Overview

Dataset statistics

Number of variables11
Number of observations482
Missing cells242
Missing cells (%)4.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory41.6 KiB
Average record size in memory88.3 B

Variable types

Text11

Dataset

Description공인중개사의 업무 및 부동산 거래신고에 관한 법률 제27조에 의해 신고된 농지(논,밭,과수원)의 실거래 가격 정보(읍.면.동별 평균, 최저,최고가)
Author농림축산식품부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220217000000002080

Alerts

구분 has 242 (50.2%) missing valuesMissing

Reproduction

Analysis started2023-12-11 03:25:17.909172
Analysis finished2023-12-11 03:25:18.496641
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

MISSING 

Distinct240
Distinct (%)100.0%
Missing242
Missing (%)50.2%
Memory size3.9 KiB
2023-12-11T12:25:18.776765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length8
Mean length8.5458333
Min length7

Characters and Unicode

Total characters2051
Distinct characters144
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

Unique240 ?
Unique (%)100.0%

Sample

1st row서울특별시 종로구
2nd row서울특별시 중랑구
3rd row서울특별시 성북구
4th row서울특별시 강북구
5th row서울특별시 도봉구
ValueCountFrequency (%)
경기도 45
 
8.8%
경상북도 24
 
4.7%
전라남도 22
 
4.3%
경상남도 22
 
4.3%
강원도 18
 
3.5%
충청남도 18
 
3.5%
서울특별시 15
 
2.9%
부산광역시 15
 
2.9%
전라북도 15
 
2.9%
충청북도 13
 
2.5%
Other values (238) 306
59.6%
2023-12-11T12:25:19.286861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
273
 
13.3%
184
 
9.0%
161
 
7.8%
99
 
4.8%
94
 
4.6%
89
 
4.3%
78
 
3.8%
60
 
2.9%
55
 
2.7%
50
 
2.4%
Other values (134) 908
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1778
86.7%
Space Separator 273
 
13.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
184
 
10.3%
161
 
9.1%
99
 
5.6%
94
 
5.3%
89
 
5.0%
78
 
4.4%
60
 
3.4%
55
 
3.1%
50
 
2.8%
48
 
2.7%
Other values (133) 860
48.4%
Space Separator
ValueCountFrequency (%)
273
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1778
86.7%
Common 273
 
13.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
184
 
10.3%
161
 
9.1%
99
 
5.6%
94
 
5.3%
89
 
5.0%
78
 
4.4%
60
 
3.4%
55
 
3.1%
50
 
2.8%
48
 
2.7%
Other values (133) 860
48.4%
Common
ValueCountFrequency (%)
273
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1778
86.7%
ASCII 273
 
13.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
273
100.0%
Hangul
ValueCountFrequency (%)
184
 
10.3%
161
 
9.1%
99
 
5.6%
94
 
5.3%
89
 
5.0%
78
 
4.4%
60
 
3.4%
55
 
3.1%
50
 
2.8%
48
 
2.7%
Other values (133) 860
48.4%
Distinct424
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-11T12:25:19.638455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.3112033
Min length1

Characters and Unicode

Total characters2560
Distinct characters16
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

Unique395 ?
Unique (%)82.0%

Sample

1st row평균
2nd row최소
3rd row415,880
4th row192,530
5th row1,156,731
ValueCountFrequency (%)
18
 
3.7%
790 5
 
1.0%
220 4
 
0.8%
700 4
 
0.8%
240 4
 
0.8%
330 3
 
0.6%
3,020 3
 
0.6%
470 3
 
0.6%
690 3
 
0.6%
1,310 2
 
0.4%
Other values (414) 433
89.8%
2023-12-11T12:25:20.168233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 416
16.2%
, 377
14.7%
1 292
11.4%
2 223
8.7%
3 217
8.5%
5 180
7.0%
4 175
6.8%
9 174
6.8%
7 172
6.7%
6 171
6.7%
Other values (6) 163
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2161
84.4%
Other Punctuation 377
 
14.7%
Dash Punctuation 18
 
0.7%
Other Letter 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 416
19.3%
1 292
13.5%
2 223
10.3%
3 217
10.0%
5 180
8.3%
4 175
8.1%
9 174
8.1%
7 172
8.0%
6 171
7.9%
8 141
 
6.5%
Other Letter
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 377
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2556
99.8%
Hangul 4
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 416
16.3%
, 377
14.7%
1 292
11.4%
2 223
8.7%
3 217
8.5%
5 180
7.0%
4 175
6.8%
9 174
6.8%
7 172
6.7%
6 171
6.7%
Other values (2) 159
 
6.2%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2556
99.8%
Hangul 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 416
16.3%
, 377
14.7%
1 292
11.4%
2 223
8.7%
3 217
8.5%
5 180
7.0%
4 175
6.8%
9 174
6.8%
7 172
6.7%
6 171
6.7%
Other values (2) 159
 
6.2%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Distinct434
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-11T12:25:20.515056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.0414938
Min length1

Characters and Unicode

Total characters2430
Distinct characters16
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

Unique410 ?
Unique (%)85.1%

Sample

1st row필지
2nd row최대
3rd row7
4th row939,600
5th row15
ValueCountFrequency (%)
18
 
3.7%
2 5
 
1.0%
3 4
 
0.8%
4 4
 
0.8%
14 3
 
0.6%
155 2
 
0.4%
1 2
 
0.4%
48 2
 
0.4%
787,880 2
 
0.4%
1,104 2
 
0.4%
Other values (424) 438
90.9%
2023-12-11T12:25:21.386510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 408
16.8%
, 361
14.9%
1 281
11.6%
2 243
10.0%
3 181
7.4%
4 174
7.2%
5 164
6.7%
7 155
 
6.4%
6 153
 
6.3%
8 150
 
6.2%
Other values (6) 160
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2047
84.2%
Other Punctuation 361
 
14.9%
Dash Punctuation 18
 
0.7%
Other Letter 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 408
19.9%
1 281
13.7%
2 243
11.9%
3 181
8.8%
4 174
8.5%
5 164
8.0%
7 155
 
7.6%
6 153
 
7.5%
8 150
 
7.3%
9 138
 
6.7%
Other Letter
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 361
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2426
99.8%
Hangul 4
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 408
16.8%
, 361
14.9%
1 281
11.6%
2 243
10.0%
3 181
7.5%
4 174
7.2%
5 164
6.8%
7 155
 
6.4%
6 153
 
6.3%
8 150
 
6.2%
Other values (2) 156
 
6.4%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2426
99.8%
Hangul 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 408
16.8%
, 361
14.9%
1 281
11.6%
2 243
10.0%
3 181
7.5%
4 174
7.2%
5 164
6.8%
7 155
 
6.4%
6 153
 
6.3%
8 150
 
6.2%
Other values (2) 156
 
6.4%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Distinct428
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-11T12:25:21.792570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.3236515
Min length1

Characters and Unicode

Total characters2566
Distinct characters16
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

Unique399 ?
Unique (%)82.8%

Sample

1st row평균
2nd row최소
3rd row591,407
4th row410,960
5th row1,024,500
ValueCountFrequency (%)
20
 
4.1%
480 4
 
0.8%
160 3
 
0.6%
470 3
 
0.6%
1,040 3
 
0.6%
570 3
 
0.6%
380 3
 
0.6%
1,110 2
 
0.4%
170,080 2
 
0.4%
680 2
 
0.4%
Other values (418) 437
90.7%
2023-12-11T12:25:22.391771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 405
15.8%
, 386
15.0%
1 267
10.4%
2 227
8.8%
4 213
8.3%
3 191
7.4%
5 189
7.4%
7 188
7.3%
8 171
6.7%
9 153
 
6.0%
Other values (6) 176
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2156
84.0%
Other Punctuation 386
 
15.0%
Dash Punctuation 20
 
0.8%
Other Letter 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 405
18.8%
1 267
12.4%
2 227
10.5%
4 213
9.9%
3 191
8.9%
5 189
8.8%
7 188
8.7%
8 171
7.9%
9 153
 
7.1%
6 152
 
7.1%
Other Letter
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 386
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2562
99.8%
Hangul 4
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 405
15.8%
, 386
15.1%
1 267
10.4%
2 227
8.9%
4 213
8.3%
3 191
7.5%
5 189
7.4%
7 188
7.3%
8 171
6.7%
9 153
 
6.0%
Other values (2) 172
6.7%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2562
99.8%
Hangul 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 405
15.8%
, 386
15.1%
1 267
10.4%
2 227
8.9%
4 213
8.3%
3 191
7.5%
5 189
7.4%
7 188
7.3%
8 171
6.7%
9 153
 
6.0%
Other values (2) 172
6.7%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Distinct429
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-11T12:25:22.780272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.0414938
Min length1

Characters and Unicode

Total characters2430
Distinct characters16
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

Unique404 ?
Unique (%)83.8%

Sample

1st row필지
2nd row최대
3rd row3
4th row840,000
5th row3
ValueCountFrequency (%)
20
 
4.1%
3 5
 
1.0%
2 5
 
1.0%
5 4
 
0.8%
6 3
 
0.6%
4 3
 
0.6%
142,860 2
 
0.4%
95 2
 
0.4%
8 2
 
0.4%
1,429 2
 
0.4%
Other values (419) 434
90.0%
2023-12-11T12:25:23.444951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 399
16.4%
, 363
14.9%
1 292
12.0%
2 226
9.3%
3 197
8.1%
4 184
7.6%
7 172
7.1%
5 151
 
6.2%
6 151
 
6.2%
9 137
 
5.6%
Other values (6) 158
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2043
84.1%
Other Punctuation 363
 
14.9%
Dash Punctuation 20
 
0.8%
Other Letter 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 399
19.5%
1 292
14.3%
2 226
11.1%
3 197
9.6%
4 184
9.0%
7 172
8.4%
5 151
 
7.4%
6 151
 
7.4%
9 137
 
6.7%
8 134
 
6.6%
Other Letter
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 363
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2426
99.8%
Hangul 4
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 399
16.4%
, 363
15.0%
1 292
12.0%
2 226
9.3%
3 197
8.1%
4 184
7.6%
7 172
7.1%
5 151
 
6.2%
6 151
 
6.2%
9 137
 
5.6%
Other values (2) 154
 
6.3%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2426
99.8%
Hangul 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 399
16.4%
, 363
15.0%
1 292
12.0%
2 226
9.3%
3 197
8.1%
4 184
7.6%
7 172
7.1%
5 151
 
6.2%
6 151
 
6.2%
9 137
 
5.6%
Other values (2) 154
 
6.3%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Distinct429
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-11T12:25:23.949034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.3423237
Min length1

Characters and Unicode

Total characters2575
Distinct characters16
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

Unique397 ?
Unique (%)82.4%

Sample

1st row평균
2nd row최소
3rd row199,793
4th row58,440
5th row1,042,736
ValueCountFrequency (%)
18
 
3.7%
380 3
 
0.6%
220 3
 
0.6%
840 3
 
0.6%
400 3
 
0.6%
450 3
 
0.6%
247,930 2
 
0.4%
294,530 2
 
0.4%
920 2
 
0.4%
22,490 2
 
0.4%
Other values (419) 441
91.5%
2023-12-11T12:25:24.685810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 410
15.9%
, 383
14.9%
1 285
11.1%
2 223
8.7%
4 198
7.7%
5 193
7.5%
3 192
7.5%
6 186
7.2%
8 171
6.6%
9 166
6.4%
Other values (6) 168
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2170
84.3%
Other Punctuation 383
 
14.9%
Dash Punctuation 18
 
0.7%
Other Letter 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 410
18.9%
1 285
13.1%
2 223
10.3%
4 198
9.1%
5 193
8.9%
3 192
8.8%
6 186
8.6%
8 171
7.9%
9 166
7.6%
7 146
 
6.7%
Other Letter
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 383
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2571
99.8%
Hangul 4
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 410
15.9%
, 383
14.9%
1 285
11.1%
2 223
8.7%
4 198
7.7%
5 193
7.5%
3 192
7.5%
6 186
7.2%
8 171
6.7%
9 166
6.5%
Other values (2) 164
 
6.4%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2571
99.8%
Hangul 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 410
15.9%
, 383
14.9%
1 285
11.1%
2 223
8.7%
4 198
7.7%
5 193
7.5%
3 192
7.5%
6 186
7.2%
8 171
6.7%
9 166
6.5%
Other values (2) 164
 
6.4%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Distinct439
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-11T12:25:25.131251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.060166
Min length1

Characters and Unicode

Total characters2439
Distinct characters16
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

Unique420 ?
Unique (%)87.1%

Sample

1st row필지
2nd row최대
3rd row3
4th row423,520
5th row5
ValueCountFrequency (%)
18
 
3.7%
1 7
 
1.5%
3 4
 
0.8%
2 3
 
0.6%
34 2
 
0.4%
97 2
 
0.4%
1,405 2
 
0.4%
8 2
 
0.4%
9 2
 
0.4%
10 2
 
0.4%
Other values (429) 438
90.9%
2023-12-11T12:25:25.771444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 404
16.6%
, 362
14.8%
1 300
12.3%
3 221
9.1%
2 202
8.3%
6 175
7.2%
4 165
6.8%
5 154
 
6.3%
7 152
 
6.2%
9 144
 
5.9%
Other values (6) 160
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2055
84.3%
Other Punctuation 362
 
14.8%
Dash Punctuation 18
 
0.7%
Other Letter 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 404
19.7%
1 300
14.6%
3 221
10.8%
2 202
9.8%
6 175
8.5%
4 165
8.0%
5 154
 
7.5%
7 152
 
7.4%
9 144
 
7.0%
8 138
 
6.7%
Other Letter
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 362
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2435
99.8%
Hangul 4
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 404
16.6%
, 362
14.9%
1 300
12.3%
3 221
9.1%
2 202
8.3%
6 175
7.2%
4 165
6.8%
5 154
 
6.3%
7 152
 
6.2%
9 144
 
5.9%
Other values (2) 156
 
6.4%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2435
99.8%
Hangul 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 404
16.6%
, 362
14.9%
1 300
12.3%
3 221
9.1%
2 202
8.3%
6 175
7.2%
4 165
6.8%
5 154
 
6.3%
7 152
 
6.2%
9 144
 
5.9%
Other values (2) 156
 
6.4%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Distinct428
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-11T12:25:26.336961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.379668
Min length1

Characters and Unicode

Total characters2593
Distinct characters16
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

Unique394 ?
Unique (%)81.7%

Sample

1st row평균
2nd row최소
3rd row36,680
4th row29,910
5th row1,118,075
ValueCountFrequency (%)
16
 
3.3%
540 4
 
0.8%
300 4
 
0.8%
370 3
 
0.6%
1,190 3
 
0.6%
830 2
 
0.4%
880 2
 
0.4%
740 2
 
0.4%
18,150 2
 
0.4%
48,350 2
 
0.4%
Other values (418) 442
91.7%
2023-12-11T12:25:27.067955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 397
15.3%
, 385
14.8%
1 305
11.8%
2 237
9.1%
4 207
8.0%
3 195
7.5%
5 190
7.3%
8 178
6.9%
7 168
6.5%
6 167
6.4%
Other values (6) 164
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2188
84.4%
Other Punctuation 385
 
14.8%
Dash Punctuation 16
 
0.6%
Other Letter 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 397
18.1%
1 305
13.9%
2 237
10.8%
4 207
9.5%
3 195
8.9%
5 190
8.7%
8 178
8.1%
7 168
7.7%
6 167
7.6%
9 144
 
6.6%
Other Letter
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 385
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2589
99.8%
Hangul 4
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 397
15.3%
, 385
14.9%
1 305
11.8%
2 237
9.2%
4 207
8.0%
3 195
7.5%
5 190
7.3%
8 178
6.9%
7 168
6.5%
6 167
6.5%
Other values (2) 160
6.2%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2589
99.8%
Hangul 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 397
15.3%
, 385
14.9%
1 305
11.8%
2 237
9.2%
4 207
8.0%
3 195
7.5%
5 190
7.3%
8 178
6.9%
7 168
6.5%
6 167
6.5%
Other values (2) 160
6.2%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Distinct436
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-11T12:25:27.579766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.1141079
Min length1

Characters and Unicode

Total characters2465
Distinct characters16
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

Unique416 ?
Unique (%)86.3%

Sample

1st row필지
2nd row최대
3rd row2
4th row43,450
5th row2
ValueCountFrequency (%)
16
 
3.3%
2 5
 
1.0%
1 4
 
0.8%
4 4
 
0.8%
28 3
 
0.6%
5 3
 
0.6%
14 3
 
0.6%
3 3
 
0.6%
13 3
 
0.6%
35 2
 
0.4%
Other values (426) 436
90.5%
2023-12-11T12:25:28.261689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 419
17.0%
, 371
15.1%
1 292
11.8%
3 212
8.6%
2 211
8.6%
5 191
7.7%
4 187
7.6%
8 150
 
6.1%
6 149
 
6.0%
7 136
 
5.5%
Other values (6) 147
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2074
84.1%
Other Punctuation 371
 
15.1%
Dash Punctuation 16
 
0.6%
Other Letter 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 419
20.2%
1 292
14.1%
3 212
10.2%
2 211
10.2%
5 191
9.2%
4 187
9.0%
8 150
 
7.2%
6 149
 
7.2%
7 136
 
6.6%
9 127
 
6.1%
Other Letter
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 371
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2461
99.8%
Hangul 4
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 419
17.0%
, 371
15.1%
1 292
11.9%
3 212
8.6%
2 211
8.6%
5 191
7.8%
4 187
7.6%
8 150
 
6.1%
6 149
 
6.1%
7 136
 
5.5%
Other values (2) 143
 
5.8%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2461
99.8%
Hangul 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 419
17.0%
, 371
15.1%
1 292
11.9%
3 212
8.6%
2 211
8.6%
5 191
7.8%
4 187
7.6%
8 150
 
6.1%
6 149
 
6.1%
7 136
 
5.5%
Other values (2) 143
 
5.8%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Distinct410
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-11T12:25:28.782461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.2738589
Min length1

Characters and Unicode

Total characters2542
Distinct characters16
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

Unique388 ?
Unique (%)80.5%

Sample

1st row평균
2nd row최소
3rd row114,665
4th row113,660
5th row765,570
ValueCountFrequency (%)
47
 
9.8%
600 3
 
0.6%
730 3
 
0.6%
1,670 3
 
0.6%
1,200 3
 
0.6%
1,180 3
 
0.6%
750 2
 
0.4%
2,110 2
 
0.4%
1,510 2
 
0.4%
1,070 2
 
0.4%
Other values (400) 412
85.5%
2023-12-11T12:25:29.365537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 400
15.7%
0 388
15.3%
1 311
12.2%
3 212
8.3%
2 209
8.2%
6 187
7.4%
4 171
6.7%
5 163
6.4%
8 159
 
6.3%
9 150
 
5.9%
Other values (6) 192
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2091
82.3%
Other Punctuation 400
 
15.7%
Dash Punctuation 47
 
1.8%
Other Letter 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 388
18.6%
1 311
14.9%
3 212
10.1%
2 209
10.0%
6 187
8.9%
4 171
8.2%
5 163
7.8%
8 159
7.6%
9 150
 
7.2%
7 141
 
6.7%
Other Letter
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 400
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2538
99.8%
Hangul 4
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
, 400
15.8%
0 388
15.3%
1 311
12.3%
3 212
8.4%
2 209
8.2%
6 187
7.4%
4 171
6.7%
5 163
6.4%
8 159
 
6.3%
9 150
 
5.9%
Other values (2) 188
7.4%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2538
99.8%
Hangul 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 400
15.8%
0 388
15.3%
1 311
12.3%
3 212
8.4%
2 209
8.2%
6 187
7.4%
4 171
6.7%
5 163
6.4%
8 159
 
6.3%
9 150
 
5.9%
Other values (2) 188
7.4%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Distinct384
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-11T12:25:29.784801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length4.3008299
Min length1

Characters and Unicode

Total characters2073
Distinct characters16
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

Unique350 ?
Unique (%)72.6%

Sample

1st row필지
2nd row최대
3rd row2
4th row115,670
5th row3
ValueCountFrequency (%)
46
 
9.5%
2 6
 
1.2%
12 4
 
0.8%
5 4
 
0.8%
11 4
 
0.8%
18 3
 
0.6%
376 3
 
0.6%
52 3
 
0.6%
39 3
 
0.6%
8 3
 
0.6%
Other values (374) 403
83.6%
2023-12-11T12:25:30.396316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 347
16.7%
, 233
11.2%
1 229
11.0%
2 197
9.5%
3 181
8.7%
5 166
8.0%
4 159
7.7%
6 151
7.3%
7 130
 
6.3%
9 117
 
5.6%
Other values (6) 163
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1790
86.3%
Other Punctuation 233
 
11.2%
Dash Punctuation 46
 
2.2%
Other Letter 4
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 347
19.4%
1 229
12.8%
2 197
11.0%
3 181
10.1%
5 166
9.3%
4 159
8.9%
6 151
8.4%
7 130
 
7.3%
9 117
 
6.5%
8 113
 
6.3%
Other Letter
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 233
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2069
99.8%
Hangul 4
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 347
16.8%
, 233
11.3%
1 229
11.1%
2 197
9.5%
3 181
8.7%
5 166
8.0%
4 159
7.7%
6 151
7.3%
7 130
 
6.3%
9 117
 
5.7%
Other values (2) 159
7.7%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2069
99.8%
Hangul 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 347
16.8%
, 233
11.3%
1 229
11.1%
2 197
9.5%
3 181
8.7%
5 166
8.0%
4 159
7.7%
6 151
7.3%
7 130
 
6.3%
9 117
 
5.7%
Other values (2) 159
7.7%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Missing values

2023-12-11T12:25:18.273879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:25:18.432907image/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

구분2010년Unnamed: 22011년Unnamed: 42012년Unnamed: 62013년Unnamed: 82014년Unnamed: 10
0<NA>평균필지평균필지평균필지평균필지평균필지
1<NA>최소최대최소최대최소최대최소최대최소최대
2서울특별시 종로구415,8807591,4073199,793336,6802114,6652
3<NA>192,530939,600410,960840,00058,440423,52029,91043,450113,660115,670
4서울특별시 중랑구1,156,731151,024,50031,042,73651,118,0752765,5703
5<NA>907,5501,508,600643,5601,280,000751,8801,408,720891,8901,344,260410,9501,128,400
6서울특별시 성북구268,9102--368,3201----
7<NA>264,710273,110--368,320368,320----
8서울특별시 강북구--63,2501678,4852812,9507--
9<NA>--63,25063,250438,600918,370311,3201,500,000--
구분2010년Unnamed: 22011년Unnamed: 42012년Unnamed: 62013년Unnamed: 82014년Unnamed: 10
472경상남도 함양군13,4851,52514,1211,35414,6951,40514,9141,30216,396395
473<NA>70045,6009047,6201,41047,10027049,35075054,580
474경상남도 거창군10,4481,59412,1141,66911,8341,56912,7431,58114,704461
475<NA>19033,6102042,15016038,48013044,86061047,610
476경상남도 합천군9,7212,12410,2442,08811,9951,97912,2652,25612,637596
477<NA>26028,32038031,97050034,75039035,2201,07036,270
478제주특별자치도 제주시43,9812,20647,7352,99563,8473,27860,2663,89460,7331,120
479<NA>1,630190,5402,650198,8402,310270,8301,090256,900800232,400
480제주특별자치도 서귀포시40,8031,98443,7732,19353,6872,42462,2853,38671,344947
481<NA>2,000147,2401,450151,2402,150188,3001,680238,8703,010277,920