Overview

Dataset statistics

Number of variables10
Number of observations195
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.7 KiB
Average record size in memory82.7 B

Variable types

Numeric2
Categorical1
Text7

Dataset

Description경상남도 하동군에 있는 공동묘지 현황 (연번, 읍면, 공동묘지명, 위치, 설치일자, 관리주체, 면적, 기수 등)의 정보를 제공하고 있습니다.
Author경상남도 하동군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15086554

Alerts

연번 is highly overall correlated with 읍면High correlation
읍면 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:47:52.054592
Analysis finished2023-12-10 23:47:53.801953
Duration1.75 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct195
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98
Minimum1
Maximum195
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T08:47:53.876731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.7
Q149.5
median98
Q3146.5
95-th percentile185.3
Maximum195
Range194
Interquartile range (IQR)97

Descriptive statistics

Standard deviation56.435804
Coefficient of variation (CV)0.57587555
Kurtosis-1.2
Mean98
Median Absolute Deviation (MAD)49
Skewness0
Sum19110
Variance3185
MonotonicityStrictly increasing
2023-12-11T08:47:54.070692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
124 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
Other values (185) 185
94.9%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
195 1
0.5%
194 1
0.5%
193 1
0.5%
192 1
0.5%
191 1
0.5%
190 1
0.5%
189 1
0.5%
188 1
0.5%
187 1
0.5%
186 1
0.5%

읍면
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
횡천면
26 
악양면
25 
적량면
21 
옥종면
21 
화개면
17 
Other values (8)
85 

Length

Max length5
Median length3
Mean length3.1282051
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
횡천면 26
13.3%
악양면 25
12.8%
적량면 21
10.8%
옥종면 21
10.8%
화개면 17
8.7%
금남면 16
8.2%
진교면 15
7.7%
고전면 14
7.2%
북천면 10
 
5.1%
청암면 9
 
4.6%
Other values (3) 21
10.8%

Length

2023-12-11T08:47:54.252117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
횡천면 26
13.3%
악양면 25
12.8%
적량면 21
10.8%
옥종면 21
10.8%
화개면 17
8.7%
금남면 16
8.2%
진교면 15
7.7%
고전면 14
7.2%
북천면 10
 
5.1%
청암면 9
 
4.6%
Other values (3) 21
10.8%

공동묘지명
Text

Distinct187
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T08:47:54.492304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length6
Mean length6.8666667
Min length6

Characters and Unicode

Total characters1339
Distinct characters133
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

Unique180 ?
Unique (%)92.3%

Sample

1st row읍내공동묘지
2nd row연화공동묘지
3rd row흥룡공동묘지
4th row화심공동묘지
5th row두곡공동묘지
ValueCountFrequency (%)
공동묘지 8
 
3.9%
신촌공동묘지 3
 
1.5%
궁항마을공동묘지 2
 
1.0%
공동묘지(1 2
 
1.0%
중기공동묘지 2
 
1.0%
유평 2
 
1.0%
오율마을공동묘지 2
 
1.0%
위태마을공동묘지 2
 
1.0%
대덕공동묘지 2
 
1.0%
상촌공동묘지 2
 
1.0%
Other values (179) 179
86.9%
2023-12-11T08:47:54.898286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 205
15.3%
지 197
14.7%
공 196
14.6%
묘 195
14.6%
30
 
2.2%
( 24
 
1.8%
) 24
 
1.8%
마 23
 
1.7%
을 21
 
1.6%
상 21
 
1.6%
Other values (123) 403
30.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1238
92.5%
Space Separator 30
 
2.2%
Open Punctuation 24
 
1.8%
Close Punctuation 24
 
1.8%
Decimal Number 23
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 205
16.6%
지 197
15.9%
공 196
15.8%
묘 195
15.8%
마 23
 
1.9%
을 21
 
1.7%
상 21
 
1.7%
하 14
 
1.1%
신 14
 
1.1%
대 12
 
1.0%
Other values (118) 340
27.5%
Decimal Number
ValueCountFrequency (%)
1 12
52.2%
2 11
47.8%
Space Separator
ValueCountFrequency (%)
30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1238
92.5%
Common 101
 
7.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 205
16.6%
지 197
15.9%
공 196
15.8%
묘 195
15.8%
마 23
 
1.9%
을 21
 
1.7%
상 21
 
1.7%
하 14
 
1.1%
신 14
 
1.1%
대 12
 
1.0%
Other values (118) 340
27.5%
Common
ValueCountFrequency (%)
30
29.7%
( 24
23.8%
) 24
23.8%
1 12
 
11.9%
2 11
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1238
92.5%
ASCII 101
 
7.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 205
16.6%
지 197
15.9%
공 196
15.8%
묘 195
15.8%
마 23
 
1.9%
을 21
 
1.7%
상 21
 
1.7%
하 14
 
1.1%
신 14
 
1.1%
대 12
 
1.0%
Other values (118) 340
27.5%
ASCII
ValueCountFrequency (%)
30
29.7%
( 24
23.8%
) 24
23.8%
1 12
 
11.9%
2 11
 
10.9%

위치
Text

Distinct194
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T08:47:55.232631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length21
Mean length9.7282051
Min length5

Characters and Unicode

Total characters1897
Distinct characters119
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

Unique193 ?
Unique (%)99.0%

Sample

1st row읍내리 349-11
2nd row읍내리 산7-3
3rd row흥룡리 산3
4th row화심리 산36
5th row두곡리 산51
ValueCountFrequency (%)
산 35
 
7.4%
적량면 21
 
4.5%
진교면 15
 
3.2%
청암면 9
 
1.9%
동리 6
 
1.3%
양보면 6
 
1.3%
신월리 5
 
1.1%
남산리 5
 
1.1%
궁항리 5
 
1.1%
산55 5
 
1.1%
Other values (262) 358
76.2%
2023-12-11T08:47:55.706980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
294
 
15.5%
산 202
 
10.6%
리 195
 
10.3%
1 106
 
5.6%
2 65
 
3.4%
8 55
 
2.9%
지 54
 
2.8%
5 53
 
2.8%
7 51
 
2.7%
면 51
 
2.7%
Other values (109) 771
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1023
53.9%
Decimal Number 526
27.7%
Space Separator 294
 
15.5%
Dash Punctuation 29
 
1.5%
Other Punctuation 17
 
0.9%
Close Punctuation 4
 
0.2%
Open Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 202
19.7%
리 195
19.1%
지 54
 
5.3%
면 51
 
5.0%
번 49
 
4.8%
량 23
 
2.2%
적 21
 
2.1%
진 19
 
1.9%
교 16
 
1.6%
암 15
 
1.5%
Other values (94) 378
37.0%
Decimal Number
ValueCountFrequency (%)
1 106
20.2%
2 65
12.4%
8 55
10.5%
5 53
10.1%
7 51
9.7%
3 49
9.3%
6 42
 
8.0%
4 40
 
7.6%
9 36
 
6.8%
0 29
 
5.5%
Space Separator
ValueCountFrequency (%)
294
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Other Punctuation
ValueCountFrequency (%)
, 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1023
53.9%
Common 874
46.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 202
19.7%
리 195
19.1%
지 54
 
5.3%
면 51
 
5.0%
번 49
 
4.8%
량 23
 
2.2%
적 21
 
2.1%
진 19
 
1.9%
교 16
 
1.6%
암 15
 
1.5%
Other values (94) 378
37.0%
Common
ValueCountFrequency (%)
294
33.6%
1 106
 
12.1%
2 65
 
7.4%
8 55
 
6.3%
5 53
 
6.1%
7 51
 
5.8%
3 49
 
5.6%
6 42
 
4.8%
4 40
 
4.6%
9 36
 
4.1%
Other values (5) 83
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1023
53.9%
ASCII 874
46.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
294
33.6%
1 106
 
12.1%
2 65
 
7.4%
8 55
 
6.3%
5 53
 
6.1%
7 51
 
5.8%
3 49
 
5.6%
6 42
 
4.8%
4 40
 
4.6%
9 36
 
4.1%
Other values (5) 83
 
9.5%
Hangul
ValueCountFrequency (%)
산 202
19.7%
리 195
19.1%
지 54
 
5.3%
면 51
 
5.0%
번 49
 
4.8%
량 23
 
2.2%
적 21
 
2.1%
진 19
 
1.9%
교 16
 
1.6%
암 15
 
1.5%
Other values (94) 378
37.0%

설치일자
Text

Distinct56
Distinct (%)28.7%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T08:47:55.920488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length10
Mean length8.8
Min length4

Characters and Unicode

Total characters1716
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)20.0%

Sample

1st row1962-05-31
2nd row1962-05-31
3rd row1961-09-01
4th row1961-09-01
5th row1979-06-27
ValueCountFrequency (%)
1979-06-22 46
23.6%
1910 25
12.8%
1921-08-20 24
12.3%
1979 16
 
8.2%
1962-11-08 9
 
4.6%
1962-05-31 8
 
4.1%
1966-09-01 6
 
3.1%
1919-04-22 3
 
1.5%
1913-05-22 3
 
1.5%
1989-04-01 2
 
1.0%
Other values (46) 53
27.2%
2023-12-11T08:47:56.305691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 337
19.6%
- 306
17.8%
9 288
16.8%
0 237
13.8%
2 233
13.6%
6 94
 
5.5%
7 84
 
4.9%
8 54
 
3.1%
3 34
 
2.0%
5 27
 
1.6%
Other values (3) 22
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1404
81.8%
Dash Punctuation 306
 
17.8%
Open Punctuation 3
 
0.2%
Close Punctuation 3
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 337
24.0%
9 288
20.5%
0 237
16.9%
2 233
16.6%
6 94
 
6.7%
7 84
 
6.0%
8 54
 
3.8%
3 34
 
2.4%
5 27
 
1.9%
4 16
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 306
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1716
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 337
19.6%
- 306
17.8%
9 288
16.8%
0 237
13.8%
2 233
13.6%
6 94
 
5.5%
7 84
 
4.9%
8 54
 
3.1%
3 34
 
2.0%
5 27
 
1.6%
Other values (3) 22
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1716
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 337
19.6%
- 306
17.8%
9 288
16.8%
0 237
13.8%
2 233
13.6%
6 94
 
5.5%
7 84
 
4.9%
8 54
 
3.1%
3 34
 
2.0%
5 27
 
1.6%
Other values (3) 22
 
1.3%

관리주체
Text

Distinct172
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T08:47:56.597259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length5
Mean length5.6153846
Min length4

Characters and Unicode

Total characters1095
Distinct characters137
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique155 ?
Unique (%)79.5%

Sample

1st row연화마을회
2nd row연산마을회
3rd row흥룡마을회
4th row화심마을회
5th row두곡마을회
ValueCountFrequency (%)
여의마을회 4
 
2.0%
공동 4
 
2.0%
상촌마을회 3
 
1.5%
원곡마을회 3
 
1.5%
횡보마을회 3
 
1.5%
명천마을회 3
 
1.5%
신촌마을회 3
 
1.5%
궁항마을회 3
 
1.5%
마을회 3
 
1.5%
유평마을회 2
 
1.0%
Other values (159) 173
84.8%
2023-12-11T08:47:57.072554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 194
17.7%
마 193
17.6%
을 191
17.4%
45
 
4.1%
신 18
 
1.6%
동 15
 
1.4%
　 13
 
1.2%
대 12
 
1.1%
상 12
 
1.1%
촌 12
 
1.1%
Other values (127) 390
35.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1025
93.6%
Space Separator 58
 
5.3%
Other Punctuation 12
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 194
18.9%
마 193
18.8%
을 191
18.6%
신 18
 
1.8%
동 15
 
1.5%
대 12
 
1.2%
상 12
 
1.2%
촌 12
 
1.2%
정 12
 
1.2%
평 11
 
1.1%
Other values (124) 355
34.6%
Space Separator
ValueCountFrequency (%)
45
77.6%
　 13
 
22.4%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1025
93.6%
Common 70
 
6.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 194
18.9%
마 193
18.8%
을 191
18.6%
신 18
 
1.8%
동 15
 
1.5%
대 12
 
1.2%
상 12
 
1.2%
촌 12
 
1.2%
정 12
 
1.2%
평 11
 
1.1%
Other values (124) 355
34.6%
Common
ValueCountFrequency (%)
45
64.3%
　 13
 
18.6%
, 12
 
17.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1025
93.6%
ASCII 57
 
5.2%
None 13
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 194
18.9%
마 193
18.8%
을 191
18.6%
신 18
 
1.8%
동 15
 
1.5%
대 12
 
1.2%
상 12
 
1.2%
촌 12
 
1.2%
정 12
 
1.2%
평 11
 
1.1%
Other values (124) 355
34.6%
ASCII
ValueCountFrequency (%)
45
78.9%
, 12
 
21.1%
None
ValueCountFrequency (%)
　 13
100.0%

면적(제곱미터)
Real number (ℝ)

Distinct184
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6476.0308
Minimum157
Maximum68331
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T08:47:57.223740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum157
5-th percentile885.8
Q11983
median4324
Q38149
95-th percentile18693.4
Maximum68331
Range68174
Interquartile range (IQR)6166

Descriptive statistics

Standard deviation7917.5379
Coefficient of variation (CV)1.2225912
Kurtosis25.400235
Mean6476.0308
Median Absolute Deviation (MAD)2592
Skewness4.2352421
Sum1262826
Variance62687407
MonotonicityNot monotonic
2023-12-11T08:47:57.345951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1983 3
 
1.5%
8172 2
 
1.0%
1838 2
 
1.0%
5000 2
 
1.0%
979 2
 
1.0%
5554 2
 
1.0%
1650 2
 
1.0%
1732 2
 
1.0%
3888 2
 
1.0%
1944 2
 
1.0%
Other values (174) 174
89.2%
ValueCountFrequency (%)
157 1
0.5%
377 1
0.5%
549 1
0.5%
663 1
0.5%
674 1
0.5%
700 1
0.5%
715 1
0.5%
776 1
0.5%
793 1
0.5%
869 1
0.5%
ValueCountFrequency (%)
68331 1
0.5%
52701 1
0.5%
37884 1
0.5%
29752 1
0.5%
28760 1
0.5%
21967 1
0.5%
20727 1
0.5%
19815 1
0.5%
19023 1
0.5%
19007 1
0.5%

만장기수
Text

Distinct90
Distinct (%)46.2%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T08:47:57.668915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.7897436
Min length1

Characters and Unicode

Total characters544
Distinct characters12
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

Unique64 ?
Unique (%)32.8%

Sample

1st row1867
2nd row4508
3rd row1102
4th row1628
5th row2104
ValueCountFrequency (%)
300 14
 
7.2%
200 14
 
7.2%
50 14
 
7.2%
100 10
 
5.1%
70 9
 
4.6%
250 8
 
4.1%
150 6
 
3.1%
120 6
 
3.1%
500 6
 
3.1%
40 5
 
2.6%
Other values (80) 103
52.8%
2023-12-11T08:47:58.068137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 196
36.0%
2 72
 
13.2%
5 64
 
11.8%
1 61
 
11.2%
3 41
 
7.5%
4 30
 
5.5%
7 26
 
4.8%
8 20
 
3.7%
6 19
 
3.5%
9 13
 
2.4%
Other values (2) 2
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 542
99.6%
Other Letter 2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 196
36.2%
2 72
 
13.3%
5 64
 
11.8%
1 61
 
11.3%
3 41
 
7.6%
4 30
 
5.5%
7 26
 
4.8%
8 20
 
3.7%
6 19
 
3.5%
9 13
 
2.4%
Other Letter
ValueCountFrequency (%)
미 1
50.0%
상 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 542
99.6%
Hangul 2
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 196
36.2%
2 72
 
13.3%
5 64
 
11.8%
1 61
 
11.3%
3 41
 
7.6%
4 30
 
5.5%
7 26
 
4.8%
8 20
 
3.7%
6 19
 
3.5%
9 13
 
2.4%
Hangul
ValueCountFrequency (%)
미 1
50.0%
상 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 542
99.6%
Hangul 2
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 196
36.2%
2 72
 
13.3%
5 64
 
11.8%
1 61
 
11.3%
3 41
 
7.6%
4 30
 
5.5%
7 26
 
4.8%
8 20
 
3.7%
6 19
 
3.5%
9 13
 
2.4%
Hangul
ValueCountFrequency (%)
미 1
50.0%
상 1
50.0%

안치기수
Text

Distinct129
Distinct (%)66.2%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T08:47:58.361270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.574359
Min length1

Characters and Unicode

Total characters502
Distinct characters12
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

Unique86 ?
Unique (%)44.1%

Sample

1st row1801
2nd row4290
3rd row1030
4th row1580
5th row1947
ValueCountFrequency (%)
200 6
 
3.1%
31 5
 
2.6%
50 5
 
2.6%
55 4
 
2.1%
106 4
 
2.1%
300 3
 
1.5%
21 3
 
1.5%
150 3
 
1.5%
73 3
 
1.5%
40 3
 
1.5%
Other values (119) 156
80.0%
2023-12-11T08:47:58.744150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 105
20.9%
0 81
16.1%
2 78
15.5%
3 61
12.2%
5 54
10.8%
6 32
 
6.4%
4 26
 
5.2%
7 22
 
4.4%
8 21
 
4.2%
9 20
 
4.0%
Other values (2) 2
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 500
99.6%
Other Letter 2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 105
21.0%
0 81
16.2%
2 78
15.6%
3 61
12.2%
5 54
10.8%
6 32
 
6.4%
4 26
 
5.2%
7 22
 
4.4%
8 21
 
4.2%
9 20
 
4.0%
Other Letter
ValueCountFrequency (%)
미 1
50.0%
상 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 500
99.6%
Hangul 2
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 105
21.0%
0 81
16.2%
2 78
15.6%
3 61
12.2%
5 54
10.8%
6 32
 
6.4%
4 26
 
5.2%
7 22
 
4.4%
8 21
 
4.2%
9 20
 
4.0%
Hangul
ValueCountFrequency (%)
미 1
50.0%
상 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 500
99.6%
Hangul 2
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 105
21.0%
0 81
16.2%
2 78
15.6%
3 61
12.2%
5 54
10.8%
6 32
 
6.4%
4 26
 
5.2%
7 22
 
4.4%
8 21
 
4.2%
9 20
 
4.0%
Hangul
ValueCountFrequency (%)
미 1
50.0%
상 1
50.0%

매장가능기수
Text

Distinct109
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-11T08:47:58.976289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.0564103
Min length1

Characters and Unicode

Total characters401
Distinct characters13
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

Unique76 ?
Unique (%)39.0%

Sample

1st row66
2nd row218
3rd row72
4th row48
5th row157
ValueCountFrequency (%)
0 29
 
14.9%
9 6
 
3.1%
19 6
 
3.1%
50 5
 
2.6%
35 4
 
2.1%
2 4
 
2.1%
49 4
 
2.1%
4 4
 
2.1%
29 3
 
1.5%
18 3
 
1.5%
Other values (98) 127
65.1%
2023-12-11T08:47:59.353977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 69
17.2%
0 67
16.7%
9 41
10.2%
2 38
9.5%
4 36
9.0%
8 36
9.0%
5 31
7.7%
3 31
7.7%
7 30
7.5%
6 17
 
4.2%
Other values (3) 5
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 396
98.8%
Dash Punctuation 3
 
0.7%
Other Letter 2
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 69
17.4%
0 67
16.9%
9 41
10.4%
2 38
9.6%
4 36
9.1%
8 36
9.1%
5 31
7.8%
3 31
7.8%
7 30
7.6%
6 17
 
4.3%
Other Letter
ValueCountFrequency (%)
미 1
50.0%
상 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 399
99.5%
Hangul 2
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 69
17.3%
0 67
16.8%
9 41
10.3%
2 38
9.5%
4 36
9.0%
8 36
9.0%
5 31
7.8%
3 31
7.8%
7 30
7.5%
6 17
 
4.3%
Hangul
ValueCountFrequency (%)
미 1
50.0%
상 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 399
99.5%
Hangul 2
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 69
17.3%
0 67
16.8%
9 41
10.3%
2 38
9.5%
4 36
9.0%
8 36
9.0%
5 31
7.8%
3 31
7.8%
7 30
7.5%
6 17
 
4.3%
Hangul
ValueCountFrequency (%)
미 1
50.0%
상 1
50.0%

Interactions

2023-12-11T08:47:53.054494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:47:52.809750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:47:53.163737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:47:52.931509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:47:59.465151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면설치일자면적(제곱미터)만장기수
연번1.0000.9500.8960.2040.660
읍면0.9501.0000.9510.4510.789
설치일자0.8960.9511.0000.6700.986
면적(제곱미터)0.2040.4510.6701.0000.883
만장기수0.6600.7890.9860.8831.000
2023-12-11T08:47:59.589971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면적(제곱미터)읍면
연번1.0000.2620.797
면적(제곱미터)0.2621.0000.219
읍면0.7970.2191.000

Missing values

2023-12-11T08:47:53.569610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:47:53.747327image/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

연번읍면공동묘지명위치설치일자관리주체면적(제곱미터)만장기수안치기수매장가능기수
01하동읍읍내공동묘지읍내리 349-111962-05-31연화마을회59111867180166
12하동읍연화공동묘지읍내리 산7-31962-05-31연산마을회2975245084290218
23하동읍흥룡공동묘지흥룡리 산31961-09-01흥룡마을회378841102103072
34하동읍화심공동묘지화심리 산361961-09-01화심마을회86781628158048
45하동읍두곡공동묘지두곡리 산511979-06-27두곡마을회1356721041947157
56하동읍화산공동묘지비파리 산61963-01-05화산마을회198360155645
67하동읍목도공동묘지목도리 산271920(1979-06-29)목도마을회57523807373275
78화개면검두공동묘지부춘리산218,213-11979검두마을회254350500
89화개면중기공동묘지덕은리산53-11979중기마을회715705515
910화개면상덕공동묘지덕은리산491979상덕마을회24871201200
연번읍면공동묘지명위치설치일자관리주체면적(제곱미터)만장기수안치기수매장가능기수
185186옥종면동곡마을공동묘지대곡리 산1571979-06-22동곡마을회861622062158
186187옥종면추동마을공동묘지대곡리 산471979-06-22추동마을회555425020248
187188옥종면오율마을공동묘지궁항리 산691979-06-22오율마을회869441529
188189옥종면궁항마을공동묘지궁항리 산1071979-06-22궁항마을회19831001981
189190옥종면궁항마을공동묘지궁항리 산1451979-06-29궁항마을회23471182593
190191옥종면오율마을공동묘지궁항리 산801979-06-22오율마을회207271001387
191192옥종면위태마을공동묘지위태리 산551979-06-22위태마을회446322515471
192193옥종면위태마을공동묘지위태리 산2801979-06-22위태마을회979491435
193194옥종면갈성마을공동묘지위태리 산1921979-06-22갈성마을회1135957352350
194195옥종면회신마을공동묘지회신리 산621979-06-23회신마을회35271788098