Overview

Dataset statistics

Number of variables33
Number of observations144
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.3 KiB
Average record size in memory264.9 B

Variable types

Text33

Dataset

Description우리나라 온실가스 인벤토리 배출량은 국내 활동(에너지, 산업공정, 농업, LULUCF*, 폐기물)으로 발생하는, 교토의정서에서 규 정한 6대 직접온실가스인 이산화탄소, 메탄, 아산화질소, 수소불화탄소, 과불화탄소, 육불화황의 배출, 흡수량을 보고한다.*LULUCF(Land Use, Land-Use Change and Forestry) : 토지이용, 토지이용 변화 및 임업단위: 백만톤 CO2 eq., NO = 배출활동 및 공정이 없는 경우, NE = 산정하지 아니하는 경우, NA = 자연적, 이론적으로 발생하지 않는 활동 및 공정의 경우, IE = 다른 항목에 포함하여 보고하는 경우, C = 기밀정보인 경우
Author환경부 온실가스종합정보센터
URLhttps://www.data.go.kr/data/15049589/fileData.do

Alerts

분야 및 연도 has unique valuesUnique

Reproduction

Analysis started2024-01-14 13:43:27.733946
Analysis finished2024-01-14 13:43:29.095650
Duration1.36 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

분야 및 연도
Text

UNIQUE 

Distinct144
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:29.333256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length27.5
Mean length17.041667
Min length2

Characters and Unicode

Total characters2454
Distinct characters213
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)100.0%

Sample

1st row총배출량(Gg CO2eq)
2nd row순배출량
3rd row에너지
4th rowA 연료연소
5th rowA 연료연소_1 에너지산업
ValueCountFrequency (%)
a 56
 
8.9%
및 47
 
7.4%
b 27
 
4.3%
c 19
 
3.0%
f 17
 
2.7%
연료연소_2 13
 
2.1%
제조업 13
 
2.1%
육불화황 13
 
2.1%
할로카본 13
 
2.1%
배출 12
 
1.9%
Other values (274) 401
63.5%
2024-01-14T22:43:29.860091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
487
 
19.8%
_ 143
 
5.8%
지 70
 
2.9%
연 68
 
2.8%
소 61
 
2.5%
A 56
 
2.3%
업 53
 
2.2%
및 47
 
1.9%
산 46
 
1.9%
2 40
 
1.6%
Other values (203) 1383
56.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1468
59.8%
Space Separator 487
 
19.8%
Uppercase Letter 166
 
6.8%
Connector Punctuation 143
 
5.8%
Decimal Number 127
 
5.2%
Lowercase Letter 40
 
1.6%
Open Punctuation 11
 
0.4%
Close Punctuation 11
 
0.4%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 70
 
4.8%
연 68
 
4.6%
소 61
 
4.2%
업 53
 
3.6%
및 47
 
3.2%
산 46
 
3.1%
료 33
 
2.2%
기 32
 
2.2%
타 30
 
2.0%
제 27
 
1.8%
Other values (162) 1001
68.2%
Uppercase Letter
ValueCountFrequency (%)
A 56
33.7%
B 27
16.3%
C 25
15.1%
F 19
 
11.4%
D 12
 
7.2%
O 8
 
4.8%
E 5
 
3.0%
N 4
 
2.4%
G 2
 
1.2%
U 2
 
1.2%
Other values (4) 6
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
f 7
17.5%
a 6
15.0%
b 6
15.0%
e 5
12.5%
c 4
10.0%
o 3
7.5%
d 2
 
5.0%
m 2
 
5.0%
n 2
 
5.0%
q 1
 
2.5%
Other values (2) 2
 
5.0%
Decimal Number
ValueCountFrequency (%)
2 40
31.5%
1 26
20.5%
3 18
14.2%
4 15
 
11.8%
5 9
 
7.1%
6 7
 
5.5%
8 3
 
2.4%
7 3
 
2.4%
0 3
 
2.4%
9 3
 
2.4%
Space Separator
ValueCountFrequency (%)
487
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 143
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1468
59.8%
Common 780
31.8%
Latin 206
 
8.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 70
 
4.8%
연 68
 
4.6%
소 61
 
4.2%
업 53
 
3.6%
및 47
 
3.2%
산 46
 
3.1%
료 33
 
2.2%
기 32
 
2.2%
타 30
 
2.0%
제 27
 
1.8%
Other values (162) 1001
68.2%
Latin
ValueCountFrequency (%)
A 56
27.2%
B 27
13.1%
C 25
12.1%
F 19
 
9.2%
D 12
 
5.8%
O 8
 
3.9%
f 7
 
3.4%
a 6
 
2.9%
b 6
 
2.9%
e 5
 
2.4%
Other values (16) 35
17.0%
Common
ValueCountFrequency (%)
487
62.4%
_ 143
 
18.3%
2 40
 
5.1%
1 26
 
3.3%
3 18
 
2.3%
4 15
 
1.9%
( 11
 
1.4%
) 11
 
1.4%
5 9
 
1.2%
6 7
 
0.9%
Other values (5) 13
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1468
59.8%
ASCII 986
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
487
49.4%
_ 143
 
14.5%
A 56
 
5.7%
2 40
 
4.1%
B 27
 
2.7%
1 26
 
2.6%
C 25
 
2.5%
F 19
 
1.9%
3 18
 
1.8%
4 15
 
1.5%
Other values (31) 130
 
13.2%
Hangul
ValueCountFrequency (%)
지 70
 
4.8%
연 68
 
4.6%
소 61
 
4.2%
업 53
 
3.6%
및 47
 
3.2%
산 46
 
3.1%
료 33
 
2.2%
기 32
 
2.2%
타 30
 
2.0%
제 27
 
1.8%
Other values (162) 1001
68.2%

1990
Text

Distinct99
Distinct (%)68.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:30.133127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.9305556
Min length1

Characters and Unicode

Total characters998
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)64.6%

Sample

1st row292105.0629
2nd row254159.2211
3rd row240294.4846
4th row235182.2214
5th row48351.20284
ValueCountFrequency (%)
0 41
28.5%
13947.29207 2
 
1.4%
38226.51129 2
 
1.4%
648.66161 2
 
1.4%
173.40009 2
 
1.4%
982.8 2
 
1.4%
1.79552 1
 
0.7%
2427.17284 1
 
0.7%
4605.55056 1
 
0.7%
52.22267 1
 
0.7%
Other values (89) 89
61.8%
2024-01-14T22:43:30.579620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 116
11.6%
0 107
10.7%
1 104
10.4%
. 102
10.2%
4 94
9.4%
8 90
9.0%
3 82
8.2%
7 80
8.0%
9 75
7.5%
5 74
7.4%
Other values (3) 74
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 889
89.1%
Other Punctuation 102
 
10.2%
Dash Punctuation 6
 
0.6%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 116
13.0%
0 107
12.0%
1 104
11.7%
4 94
10.6%
8 90
10.1%
3 82
9.2%
7 80
9.0%
9 75
8.4%
5 74
8.3%
6 67
7.5%
Other Punctuation
ValueCountFrequency (%)
. 102
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 997
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 116
11.6%
0 107
10.7%
1 104
10.4%
. 102
10.2%
4 94
9.4%
8 90
9.0%
3 82
8.2%
7 80
8.0%
9 75
7.5%
5 74
7.4%
Other values (2) 73
7.3%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 998
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 116
11.6%
0 107
10.7%
1 104
10.4%
. 102
10.2%
4 94
9.4%
8 90
9.0%
3 82
8.2%
7 80
8.0%
9 75
7.5%
5 74
7.4%
Other values (3) 74
7.4%

1991
Text

Distinct97
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:30.976370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.9236111
Min length1

Characters and Unicode

Total characters997
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)62.5%

Sample

1st row315352.6113
2nd row281385.5253
3rd row258113.1879
4th row253554.4804
5th row54790.06885
ValueCountFrequency (%)
0 42
29.2%
332.61047 2
 
1.4%
16767.67819 2
 
1.4%
798.876 2
 
1.4%
77.89591 2
 
1.4%
34164.23581 2
 
1.4%
689.1024 2
 
1.4%
315352.6113 1
 
0.7%
643.38148 1
 
0.7%
387.7062 1
 
0.7%
Other values (87) 87
60.4%
2024-01-14T22:43:31.459345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 109
10.9%
. 101
10.1%
3 100
10.0%
8 92
9.2%
5 92
9.2%
1 89
8.9%
2 88
8.8%
6 87
8.7%
7 80
8.0%
4 78
7.8%
Other values (3) 81
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 889
89.2%
Other Punctuation 101
 
10.1%
Dash Punctuation 6
 
0.6%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 109
12.3%
3 100
11.2%
8 92
10.3%
5 92
10.3%
1 89
10.0%
2 88
9.9%
6 87
9.8%
7 80
9.0%
4 78
8.8%
9 74
8.3%
Other Punctuation
ValueCountFrequency (%)
. 101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 996
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 109
10.9%
. 101
10.1%
3 100
10.0%
8 92
9.2%
5 92
9.2%
1 89
8.9%
2 88
8.8%
6 87
8.7%
7 80
8.0%
4 78
7.8%
Other values (2) 80
8.0%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 997
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 109
10.9%
. 101
10.1%
3 100
10.0%
8 92
9.2%
5 92
9.2%
1 89
8.9%
2 88
8.8%
6 87
8.7%
7 80
8.0%
4 78
7.8%
Other values (3) 81
8.1%

1992
Text

Distinct99
Distinct (%)68.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:31.746220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length7.0277778
Min length1

Characters and Unicode

Total characters1012
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)64.6%

Sample

1st row343354.1466
2nd row310216.9541
3rd row278995.6349
4th row275205.9382
5th row62374.89943
ValueCountFrequency (%)
0 41
28.5%
84.84317 2
 
1.4%
33542.19195 2
 
1.4%
663.8049 2
 
1.4%
20811.83027 2
 
1.4%
1871.064 2
 
1.4%
0.41905 1
 
0.7%
717.76166 1
 
0.7%
2576.1275 1
 
0.7%
4852.90354 1
 
0.7%
Other values (89) 89
61.8%
2024-01-14T22:43:32.304053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 113
11.2%
0 106
10.5%
3 103
10.2%
. 101
10.0%
4 97
9.6%
6 92
9.1%
2 90
8.9%
9 82
8.1%
5 77
7.6%
8 73
7.2%
Other values (3) 78
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 904
89.3%
Other Punctuation 101
 
10.0%
Dash Punctuation 6
 
0.6%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 113
12.5%
0 106
11.7%
3 103
11.4%
4 97
10.7%
6 92
10.2%
2 90
10.0%
9 82
9.1%
5 77
8.5%
8 73
8.1%
7 71
7.9%
Other Punctuation
ValueCountFrequency (%)
. 101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1011
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 113
11.2%
0 106
10.5%
3 103
10.2%
. 101
10.0%
4 97
9.6%
6 92
9.1%
2 90
8.9%
9 82
8.1%
5 77
7.6%
8 73
7.2%
Other values (2) 77
7.6%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1012
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 113
11.2%
0 106
10.5%
3 103
10.2%
. 101
10.0%
4 97
9.6%
6 92
9.1%
2 90
8.9%
9 82
8.1%
5 77
7.6%
8 73
7.2%
Other values (3) 78
7.7%

1993
Text

Distinct99
Distinct (%)68.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:32.574347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length6.9861111
Min length1

Characters and Unicode

Total characters1006
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)64.6%

Sample

1st row378545.9775
2nd row346994.152
3rd row308499.8086
4th row305340.2473
5th row68765.12032
ValueCountFrequency (%)
0 41
28.5%
107.53002 2
 
1.4%
31971.37302 2
 
1.4%
657.06447 2
 
1.4%
22053.60836 2
 
1.4%
2106 2
 
1.4%
0.36871 1
 
0.7%
758.49221 1
 
0.7%
2627.1107 1
 
0.7%
4927.74999 1
 
0.7%
Other values (89) 89
61.8%
2024-01-14T22:43:33.058906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 113
11.2%
1 111
11.0%
2 101
10.0%
. 100
9.9%
3 98
9.7%
5 83
8.3%
9 82
8.2%
4 82
8.2%
7 81
8.1%
8 76
7.6%
Other values (3) 79
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 898
89.3%
Other Punctuation 100
 
9.9%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 113
12.6%
1 111
12.4%
2 101
11.2%
3 98
10.9%
5 83
9.2%
9 82
9.1%
4 82
9.1%
7 81
9.0%
8 76
8.5%
6 71
7.9%
Other Punctuation
ValueCountFrequency (%)
. 100
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1005
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 113
11.2%
1 111
11.0%
2 101
10.0%
. 100
10.0%
3 98
9.8%
5 83
8.3%
9 82
8.2%
4 82
8.2%
7 81
8.1%
8 76
7.6%
Other values (2) 78
7.8%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1006
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 113
11.2%
1 111
11.0%
2 101
10.0%
. 100
9.9%
3 98
9.7%
5 83
8.3%
9 82
8.2%
4 82
8.2%
7 81
8.1%
8 76
7.6%
Other values (3) 79
7.9%

1994
Text

Distinct100
Distinct (%)69.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:33.354320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.0763889
Min length1

Characters and Unicode

Total characters1019
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)65.3%

Sample

1st row403568.6135
2nd row369637.16
3rd row327799.6796
4th row325066.5825
5th row83606.21142
ValueCountFrequency (%)
0 40
27.8%
2266.992 2
 
1.4%
120.91322 2
 
1.4%
656.03808 2
 
1.4%
25421.0868 2
 
1.4%
34377.76848 2
 
1.4%
10.37572 1
 
0.7%
403568.6135 1
 
0.7%
400.3792 1
 
0.7%
2426.45504 1
 
0.7%
Other values (90) 90
62.5%
2024-01-14T22:43:33.881003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 115
11.3%
0 109
10.7%
. 103
10.1%
4 97
9.5%
1 96
9.4%
6 87
8.5%
3 86
8.4%
7 84
8.2%
5 83
8.1%
9 76
7.5%
Other values (3) 83
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 908
89.1%
Other Punctuation 103
 
10.1%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 115
12.7%
0 109
12.0%
4 97
10.7%
1 96
10.6%
6 87
9.6%
3 86
9.5%
7 84
9.3%
5 83
9.1%
9 76
8.4%
8 75
8.3%
Other Punctuation
ValueCountFrequency (%)
. 103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1018
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 115
11.3%
0 109
10.7%
. 103
10.1%
4 97
9.5%
1 96
9.4%
6 87
8.5%
3 86
8.4%
7 84
8.3%
5 83
8.2%
9 76
7.5%
Other values (2) 82
8.1%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1019
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 115
11.3%
0 109
10.7%
. 103
10.1%
4 97
9.5%
1 96
9.4%
6 87
8.5%
3 86
8.4%
7 84
8.2%
5 83
8.1%
9 76
7.5%
Other values (3) 83
8.1%

1995
Text

Distinct100
Distinct (%)69.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:34.188314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.1458333
Min length1

Characters and Unicode

Total characters1029
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)65.3%

Sample

1st row433787.9248
2nd row401626.6678
3rd row352000.6819
4th row349613.2315
5th row91684.69032
ValueCountFrequency (%)
0 40
27.8%
2609.568 2
 
1.4%
137.80257 2
 
1.4%
670.63416 2
 
1.4%
29288.39457 2
 
1.4%
33104.37186 2
 
1.4%
11.74402 1
 
0.7%
433787.9248 1
 
0.7%
445.97142 1
 
0.7%
2501.24785 1
 
0.7%
Other values (90) 90
62.5%
2024-01-14T22:43:34.693970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 111
10.8%
3 105
10.2%
1 103
10.0%
. 103
10.0%
4 102
9.9%
6 100
9.7%
2 93
9.0%
8 88
8.6%
5 79
7.7%
7 71
6.9%
Other values (3) 74
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 918
89.2%
Other Punctuation 103
 
10.0%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 111
12.1%
3 105
11.4%
1 103
11.2%
4 102
11.1%
6 100
10.9%
2 93
10.1%
8 88
9.6%
5 79
8.6%
7 71
7.7%
9 66
7.2%
Other Punctuation
ValueCountFrequency (%)
. 103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1028
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 111
10.8%
3 105
10.2%
1 103
10.0%
. 103
10.0%
4 102
9.9%
6 100
9.7%
2 93
9.0%
8 88
8.6%
5 79
7.7%
7 71
6.9%
Other values (2) 73
7.1%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1029
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 111
10.8%
3 105
10.2%
1 103
10.0%
. 103
10.0%
4 102
9.9%
6 100
9.7%
2 93
9.0%
8 88
8.6%
5 79
7.7%
7 71
6.9%
Other values (3) 74
7.2%

1996
Text

Distinct100
Distinct (%)69.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:35.010340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.1666667
Min length1

Characters and Unicode

Total characters1032
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)65.3%

Sample

1st row470280.3003
2nd row434432.7187
3rd row385582.1095
4th row383185.792
5th row108977.7905
ValueCountFrequency (%)
0 40
27.8%
2859.48 2
 
1.4%
145.71858 2
 
1.4%
688.09859 2
 
1.4%
34901.27113 2
 
1.4%
37033.67497 2
 
1.4%
13.86016 1
 
0.7%
470280.3003 1
 
0.7%
460.71199 1
 
0.7%
2572.1381 1
 
0.7%
Other values (90) 90
62.5%
2024-01-14T22:43:35.504113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 116
11.2%
3 103
10.0%
. 103
10.0%
1 103
10.0%
8 99
9.6%
4 97
9.4%
2 96
9.3%
7 85
8.2%
5 84
8.1%
9 74
7.2%
Other values (3) 72
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 921
89.2%
Other Punctuation 103
 
10.0%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 116
12.6%
3 103
11.2%
1 103
11.2%
8 99
10.7%
4 97
10.5%
2 96
10.4%
7 85
9.2%
5 84
9.1%
9 74
8.0%
6 64
6.9%
Other Punctuation
ValueCountFrequency (%)
. 103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1031
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 116
11.3%
3 103
10.0%
. 103
10.0%
1 103
10.0%
8 99
9.6%
4 97
9.4%
2 96
9.3%
7 85
8.2%
5 84
8.1%
9 74
7.2%
Other values (2) 71
6.9%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1032
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 116
11.2%
3 103
10.0%
. 103
10.0%
1 103
10.0%
8 99
9.6%
4 97
9.4%
2 96
9.3%
7 85
8.2%
5 84
8.1%
9 74
7.2%
Other values (3) 72
7.0%

1997
Text

Distinct101
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:35.813477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.2847222
Min length1

Characters and Unicode

Total characters1049
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)66.0%

Sample

1st row501912.2509
2nd row461298.0841
3rd row411617.5285
4th row409141.4023
5th row122325.2001
ValueCountFrequency (%)
0 39
27.1%
3255.408 2
 
1.4%
166.6306 2
 
1.4%
704.77654 2
 
1.4%
38303.13956 2
 
1.4%
41948.40184 2
 
1.4%
0.18753 1
 
0.7%
909.51171 1
 
0.7%
3020.52299 1
 
0.7%
5602.28357 1
 
0.7%
Other values (91) 91
63.2%
2024-01-14T22:43:36.269381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 119
11.3%
4 110
10.5%
1 107
10.2%
. 104
9.9%
2 101
9.6%
5 98
9.3%
3 91
8.7%
6 81
7.7%
7 81
7.7%
8 80
7.6%
Other values (3) 77
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 937
89.3%
Other Punctuation 104
 
9.9%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 119
12.7%
4 110
11.7%
1 107
11.4%
2 101
10.8%
5 98
10.5%
3 91
9.7%
6 81
8.6%
7 81
8.6%
8 80
8.5%
9 69
7.4%
Other Punctuation
ValueCountFrequency (%)
. 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1048
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 119
11.4%
4 110
10.5%
1 107
10.2%
. 104
9.9%
2 101
9.6%
5 98
9.4%
3 91
8.7%
6 81
7.7%
7 81
7.7%
8 80
7.6%
Other values (2) 76
7.3%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1049
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 119
11.3%
4 110
10.5%
1 107
10.2%
. 104
9.9%
2 101
9.6%
5 98
9.3%
3 91
8.7%
6 81
7.7%
7 81
7.7%
8 80
7.6%
Other values (3) 77
7.3%

1998
Text

Distinct101
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:36.564453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.1458333
Min length1

Characters and Unicode

Total characters1029
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)66.0%

Sample

1st row431434.4559
2nd row382505.5031
3rd row351493.3078
4th row349141.9397
5th row106295.165
ValueCountFrequency (%)
0 39
27.1%
1943.136 2
 
1.4%
137.13183 2
 
1.4%
710.4685 2
 
1.4%
37885.53396 2
 
1.4%
50616.1096 2
 
1.4%
0.17213 1
 
0.7%
1010.98293 1
 
0.7%
2981.3322 1
 
0.7%
5535.571 1
 
0.7%
Other values (91) 91
63.2%
2024-01-14T22:43:36.914631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 109
10.6%
0 104
10.1%
. 104
10.1%
1 103
10.0%
2 92
8.9%
5 91
8.8%
4 89
8.6%
6 88
8.6%
9 84
8.2%
7 83
8.1%
Other values (3) 82
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 917
89.1%
Other Punctuation 104
 
10.1%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 109
11.9%
0 104
11.3%
1 103
11.2%
2 92
10.0%
5 91
9.9%
4 89
9.7%
6 88
9.6%
9 84
9.2%
7 83
9.1%
8 74
8.1%
Other Punctuation
ValueCountFrequency (%)
. 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1028
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
3 109
10.6%
0 104
10.1%
. 104
10.1%
1 103
10.0%
2 92
8.9%
5 91
8.9%
4 89
8.7%
6 88
8.6%
9 84
8.2%
7 83
8.1%
Other values (2) 81
7.9%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1029
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 109
10.6%
0 104
10.1%
. 104
10.1%
1 103
10.0%
2 92
8.9%
5 91
8.8%
4 89
8.6%
6 88
8.6%
9 84
8.2%
7 83
8.1%
Other values (3) 82
8.0%

1999
Text

Distinct101
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:37.148583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.2361111
Min length1

Characters and Unicode

Total characters1042
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)66.0%

Sample

1st row469414.8284
2nd row412334.4732
3rd row382112.7798
4th row379577.0706
5th row116150.2112
ValueCountFrequency (%)
0 39
27.1%
3641.508 2
 
1.4%
141.55884 2
 
1.4%
710.72401 2
 
1.4%
40983.09743 2
 
1.4%
58350.89519 2
 
1.4%
0.15016 1
 
0.7%
1016.55214 1
 
0.7%
2832.07655 1
 
0.7%
5279.09267 1
 
0.7%
Other values (91) 91
63.2%
2024-01-14T22:43:37.486713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 125
12.0%
1 113
10.8%
. 104
10.0%
2 97
9.3%
5 91
8.7%
3 90
8.6%
4 88
8.4%
7 87
8.3%
9 86
8.3%
6 78
7.5%
Other values (3) 83
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 930
89.3%
Other Punctuation 104
 
10.0%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 125
13.4%
1 113
12.2%
2 97
10.4%
5 91
9.8%
3 90
9.7%
4 88
9.5%
7 87
9.4%
9 86
9.2%
6 78
8.4%
8 75
8.1%
Other Punctuation
ValueCountFrequency (%)
. 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1041
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 125
12.0%
1 113
10.9%
. 104
10.0%
2 97
9.3%
5 91
8.7%
3 90
8.6%
4 88
8.5%
7 87
8.4%
9 86
8.3%
6 78
7.5%
Other values (2) 82
7.9%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1042
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 125
12.0%
1 113
10.8%
. 104
10.0%
2 97
9.3%
5 91
8.7%
3 90
8.6%
4 88
8.4%
7 87
8.3%
9 86
8.3%
6 78
7.5%
Other values (3) 83
8.0%

2000
Text

Distinct101
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:37.712160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.2708333
Min length1

Characters and Unicode

Total characters1047
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)66.0%

Sample

1st row502730.4499
2nd row442635.7351
3rd row411584.709
4th row408915.2528
5th row136124.2042
ValueCountFrequency (%)
0 39
27.1%
3236.22 2
 
1.4%
147.70239 2
 
1.4%
717.82647 2
 
1.4%
38853.06342 2
 
1.4%
61380.17046 2
 
1.4%
0.12532 1
 
0.7%
1090.18104 1
 
0.7%
2760.71501 1
 
0.7%
5152.77989 1
 
0.7%
Other values (91) 91
63.2%
2024-01-14T22:43:38.171916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 120
11.5%
0 114
10.9%
. 104
9.9%
2 102
9.7%
4 90
8.6%
6 88
8.4%
8 88
8.4%
7 85
8.1%
9 83
7.9%
5 83
7.9%
Other values (3) 90
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 935
89.3%
Other Punctuation 104
 
9.9%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 120
12.8%
0 114
12.2%
2 102
10.9%
4 90
9.6%
6 88
9.4%
8 88
9.4%
7 85
9.1%
9 83
8.9%
5 83
8.9%
3 82
8.8%
Other Punctuation
ValueCountFrequency (%)
. 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1046
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 120
11.5%
0 114
10.9%
. 104
9.9%
2 102
9.8%
4 90
8.6%
6 88
8.4%
8 88
8.4%
7 85
8.1%
9 83
7.9%
5 83
7.9%
Other values (2) 89
8.5%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1047
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 120
11.5%
0 114
10.9%
. 104
9.9%
2 102
9.7%
4 90
8.6%
6 88
8.4%
8 88
8.4%
7 85
8.1%
9 83
7.9%
5 83
7.9%
Other values (3) 90
8.6%

2001
Text

Distinct101
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:38.473920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.2361111
Min length1

Characters and Unicode

Total characters1042
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)66.0%

Sample

1st row516008.7176
2nd row456469.1168
3rd row425928.6322
4th row423225.0276
5th row147477.0262
ValueCountFrequency (%)
0 39
27.1%
556.92 2
 
1.4%
143.61384 2
 
1.4%
699.38332 2
 
1.4%
37972.83327 2
 
1.4%
60937.94137 2
 
1.4%
0.10814 1
 
0.7%
1139.71651 1
 
0.7%
2659.89838 1
 
0.7%
4968.3293 1
 
0.7%
Other values (91) 91
63.2%
2024-01-14T22:43:38.885045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 116
11.1%
1 107
10.3%
. 104
10.0%
2 104
10.0%
3 102
9.8%
8 95
9.1%
9 89
8.5%
5 85
8.2%
6 84
8.1%
7 82
7.9%
Other values (3) 74
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 930
89.3%
Other Punctuation 104
 
10.0%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 116
12.5%
1 107
11.5%
2 104
11.2%
3 102
11.0%
8 95
10.2%
9 89
9.6%
5 85
9.1%
6 84
9.0%
7 82
8.8%
4 66
7.1%
Other Punctuation
ValueCountFrequency (%)
. 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1041
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 116
11.1%
1 107
10.3%
. 104
10.0%
2 104
10.0%
3 102
9.8%
8 95
9.1%
9 89
8.5%
5 85
8.2%
6 84
8.1%
7 82
7.9%
Other values (2) 73
7.0%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1042
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 116
11.1%
1 107
10.3%
. 104
10.0%
2 104
10.0%
3 102
9.8%
8 95
9.1%
9 89
8.5%
5 85
8.2%
6 84
8.1%
7 82
7.9%
Other values (3) 74
7.1%

2002
Text

Distinct101
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:39.167713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.2777778
Min length1

Characters and Unicode

Total characters1048
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)66.0%

Sample

1st row538458.0707
2nd row481101.1682
3rd row445254.6332
4th row442541.4214
5th row155764.2695
ValueCountFrequency (%)
0 39
27.1%
1993.68 2
 
1.4%
153.38695 2
 
1.4%
666.41203 2
 
1.4%
38058.61392 2
 
1.4%
58844.14344 2
 
1.4%
0.09636 1
 
0.7%
1187.80341 1
 
0.7%
2611.14914 1
 
0.7%
4870.39147 1
 
0.7%
Other values (91) 91
63.2%
2024-01-14T22:43:39.673276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 114
10.9%
. 104
9.9%
0 103
9.8%
4 101
9.6%
3 100
9.5%
8 92
8.8%
2 91
8.7%
5 90
8.6%
6 84
8.0%
7 83
7.9%
Other values (3) 86
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 936
89.3%
Other Punctuation 104
 
9.9%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 114
12.2%
0 103
11.0%
4 101
10.8%
3 100
10.7%
8 92
9.8%
2 91
9.7%
5 90
9.6%
6 84
9.0%
7 83
8.9%
9 78
8.3%
Other Punctuation
ValueCountFrequency (%)
. 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1047
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 114
10.9%
. 104
9.9%
0 103
9.8%
4 101
9.6%
3 100
9.6%
8 92
8.8%
2 91
8.7%
5 90
8.6%
6 84
8.0%
7 83
7.9%
Other values (2) 85
8.1%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1048
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 114
10.9%
. 104
9.9%
0 103
9.8%
4 101
9.6%
3 100
9.5%
8 92
8.8%
2 91
8.7%
5 90
8.6%
6 84
8.0%
7 83
7.9%
Other values (3) 86
8.2%

2003
Text

Distinct101
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:39.979491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.2777778
Min length1

Characters and Unicode

Total characters1048
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)66.0%

Sample

1st row548808.4335
2nd row491936.6703
3rd row452962.4605
4th row450177.558
5th row159992.5131
ValueCountFrequency (%)
0 39
27.1%
0.04932 2
 
1.4%
157.16172 2
 
1.4%
648.50306 2
 
1.4%
40698.57805 2
 
1.4%
58359.59852 2
 
1.4%
0.10124 1
 
0.7%
1223.80579 1
 
0.7%
2554.85476 1
 
0.7%
4764.77262 1
 
0.7%
Other values (91) 91
63.2%
2024-01-14T22:43:40.467347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 129
12.3%
. 104
9.9%
2 100
9.5%
8 96
9.2%
3 96
9.2%
5 95
9.1%
1 95
9.1%
4 83
7.9%
7 82
7.8%
9 81
7.7%
Other values (3) 87
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 936
89.3%
Other Punctuation 104
 
9.9%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 129
13.8%
2 100
10.7%
8 96
10.3%
3 96
10.3%
5 95
10.1%
1 95
10.1%
4 83
8.9%
7 82
8.8%
9 81
8.7%
6 79
8.4%
Other Punctuation
ValueCountFrequency (%)
. 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1047
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 129
12.3%
. 104
9.9%
2 100
9.6%
8 96
9.2%
3 96
9.2%
5 95
9.1%
1 95
9.1%
4 83
7.9%
7 82
7.8%
9 81
7.7%
Other values (2) 86
8.2%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1048
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 129
12.3%
. 104
9.9%
2 100
9.5%
8 96
9.2%
3 96
9.2%
5 95
9.1%
1 95
9.1%
4 83
7.9%
7 82
7.8%
9 81
7.7%
Other values (3) 87
8.3%

2004
Text

Distinct101
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:40.764266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.3125
Min length1

Characters and Unicode

Total characters1053
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)66.0%

Sample

1st row557042.8239
2nd row498765.4611
3rd row460054.6416
4th row456994.3356
5th row172849.3016
ValueCountFrequency (%)
0 39
27.1%
0.02456 2
 
1.4%
169.36322 2
 
1.4%
602.03325 2
 
1.4%
42483.51607 2
 
1.4%
59625.34892 2
 
1.4%
0.11108 1
 
0.7%
1203.13281 1
 
0.7%
2617.19364 1
 
0.7%
4868.60468 1
 
0.7%
Other values (91) 91
63.2%
2024-01-14T22:43:41.298532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 127
12.1%
3 108
10.3%
6 105
10.0%
2 105
10.0%
. 104
9.9%
1 103
9.8%
4 86
8.2%
5 84
8.0%
7 80
7.6%
8 72
6.8%
Other values (3) 79
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 941
89.4%
Other Punctuation 104
 
9.9%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 127
13.5%
3 108
11.5%
6 105
11.2%
2 105
11.2%
1 103
10.9%
4 86
9.1%
5 84
8.9%
7 80
8.5%
8 72
7.7%
9 71
7.5%
Other Punctuation
ValueCountFrequency (%)
. 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1052
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 127
12.1%
3 108
10.3%
6 105
10.0%
2 105
10.0%
. 104
9.9%
1 103
9.8%
4 86
8.2%
5 84
8.0%
7 80
7.6%
8 72
6.8%
Other values (2) 78
7.4%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1053
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 127
12.1%
3 108
10.3%
6 105
10.0%
2 105
10.0%
. 104
9.9%
1 103
9.8%
4 86
8.2%
5 84
8.0%
7 80
7.6%
8 72
6.8%
Other values (3) 79
7.5%

2005
Text

Distinct101
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:41.754291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.3263889
Min length1

Characters and Unicode

Total characters1055
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)66.0%

Sample

1st row561483.3645
2nd row505161.0965
3rd row469333.9397
4th row466222.8311
5th row179003.7325
ValueCountFrequency (%)
0 39
27.1%
0.06356 2
 
1.4%
194.17634 2
 
1.4%
514.27605 2
 
1.4%
42937.63652 2
 
1.4%
57678.26991 2
 
1.4%
0.12738 1
 
0.7%
1189.84629 1
 
0.7%
2689.87073 1
 
0.7%
4988.18745 1
 
0.7%
Other values (91) 91
63.2%
2024-01-14T22:43:42.329993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 115
10.9%
3 107
10.1%
0 105
10.0%
. 104
9.9%
2 102
9.7%
7 96
9.1%
5 95
9.0%
4 83
7.9%
9 81
7.7%
8 80
7.6%
Other values (3) 87
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 943
89.4%
Other Punctuation 104
 
9.9%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 115
12.2%
3 107
11.3%
0 105
11.1%
2 102
10.8%
7 96
10.2%
5 95
10.1%
4 83
8.8%
9 81
8.6%
8 80
8.5%
6 79
8.4%
Other Punctuation
ValueCountFrequency (%)
. 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1054
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 115
10.9%
3 107
10.2%
0 105
10.0%
. 104
9.9%
2 102
9.7%
7 96
9.1%
5 95
9.0%
4 83
7.9%
9 81
7.7%
8 80
7.6%
Other values (2) 86
8.2%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1055
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 115
10.9%
3 107
10.1%
0 105
10.0%
. 104
9.9%
2 102
9.7%
7 96
9.1%
5 95
9.0%
4 83
7.9%
9 81
7.7%
8 80
7.6%
Other values (3) 87
8.2%

2006
Text

Distinct101
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:42.695418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.2847222
Min length1

Characters and Unicode

Total characters1049
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)66.0%

Sample

1st row566903.4416
2nd row509455.9762
3rd row474631.2588
4th row471460.9285
5th row185847.1288
ValueCountFrequency (%)
0 39
27.1%
0.10945 2
 
1.4%
143.05334 2
 
1.4%
364.91169 2
 
1.4%
41005.47182 2
 
1.4%
59191.92661 2
 
1.4%
0.14151 1
 
0.7%
1230.41912 1
 
0.7%
2672.64133 1
 
0.7%
4934.32073 1
 
0.7%
Other values (91) 91
63.2%
2024-01-14T22:43:43.241724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 125
11.9%
2 110
10.5%
4 109
10.4%
. 104
9.9%
1 103
9.8%
3 90
8.6%
6 89
8.5%
7 84
8.0%
8 84
8.0%
5 75
7.1%
Other values (3) 76
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 937
89.3%
Other Punctuation 104
 
9.9%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 125
13.3%
2 110
11.7%
4 109
11.6%
1 103
11.0%
3 90
9.6%
6 89
9.5%
7 84
9.0%
8 84
9.0%
5 75
8.0%
9 68
7.3%
Other Punctuation
ValueCountFrequency (%)
. 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1048
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 125
11.9%
2 110
10.5%
4 109
10.4%
. 104
9.9%
1 103
9.8%
3 90
8.6%
6 89
8.5%
7 84
8.0%
8 84
8.0%
5 75
7.2%
Other values (2) 75
7.2%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1049
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 125
11.9%
2 110
10.5%
4 109
10.4%
. 104
9.9%
1 103
9.8%
3 90
8.6%
6 89
8.5%
7 84
8.0%
8 84
8.0%
5 75
7.1%
Other values (3) 76
7.2%

2007
Text

Distinct101
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:43.565234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.2708333
Min length1

Characters and Unicode

Total characters1047
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)66.0%

Sample

1st row580196.1504
2nd row522071.0537
3rd row492132.3822
4th row488738.268
5th row197249.6164
ValueCountFrequency (%)
0 39
27.1%
0.11718 2
 
1.4%
180.18049 2
 
1.4%
288.58523 2
 
1.4%
41604.00861 2
 
1.4%
60261.48927 2
 
1.4%
0.17098 1
 
0.7%
1273.20432 1
 
0.7%
2692.34634 1
 
0.7%
4958.80644 1
 
0.7%
Other values (91) 91
63.2%
2024-01-14T22:43:44.100613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 117
11.2%
1 113
10.8%
. 104
9.9%
3 100
9.6%
2 99
9.5%
4 96
9.2%
7 85
8.1%
9 84
8.0%
6 83
7.9%
8 82
7.8%
Other values (3) 84
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 935
89.3%
Other Punctuation 104
 
9.9%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 117
12.5%
1 113
12.1%
3 100
10.7%
2 99
10.6%
4 96
10.3%
7 85
9.1%
9 84
9.0%
6 83
8.9%
8 82
8.8%
5 76
8.1%
Other Punctuation
ValueCountFrequency (%)
. 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1046
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 117
11.2%
1 113
10.8%
. 104
9.9%
3 100
9.6%
2 99
9.5%
4 96
9.2%
7 85
8.1%
9 84
8.0%
6 83
7.9%
8 82
7.8%
Other values (2) 83
7.9%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1047
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 117
11.2%
1 113
10.8%
. 104
9.9%
3 100
9.6%
2 99
9.5%
4 96
9.2%
7 85
8.1%
9 84
8.0%
6 83
7.9%
8 82
7.8%
Other values (3) 84
8.0%

2008
Text

Distinct101
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:44.473120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.3194444
Min length1

Characters and Unicode

Total characters1054
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)66.0%

Sample

1st row593540.7176
2nd row534495.4289
3rd row506048.645
4th row502596.7916
5th row210717.5452
ValueCountFrequency (%)
0 39
27.1%
0.12137 2
 
1.4%
218.98903 2
 
1.4%
243.92383 2
 
1.4%
39131.89886 2
 
1.4%
61488.16185 2
 
1.4%
0.24116 1
 
0.7%
1220.8161 1
 
0.7%
2668.56653 1
 
0.7%
4902.99324 1
 
0.7%
Other values (91) 91
63.2%
2024-01-14T22:43:45.004510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 115
10.9%
0 110
10.4%
2 109
10.3%
. 104
9.9%
3 102
9.7%
6 96
9.1%
8 89
8.4%
4 87
8.3%
7 85
8.1%
5 81
7.7%
Other values (3) 76
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 942
89.4%
Other Punctuation 104
 
9.9%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 115
12.2%
0 110
11.7%
2 109
11.6%
3 102
10.8%
6 96
10.2%
8 89
9.4%
4 87
9.2%
7 85
9.0%
5 81
8.6%
9 68
7.2%
Other Punctuation
ValueCountFrequency (%)
. 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1053
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 115
10.9%
0 110
10.4%
2 109
10.4%
. 104
9.9%
3 102
9.7%
6 96
9.1%
8 89
8.5%
4 87
8.3%
7 85
8.1%
5 81
7.7%
Other values (2) 75
7.1%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1054
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 115
10.9%
0 110
10.4%
2 109
10.3%
. 104
9.9%
3 102
9.7%
6 96
9.1%
8 89
8.4%
4 87
8.3%
7 85
8.1%
5 81
7.7%
Other values (3) 76
7.2%

2009
Text

Distinct101
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:45.395513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.2361111
Min length1

Characters and Unicode

Total characters1042
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)66.0%

Sample

1st row597319.369
2nd row538470.5269
3rd row512320.7746
4th row509073.8462
5th row229408.9519
ValueCountFrequency (%)
0 39
27.1%
0.1226 2
 
1.4%
155.26512 2
 
1.4%
223.64618 2
 
1.4%
35925.98281 2
 
1.4%
61294.64643 2
 
1.4%
0.31686 1
 
0.7%
1243.59081 1
 
0.7%
2784.94639 1
 
0.7%
5105.31684 1
 
0.7%
Other values (91) 91
63.2%
2024-01-14T22:43:45.962024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 112
10.7%
3 106
10.2%
. 103
9.9%
9 100
9.6%
0 98
9.4%
1 98
9.4%
5 91
8.7%
6 88
8.4%
7 85
8.2%
8 77
7.4%
Other values (3) 84
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 931
89.3%
Other Punctuation 103
 
9.9%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 112
12.0%
3 106
11.4%
9 100
10.7%
0 98
10.5%
1 98
10.5%
5 91
9.8%
6 88
9.5%
7 85
9.1%
8 77
8.3%
4 76
8.2%
Other Punctuation
ValueCountFrequency (%)
. 103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1041
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 112
10.8%
3 106
10.2%
. 103
9.9%
9 100
9.6%
0 98
9.4%
1 98
9.4%
5 91
8.7%
6 88
8.5%
7 85
8.2%
8 77
7.4%
Other values (2) 83
8.0%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1042
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 112
10.7%
3 106
10.2%
. 103
9.9%
9 100
9.6%
0 98
9.4%
1 98
9.4%
5 91
8.7%
6 88
8.4%
7 85
8.2%
8 77
7.4%
Other values (3) 84
8.1%

2010
Text

Distinct103
Distinct (%)71.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:46.329465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.3055556
Min length1

Characters and Unicode

Total characters1052
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)68.1%

Sample

1st row655106.2989
2nd row599016.3944
3rd row564678.6543
4th row560898.2916
5th row254797.297
ValueCountFrequency (%)
0 38
26.4%
58843.38109 2
 
1.4%
204.88044 2
 
1.4%
38444.28516 2
 
1.4%
0.13035 2
 
1.4%
0.51989 1
 
0.7%
655106.2989 1
 
0.7%
11.96566 1
 
0.7%
2819.49965 1
 
0.7%
5150.63105 1
 
0.7%
Other values (93) 93
64.6%
2024-01-14T22:43:46.861758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 120
11.4%
0 107
10.2%
5 106
10.1%
. 105
10.0%
1 104
9.9%
6 90
8.6%
8 89
8.5%
2 89
8.5%
4 85
8.1%
7 75
7.1%
Other values (3) 82
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 939
89.3%
Other Punctuation 105
 
10.0%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 120
12.8%
0 107
11.4%
5 106
11.3%
1 104
11.1%
6 90
9.6%
8 89
9.5%
2 89
9.5%
4 85
9.1%
7 75
8.0%
9 74
7.9%
Other Punctuation
ValueCountFrequency (%)
. 105
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1051
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
3 120
11.4%
0 107
10.2%
5 106
10.1%
. 105
10.0%
1 104
9.9%
6 90
8.6%
8 89
8.5%
2 89
8.5%
4 85
8.1%
7 75
7.1%
Other values (2) 81
7.7%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1052
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 120
11.4%
0 107
10.2%
5 106
10.1%
. 105
10.0%
1 104
9.9%
6 90
8.6%
8 89
8.5%
2 89
8.5%
4 85
8.1%
7 75
7.1%
Other values (3) 82
7.8%

2011
Text

Distinct103
Distinct (%)71.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:47.215546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.2916667
Min length1

Characters and Unicode

Total characters1050
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)68.1%

Sample

1st row683798.1228
2nd row628553.1186
3rd row593697.4135
4th row589656.8136
5th row262387.6224
ValueCountFrequency (%)
0 38
26.4%
57762.62288 2
 
1.4%
156.2403 2
 
1.4%
38168.15482 2
 
1.4%
0.12138 2
 
1.4%
0.52061 1
 
0.7%
683798.1228 1
 
0.7%
12.26507 1
 
0.7%
2625.4726 1
 
0.7%
4798.45091 1
 
0.7%
Other values (93) 93
64.6%
2024-01-14T22:43:47.798253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 112
10.7%
1 110
10.5%
0 109
10.4%
. 105
10.0%
5 94
9.0%
8 92
8.8%
6 91
8.7%
3 86
8.2%
4 85
8.1%
9 81
7.7%
Other values (3) 85
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 937
89.2%
Other Punctuation 105
 
10.0%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 112
12.0%
1 110
11.7%
0 109
11.6%
5 94
10.0%
8 92
9.8%
6 91
9.7%
3 86
9.2%
4 85
9.1%
9 81
8.6%
7 77
8.2%
Other Punctuation
ValueCountFrequency (%)
. 105
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1049
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 112
10.7%
1 110
10.5%
0 109
10.4%
. 105
10.0%
5 94
9.0%
8 92
8.8%
6 91
8.7%
3 86
8.2%
4 85
8.1%
9 81
7.7%
Other values (2) 84
8.0%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1050
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 112
10.7%
1 110
10.5%
0 109
10.4%
. 105
10.0%
5 94
9.0%
8 92
8.8%
6 91
8.7%
3 86
8.2%
4 85
8.1%
9 81
7.7%
Other values (3) 85
8.1%

2012
Text

Distinct103
Distinct (%)71.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:48.150940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.3402778
Min length1

Characters and Unicode

Total characters1057
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)68.1%

Sample

1st row687004.9777
2nd row637740.4591
3rd row594966.1118
4th row590615.4887
5th row266405.6356
ValueCountFrequency (%)
0 38
26.4%
51554.84255 2
 
1.4%
169.05178 2
 
1.4%
37410.42754 2
 
1.4%
0.08458 2
 
1.4%
0.51343 1
 
0.7%
687004.9777 1
 
0.7%
12.39986 1
 
0.7%
2809.26729 1
 
0.7%
5112.56253 1
 
0.7%
Other values (93) 93
64.6%
2024-01-14T22:43:48.706313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 120
11.4%
0 109
10.3%
5 109
10.3%
2 108
10.2%
. 105
9.9%
4 103
9.7%
8 92
8.7%
3 80
7.6%
7 77
7.3%
9 75
7.1%
Other values (3) 79
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 944
89.3%
Other Punctuation 105
 
9.9%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 120
12.7%
0 109
11.5%
5 109
11.5%
2 108
11.4%
4 103
10.9%
8 92
9.7%
3 80
8.5%
7 77
8.2%
9 75
7.9%
6 71
7.5%
Other Punctuation
ValueCountFrequency (%)
. 105
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1056
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 120
11.4%
0 109
10.3%
5 109
10.3%
2 108
10.2%
. 105
9.9%
4 103
9.8%
8 92
8.7%
3 80
7.6%
7 77
7.3%
9 75
7.1%
Other values (2) 78
7.4%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1057
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 120
11.4%
0 109
10.3%
5 109
10.3%
2 108
10.2%
. 105
9.9%
4 103
9.7%
8 92
8.7%
3 80
7.6%
7 77
7.3%
9 75
7.1%
Other values (3) 79
7.5%

2013
Text

Distinct103
Distinct (%)71.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:49.090306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.2847222
Min length1

Characters and Unicode

Total characters1049
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)68.1%

Sample

1st row695715.3019
2nd row650683.8509
3rd row602945.0458
4th row598474.7796
5th row272977.0572
ValueCountFrequency (%)
0 38
26.4%
47052.53244 2
 
1.4%
162.09023 2
 
1.4%
37434.46187 2
 
1.4%
0.03041 2
 
1.4%
0.33903 1
 
0.7%
695715.3019 1
 
0.7%
12.25407 1
 
0.7%
2871.74893 1
 
0.7%
5213.91427 1
 
0.7%
Other values (93) 93
64.6%
2024-01-14T22:43:49.462702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 120
11.4%
1 114
10.9%
. 105
10.0%
3 101
9.6%
2 100
9.5%
4 92
8.8%
7 91
8.7%
9 83
7.9%
5 81
7.7%
8 81
7.7%
Other values (3) 81
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 936
89.2%
Other Punctuation 105
 
10.0%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 120
12.8%
1 114
12.2%
3 101
10.8%
2 100
10.7%
4 92
9.8%
7 91
9.7%
9 83
8.9%
5 81
8.7%
8 81
8.7%
6 73
7.8%
Other Punctuation
ValueCountFrequency (%)
. 105
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1048
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 120
11.5%
1 114
10.9%
. 105
10.0%
3 101
9.6%
2 100
9.5%
4 92
8.8%
7 91
8.7%
9 83
7.9%
5 81
7.7%
8 81
7.7%
Other values (2) 80
7.6%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1049
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 120
11.4%
1 114
10.9%
. 105
10.0%
3 101
9.6%
2 100
9.5%
4 92
8.8%
7 91
8.7%
9 83
7.9%
5 81
7.7%
8 81
7.7%
Other values (3) 81
7.7%

2014
Text

Distinct102
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:49.714420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.2638889
Min length1

Characters and Unicode

Total characters1046
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)68.1%

Sample

1st row690779.9182
2nd row644902.0978
3rd row595638.8481
4th row591546.8641
5th row258467.3973
ValueCountFrequency (%)
0 40
27.8%
47860.79689 2
 
1.4%
145.66962 2
 
1.4%
37979.31329 2
 
1.4%
4140.40391 1
 
0.7%
1146.4379 1
 
0.7%
2363.47818 1
 
0.7%
2902.16773 1
 
0.7%
5265.64592 1
 
0.7%
37.08676 1
 
0.7%
Other values (92) 92
63.9%
2024-01-14T22:43:50.069628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 109
10.4%
0 108
10.3%
1 108
10.3%
. 103
9.8%
2 103
9.8%
9 93
8.9%
6 89
8.5%
4 88
8.4%
7 87
8.3%
5 76
7.3%
Other values (3) 82
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 935
89.4%
Other Punctuation 103
 
9.8%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 109
11.7%
0 108
11.6%
1 108
11.6%
2 103
11.0%
9 93
9.9%
6 89
9.5%
4 88
9.4%
7 87
9.3%
5 76
8.1%
8 74
7.9%
Other Punctuation
ValueCountFrequency (%)
. 103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1045
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
3 109
10.4%
0 108
10.3%
1 108
10.3%
. 103
9.9%
2 103
9.9%
9 93
8.9%
6 89
8.5%
4 88
8.4%
7 87
8.3%
5 76
7.3%
Other values (2) 81
7.8%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1046
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 109
10.4%
0 108
10.3%
1 108
10.3%
. 103
9.8%
2 103
9.8%
9 93
8.9%
6 89
8.5%
4 88
8.4%
7 87
8.3%
5 76
7.3%
Other values (3) 82
7.8%

2015
Text

Distinct102
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:50.568525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.2013889
Min length1

Characters and Unicode

Total characters1037
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)68.1%

Sample

1st row691341.064
2nd row644769.2334
3rd row598980.4876
4th row595216.3385
5th row260499.4136
ValueCountFrequency (%)
0 40
27.8%
48504.59791 2
 
1.4%
116.88597 2
 
1.4%
41037.238 2
 
1.4%
3979.89484 1
 
0.7%
1165.77008 1
 
0.7%
2353.40606 1
 
0.7%
2890.33857 1
 
0.7%
5243.74463 1
 
0.7%
31.11873 1
 
0.7%
Other values (92) 92
63.9%
2024-01-14T22:43:50.893371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 119
11.5%
1 104
10.0%
. 103
9.9%
3 98
9.5%
8 97
9.4%
9 88
8.5%
7 88
8.5%
5 84
8.1%
2 84
8.1%
6 83
8.0%
Other values (3) 89
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 926
89.3%
Other Punctuation 103
 
9.9%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 119
12.9%
1 104
11.2%
3 98
10.6%
8 97
10.5%
9 88
9.5%
7 88
9.5%
5 84
9.1%
2 84
9.1%
6 83
9.0%
4 81
8.7%
Other Punctuation
ValueCountFrequency (%)
. 103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1036
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 119
11.5%
1 104
10.0%
. 103
9.9%
3 98
9.5%
8 97
9.4%
9 88
8.5%
7 88
8.5%
5 84
8.1%
2 84
8.1%
6 83
8.0%
Other values (2) 88
8.5%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1037
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 119
11.5%
1 104
10.0%
. 103
9.9%
3 98
9.5%
8 97
9.4%
9 88
8.5%
7 88
8.5%
5 84
8.1%
2 84
8.1%
6 83
8.0%
Other values (3) 89
8.6%

2016
Text

Distinct102
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:51.237768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.2222222
Min length1

Characters and Unicode

Total characters1040
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)68.1%

Sample

1st row692409.7748
2nd row645467.1697
3rd row600950.3384
4th row597053.6794
5th row262104.2996
ValueCountFrequency (%)
0 40
27.8%
48732.42453 2
 
1.4%
86.01122 2
 
1.4%
46090.82752 2
 
1.4%
3946.02573 1
 
0.7%
1187.87676 1
 
0.7%
2355.15978 1
 
0.7%
2891.01328 1
 
0.7%
5246.17306 1
 
0.7%
31.18076 1
 
0.7%
Other values (92) 92
63.9%
2024-01-14T22:43:51.713368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 122
11.7%
6 115
11.1%
1 107
10.3%
. 103
9.9%
2 97
9.3%
7 88
8.5%
4 86
8.3%
5 86
8.3%
3 84
8.1%
9 79
7.6%
Other values (3) 73
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 929
89.3%
Other Punctuation 103
 
9.9%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 122
13.1%
6 115
12.4%
1 107
11.5%
2 97
10.4%
7 88
9.5%
4 86
9.3%
5 86
9.3%
3 84
9.0%
9 79
8.5%
8 65
7.0%
Other Punctuation
ValueCountFrequency (%)
. 103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1039
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 122
11.7%
6 115
11.1%
1 107
10.3%
. 103
9.9%
2 97
9.3%
7 88
8.5%
4 86
8.3%
5 86
8.3%
3 84
8.1%
9 79
7.6%
Other values (2) 72
6.9%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1040
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 122
11.7%
6 115
11.1%
1 107
10.3%
. 103
9.9%
2 97
9.3%
7 88
8.5%
4 86
8.3%
5 86
8.3%
3 84
8.1%
9 79
7.6%
Other values (3) 73
7.0%

2017
Text

Distinct102
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:52.028215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.1875
Min length1

Characters and Unicode

Total characters1035
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)68.1%

Sample

1st row709422.2959
2nd row667721.0017
3rd row614421.6579
4th row610445.1996
5th row269764.271
ValueCountFrequency (%)
0 40
27.8%
43830.84957 2
 
1.4%
54.04751 2
 
1.4%
47007.15607 2
 
1.4%
3997.50642 1
 
0.7%
1374.89432 1
 
0.7%
2391.62456 1
 
0.7%
2939.75392 1
 
0.7%
5331.37848 1
 
0.7%
31.30941 1
 
0.7%
Other values (92) 92
63.9%
2024-01-14T22:43:52.524026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 116
11.2%
1 114
11.0%
. 103
10.0%
7 98
9.5%
3 96
9.3%
6 95
9.2%
4 92
8.9%
2 88
8.5%
5 77
7.4%
8 77
7.4%
Other values (3) 79
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 924
89.3%
Other Punctuation 103
 
10.0%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 116
12.6%
1 114
12.3%
7 98
10.6%
3 96
10.4%
6 95
10.3%
4 92
10.0%
2 88
9.5%
5 77
8.3%
8 77
8.3%
9 71
7.7%
Other Punctuation
ValueCountFrequency (%)
. 103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1034
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 116
11.2%
1 114
11.0%
. 103
10.0%
7 98
9.5%
3 96
9.3%
6 95
9.2%
4 92
8.9%
2 88
8.5%
5 77
7.4%
8 77
7.4%
Other values (2) 78
7.5%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1035
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 116
11.2%
1 114
11.0%
. 103
10.0%
7 98
9.5%
3 96
9.3%
6 95
9.2%
4 92
8.9%
2 88
8.5%
5 77
7.4%
8 77
7.4%
Other values (3) 79
7.6%

2018
Text

Distinct102
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:53.049966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.2013889
Min length1

Characters and Unicode

Total characters1037
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)68.1%

Sample

1st row725027.2814
2nd row684683.6421
3rd row630679.1767
4th row626251.9608
5th row286398.7255
ValueCountFrequency (%)
0 40
27.8%
42690.77525 2
 
1.4%
35.18527 2
 
1.4%
46129.5347 2
 
1.4%
4054.4485 1
 
0.7%
1399.78384 1
 
0.7%
2449.51905 1
 
0.7%
3012.85663 1
 
0.7%
5462.37569 1
 
0.7%
29.72283 1
 
0.7%
Other values (92) 92
63.9%
2024-01-14T22:43:53.602130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 111
10.7%
4 104
10.0%
. 103
9.9%
2 95
9.2%
3 93
9.0%
1 93
9.0%
5 90
8.7%
6 88
8.5%
9 87
8.4%
8 85
8.2%
Other values (3) 88
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 926
89.3%
Other Punctuation 103
 
9.9%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 111
12.0%
4 104
11.2%
2 95
10.3%
3 93
10.0%
1 93
10.0%
5 90
9.7%
6 88
9.5%
9 87
9.4%
8 85
9.2%
7 80
8.6%
Other Punctuation
ValueCountFrequency (%)
. 103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1036
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 111
10.7%
4 104
10.0%
. 103
9.9%
2 95
9.2%
3 93
9.0%
1 93
9.0%
5 90
8.7%
6 88
8.5%
9 87
8.4%
8 85
8.2%
Other values (2) 87
8.4%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1037
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 111
10.7%
4 104
10.0%
. 103
9.9%
2 95
9.2%
3 93
9.0%
1 93
9.0%
5 90
8.7%
6 88
8.5%
9 87
8.4%
8 85
8.2%
Other values (3) 88
8.5%

2019
Text

Distinct102
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:53.937293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.1666667
Min length1

Characters and Unicode

Total characters1032
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)68.1%

Sample

1st row699213.6702
2nd row661493.553
3rd row609566.834
4th row605369.3132
5th row266224.5553
ValueCountFrequency (%)
0 40
27.8%
40261.67374 2
 
1.4%
23.15117 2
 
1.4%
42104.05441 2
 
1.4%
4163.83635 1
 
0.7%
1277.03584 1
 
0.7%
2485.98596 1
 
0.7%
3063.29707 1
 
0.7%
5549.28303 1
 
0.7%
25.34778 1
 
0.7%
Other values (92) 92
63.9%
2024-01-14T22:43:54.459854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 106
10.3%
3 106
10.3%
. 103
10.0%
5 103
10.0%
2 102
9.9%
1 94
9.1%
4 94
9.1%
8 84
8.1%
6 78
7.6%
9 78
7.6%
Other values (3) 84
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 921
89.2%
Other Punctuation 103
 
10.0%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 106
11.5%
3 106
11.5%
5 103
11.2%
2 102
11.1%
1 94
10.2%
4 94
10.2%
8 84
9.1%
6 78
8.5%
9 78
8.5%
7 76
8.3%
Other Punctuation
ValueCountFrequency (%)
. 103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1031
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 106
10.3%
3 106
10.3%
. 103
10.0%
5 103
10.0%
2 102
9.9%
1 94
9.1%
4 94
9.1%
8 84
8.1%
6 78
7.6%
9 78
7.6%
Other values (2) 83
8.1%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1032
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 106
10.3%
3 106
10.3%
. 103
10.0%
5 103
10.0%
2 102
9.9%
1 94
9.1%
4 94
9.1%
8 84
8.1%
6 78
7.6%
9 78
7.6%
Other values (3) 84
8.1%

2020
Text

Distinct102
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:54.787688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.1388889
Min length1

Characters and Unicode

Total characters1028
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)68.1%

Sample

1st row654445.4591
2nd row616558.8974
3rd row568060.442
4th row563854.3119
5th row237037.5124
ValueCountFrequency (%)
0 40
27.8%
40521.96255 2
 
1.4%
15.50046 2
 
1.4%
41692.27191 2
 
1.4%
4320.66567 1
 
0.7%
1340.72015 1
 
0.7%
2506.95329 1
 
0.7%
3096.37165 1
 
0.7%
5603.32494 1
 
0.7%
22.15082 1
 
0.7%
Other values (92) 92
63.9%
2024-01-14T22:43:55.314651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 121
11.8%
0 112
10.9%
. 103
10.0%
2 97
9.4%
5 92
8.9%
3 91
8.9%
6 90
8.8%
4 89
8.7%
7 86
8.4%
9 78
7.6%
Other values (3) 69
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 917
89.2%
Other Punctuation 103
 
10.0%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 121
13.2%
0 112
12.2%
2 97
10.6%
5 92
10.0%
3 91
9.9%
6 90
9.8%
4 89
9.7%
7 86
9.4%
9 78
8.5%
8 61
6.7%
Other Punctuation
ValueCountFrequency (%)
. 103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1027
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 121
11.8%
0 112
10.9%
. 103
10.0%
2 97
9.4%
5 92
9.0%
3 91
8.9%
6 90
8.8%
4 89
8.7%
7 86
8.4%
9 78
7.6%
Other values (2) 68
6.6%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1028
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 121
11.8%
0 112
10.9%
. 103
10.0%
2 97
9.4%
5 92
8.9%
3 91
8.9%
6 90
8.8%
4 89
8.7%
7 86
8.4%
9 78
7.6%
Other values (3) 69
6.7%

2021
Text

Distinct102
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-01-14T22:43:55.710378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.1319444
Min length1

Characters and Unicode

Total characters1027
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)68.1%

Sample

1st row676647.9049
2nd row638881.5876
3rd row587730.603
4th row583183.4266
5th row241080.4824
ValueCountFrequency (%)
0 40
27.8%
40388.58252 2
 
1.4%
6.6776 2
 
1.4%
41518.60035 2
 
1.4%
4487.44969 1
 
0.7%
1433.3201 1
 
0.7%
2538.01973 1
 
0.7%
3144.10973 1
 
0.7%
5682.12946 1
 
0.7%
19.05425 1
 
0.7%
Other values (92) 92
63.9%
2024-01-14T22:43:56.290481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 111
10.8%
. 103
10.0%
6 99
9.6%
1 96
9.3%
3 94
9.2%
4 93
9.1%
7 91
8.9%
5 89
8.7%
2 88
8.6%
8 87
8.5%
Other values (3) 76
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 916
89.2%
Other Punctuation 103
 
10.0%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 111
12.1%
6 99
10.8%
1 96
10.5%
3 94
10.3%
4 93
10.2%
7 91
9.9%
5 89
9.7%
2 88
9.6%
8 87
9.5%
9 68
7.4%
Other Punctuation
ValueCountFrequency (%)
. 103
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1026
99.9%
Latin 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 111
10.8%
. 103
10.0%
6 99
9.6%
1 96
9.4%
3 94
9.2%
4 93
9.1%
7 91
8.9%
5 89
8.7%
2 88
8.6%
8 87
8.5%
Other values (2) 75
7.3%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1027
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 111
10.8%
. 103
10.0%
6 99
9.6%
1 96
9.3%
3 94
9.2%
4 93
9.1%
7 91
8.9%
5 89
8.7%
2 88
8.6%
8 87
8.5%
Other values (3) 76
7.4%

Sample

분야 및 연도19901991199219931994199519961997199819992000200120022003200420052006200720082009201020112012201320142015201620172018201920202021
0총배출량(Gg CO2eq)292105.0629315352.6113343354.1466378545.9775403568.6135433787.9248470280.3003501912.2509431434.4559469414.8284502730.4499516008.7176538458.0707548808.4335557042.8239561483.3645566903.4416580196.1504593540.7176597319.369655106.2989683798.1228687004.9777695715.3019690779.9182691341.064692409.7748709422.2959725027.2814699213.6702654445.4591676647.9049
1순배출량254159.2211281385.5253310216.9541346994.152369637.16401626.6678434432.7187461298.0841382505.5031412334.4732442635.7351456469.1168481101.1682491936.6703498765.4611505161.0965509455.9762522071.0537534495.4289538470.5269599016.3944628553.1186637740.4591650683.8509644902.0978644769.2334645467.1697667721.0017684683.6421661493.553616558.8974638881.5876
2에너지240294.4846258113.1879278995.6349308499.8086327799.6796352000.6819385582.1095411617.5285351493.3078382112.7798411584.709425928.6322445254.6332452962.4605460054.6416469333.9397474631.2588492132.3822506048.645512320.7746564678.6543593697.4135594966.1118602945.0458595638.8481598980.4876600950.3384614421.6579630679.1767609566.834568060.442587730.603
3A 연료연소235182.2214253554.4804275205.9382305340.2473325066.5825349613.2315383185.792409141.4023349141.9397379577.0706408915.2528423225.0276442541.4214450177.558456994.3356466222.8311471460.9285488738.268502596.7916509073.8462560898.2916589656.8136590615.4887598474.7796591546.8641595216.3385597053.6794610445.1996626251.9608605369.3132563854.3119583183.4266
4A 연료연소_1 에너지산업48351.2028454790.0688562374.8994368765.1203283606.2114291684.69032108977.7905122325.2001106295.165116150.2112136124.2042147477.0262155764.2695159992.5131172849.3016179003.7325185847.1288197249.6164210717.5452229408.9519254797.297262387.6224266405.6356272977.0572258467.3973260499.4136262104.2996269764.271286398.7255266224.5553237037.5124241080.4824
5A 연료연소_1 에너지산업_a 공공전기 및 열 생산36575.2483242684.3066550111.9451156338.831271011.1102178688.0282895316.81269107294.304491114.0321100604.4665120214.7407131396.3269140828.372144871.8738156494.4203162906.147170054.0406181313.0872192998.1396212377.7119239287.6199246092.5675249479.0795256140.3434241712.3089242127.8139242482.4401251381.469268355.6091248745.7564218065.4522223656.5538
6A 연료연소_1 에너지산업_b 석유정제11313.2826411603.4959211668.0520811884.3823911953.4589312366.6387912838.4579213283.0165613243.4452213678.7402513791.0218213723.6082513504.3662513278.4052613348.1602113583.8560113738.1135213963.3524715528.6438714626.3441513035.0616114056.0817514658.0748314592.2835714889.2121316573.2812217916.0179615847.6049515858.2861315364.4945815173.2655814013.5573
7A 연료연소_1 에너지산업_c 고체연료 제조 및 기타 에너지 산업462.67187502.26628594.90224541.90673641.64228630.02325822.519841747.879191937.687631867.004452118.44162357.091081431.531281842.234053006.721052513.729492054.974631973.176782190.761732404.89592474.615452238.973172268.481312244.430221865.876281798.318471705.841572535.197042184.830242114.304343798.794723410.37127
8A 연료연소_2 제조업 및 건설업76558.1150888000.4274497959.05543108051.2625112797.2093115848.4307124012.8477129601.7618120270.7516125754.7273130644.9286131298.2824137369.8176139700.7857137412.3659137891.9959139452.3154144299.6378149315.9962138744.3666162915.0655184640.0992180535.3677182059.619193760.9184188485.3573182566.1092187755.9637188048.7597187608.8323181711.1211194347.7475
9A 연료연소_2 제조업 및 건설업_a 철강30929.0651435743.4081738901.2039543578.2960842776.0029744917.3461447438.792847944.0741348259.5922650243.4103652156.3726651991.0767253997.2441154892.2735656180.2895657086.0702761859.7370663074.9031168743.4224860073.6117777756.2657190665.6208690217.0858290606.82187105262.6594102034.438894503.20697100662.630696499.1466396436.5326393136.8461296946.24836
분야 및 연도19901991199219931994199519961997199819992000200120022003200420052006200720082009201020112012201320142015201620172018201920202021
134B 하폐수처리_1 폐수처리73.8566288.50258112.8768130.45716177.52923211.5168116.03172112.8128795.26569116.26549116.26549137.26529161.7545164.55486129.67451182.36991120.24074229.4133214.23304213.26103261.79778458.81846298.10384397.55364346.3379279.96023375.65621480.84379321.96346135.56845172.6252471.93024
135B 하폐수처리_2 하수처리1398.78441438.1411523.033421323.708111662.481661637.368541644.052361503.730081547.37951520.393281506.722911526.248091563.771841502.803131474.75931562.870441456.240011413.310511361.137611377.168311435.438051443.275481418.361411394.644711373.295351416.215711399.806791385.643831403.237741405.555651398.286391366.80312
136C 폐기물소각1429.312111920.014612381.194642901.235393065.528894172.939394728.711535240.985834903.070635725.23667634.599188068.989726924.045396986.436566973.878275989.665576626.293935928.0795864.783785697.267845614.117046175.470666811.134696951.779686303.300956836.548137116.550357148.258837067.156286406.801216593.226036326.01861
137D 기타000014.345021.717455.2893815.7541515.1440554.34309106.46587105.02142157.49361157.95252163.94993237.84803287.28827305.33248314.54419335.82386285.5964338.67229356.91895430.21646491.11272623.28354692.87316699.2997790.48552837.16384787.88439810.74957
138별도항목(Memo Item)00000000000000000000000000000000
139C 국제벙커링 및 다국적 작전13947.2920716767.6781920811.8302722053.6083625421.086829288.3945734901.2711338303.1395637885.5339640983.0974338853.0634237972.8332738058.6139240698.5780542483.5160742937.6365241005.4718241604.0086139131.8988635925.9828138444.2851638168.1548237410.4275437434.4618737979.3132941037.23846090.8275247007.1560746129.534742104.0544141692.2719141518.60035
140C 국제벙커링 및 다국적 작전_1 벙커링13947.2920716767.6781920811.8302722053.6083625421.086829288.3945734901.2711338303.1395637885.5339640983.0974338853.0634237972.8332738058.6139240698.5780542483.5160742937.6365241005.4718241604.0086139131.8988635925.9828138444.2851638168.1548237410.4275437434.4618737979.3132941037.23846090.8275247007.1560746129.534742104.0544141692.2719141518.60035
141C 국제벙커링 및 다국적 작전_1 벙커링_a 국제 항공6244.182234259.296345094.723365632.112296324.9247151.513897815.414318510.525877053.29157281.224067685.549248053.890419097.044869560.8482410189.1430610603.921498598.5367612112.9847311051.2296710526.3029311718.915211819.0948211908.213312573.3383312603.6903912962.1546614480.2607914833.606315628.8404115926.328349941.900417810.97608
142C 국제벙커링 및 다국적 작전_1 벙커링_b 국제 해운7703.1098412508.3818515717.1069116421.4960719096.162822136.8806727085.8568229792.613730832.2424633701.8733731167.5141829918.9428728961.5690631137.7298132294.3730132333.7150432406.9350629491.0238728080.6691925399.6798826725.3699626349.0625502.2142424861.1235425375.6229128075.0833431610.5667332173.5497830500.6942926177.7260731750.371533707.62427
143C 국제벙커링 및 다국적 작전_2 다국적 작전CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC