1.6%
14 6
1.6%
15 7
1.9%
ValueCountFrequency (%)
143 1
0.3%
137 1
0.3%
127 1
0.3%
102 1
0.3%
93 1
0.3%
91 1
0.3%
87 1
0.3%
84 1
0.3%
83 1
0.3%
81 1
0.3%

전화번호
Text

MISSING 

Distinct257
Distinct (%)99.6%
Missing113
Missing (%)30.5%
Memory size3.0 KiB
2023-12-13T00:14:01.166565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length12.089147
Min length12

Characters and Unicode

Total characters3119
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique256 ?
Unique (%)99.2%

Sample

1st row054-654-3572
2nd row054-653-4840
3rd row054-654-8825
4th row054-652-5600
5th row054-653-5953
ValueCountFrequency (%)
054-652-2381 2
 
0.8%
054-652-9780 1
 
0.4%
054-655-4403 1
 
0.4%
054-652-9232 1
 
0.4%
054-652-2258 1
 
0.4%
054-653-1125 1
 
0.4%
054-652-1337 1
 
0.4%
054-652-9149 1
 
0.4%
054-652-4668 1
 
0.4%
054-652-4445 1
 
0.4%
Other values (247) 247
95.7%
2023-12-13T00:14:01.527802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 694
22.3%
- 517
16.6%
4 391
12.5%
0 378
12.1%
6 342
11.0%
3 196
 
6.3%
2 192
 
6.2%
8 110
 
3.5%
1 110
 
3.5%
7 88
 
2.8%
Other values (2) 101
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2584
82.8%
Dash Punctuation 517
 
16.6%
Space Separator 18
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 694
26.9%
4 391
15.1%
0 378
14.6%
6 342
13.2%
3 196
 
7.6%
2 192
 
7.4%
8 110
 
4.3%
1 110
 
4.3%
7 88
 
3.4%
9 83
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 517
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3119
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 694
22.3%
- 517
16.6%
4 391
12.5%
0 378
12.1%
6 342
11.0%
3 196
 
6.3%
2 192
 
6.2%
8 110
 
3.5%
1 110
 
3.5%
7 88
 
2.8%
Other values (2) 101
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3119
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 694
22.3%
- 517
16.6%
4 391
12.5%
0 378
12.1%
6 342
11.0%
3 196
 
6.3%
2 192
 
6.2%
8 110
 
3.5%
1 110
 
3.5%
7 88
 
2.8%
Other values (2) 101
 
3.2%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
Minimum2022-08-26 00:00:00
Maximum2022-08-26 00:00:00
2023-12-13T00:14:01.660133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:14:01.751442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T00:13:55.876902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:55.285229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:55.579783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:55.972762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:55.375111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:55.678983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:56.066365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:55.485254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:13:55.781525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:14:01.823992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면건축년도사용인원
연번1.0000.9740.3720.149
읍면0.9741.0000.2830.212
건축년도0.3720.2831.0000.300
사용인원0.1490.2120.3001.000
2023-12-13T00:14:01.931560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번건축년도사용인원읍면
연번1.0000.047-0.1250.900
건축년도0.0471.000-0.2400.134
사용인원-0.125-0.2401.0000.089
읍면0.9000.1340.0891.000

Missing values

2023-12-13T00:13:56.190454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:13:56.682637image/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

연번읍면마을명회관(경로당)명소재지 주소건축년도규모(면적)사용인원전화번호기준일자
01예천읍노하리노하리경로당경상북도 예천군 예천읍 맛고을길 61201886.7852<NA>2022-08-26
12예천읍노상리노상리경로당경상북도 예천군 예천읍 중앙로 6200199.168054-654-35722022-08-26
23예천읍백전1리백전1(남)경로당경상북도 예천군 예천읍 군청길 74197582.9754054-653-48402022-08-26
34예천읍백전1리백전1(여)경로당경상북도 예천군 예천읍 군청길 74197789.2554054-654-88252022-08-26
45예천읍백전2리백전2리경로당경상북도 예천군 예천읍 밤나무골길 222000164.9530054-652-56002022-08-26
56예천읍동본1리동본1리경로당경상북도 예천군 예천읍 상설시장2길 21, 1층200998.7102054-653-59532022-08-26
67예천읍동본2리동본2리경로당경상북도 예천군 예천읍 보문로 42-7200168.9936054-653-98682022-08-26
78예천읍남본1리남본1리경로당경상북도 예천군 예천읍 맛고을길 142018110.89127<NA>2022-08-26
89예천읍남본2리남본2리경로당경상북도 예천군 예천읍 남부초등길 8-2200999.151<NA>2022-08-26
910예천읍남본2리남산경로당경상북도 예천군 예천읍 남산공원길 9-1201069.232<NA>2022-08-26
연번읍면마을명회관(경로당)명소재지 주소건축년도규모(면적)사용인원전화번호기준일자
361362풍양면공덕3리공덕3리(봉림)경로당경상북도 예천군 풍양면 삼강로 2262018102.830054-655-03382022-08-26
362363풍양면낙상1리낙상1리(삼탄)경로당경상북도 예천군 풍양면 삼탄길 141200483.9638<NA>2022-08-26
363364풍양면낙상2리낙상2리경로당경상북도 예천군 풍양면 낙상1길 49-92008102.36137054-653-88472022-08-26
364365풍양면낙상2리낙상2리(할머니)경로당경상북도 예천군 풍양면 낙상2길 49200316.5219054-653-98652022-08-26
365366풍양면낙상3리낙상3리(새터)경로당경상북도 예천군 풍양면 상풍로 1348-4200185.6230<NA>2022-08-26
366367풍양면낙상3리낙상3리(들마)경로당경상북도 예천군 풍양면 상풍로 1234-8200366.2824<NA>2022-08-26
367368풍양면와룡1리와룡1리(모라물)경로당경상북도 예천군 풍양면 영풍로 190-21201413330054-653-88572022-08-26
368369풍양면와룡2리와룡2리(서동)경로당경상북도 예천군 풍양면 와룡길 63-6200382.2441<NA>2022-08-26
369370풍양면효갈1리효갈1리(갈밭)경로당경상북도 예천군 풍양면 덕암로 1118200386.2834054-653-02332022-08-26
370371풍양면효갈2리효갈2리(효제)경로당경상북도 예천군 풍양면 덕암로 126920018622<NA>2022-08-26