Overview

Dataset statistics

Number of variables54
Number of observations73
Missing cells146
Missing cells (%)3.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.1 KiB
Average record size in memory436.8 B

Variable types

Numeric1
Text47
Unsupported2
Categorical3
DateTime1

Alerts

last_load_dttm has constant value ""Constant
answer_gubun is highly imbalanced (54.4%)Imbalance
job_student has 73 (100.0%) missing valuesMissing
income_100 has 73 (100.0%) missing valuesMissing
job_student is an unsupported type, check if it needs cleaning or further analysisUnsupported
income_100 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-17 14:25:46.876564
Analysis finished2024-04-17 14:25:47.822857
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

total
Real number (ℝ)

Distinct70
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4942.0252
Minimum1
Maximum87848
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2024-04-17T23:25:47.892477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.086
Q175
median247
Q3869
95-th percentile24157.2
Maximum87848
Range87847
Interquartile range (IQR)794

Descriptive statistics

Standard deviation17321.262
Coefficient of variation (CV)3.5048915
Kurtosis17.137018
Mean4942.0252
Median Absolute Deviation (MAD)241.67
Skewness4.2287891
Sum360767.84
Variance3.0002613 × 108
MonotonicityNot monotonic
2024-04-17T23:25:48.012193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.44 2
 
2.7%
1.0 2
 
2.7%
5.2 2
 
2.7%
303.0 1
 
1.4%
104.0 1
 
1.4%
408.0 1
 
1.4%
109.0 1
 
1.4%
36.0 1
 
1.4%
425.0 1
 
1.4%
2000.0 1
 
1.4%
Other values (60) 60
82.2%
ValueCountFrequency (%)
1.0 2
2.7%
4.82 1
1.4%
5.02 1
1.4%
5.13 1
1.4%
5.2 2
2.7%
5.33 1
1.4%
5.34 1
1.4%
5.35 1
1.4%
5.44 2
2.7%
5.57 1
1.4%
ValueCountFrequency (%)
87848.0 1
1.4%
86256.0 1
1.4%
77554.0 1
1.4%
42786.0 1
1.4%
11738.0 1
1.4%
10629.0 1
1.4%
8069.0 1
1.4%
4586.0 1
1.4%
3837.0 1
1.4%
2000.0 1
1.4%
Distinct68
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:48.248333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.2328767
Min length3

Characters and Unicode

Total characters309
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)86.3%

Sample

1st row12053
2nd row6390
3rd row1979
4th row13457
5th row887
ValueCountFrequency (%)
3.3 2
 
2.7%
2.9 2
 
2.7%
4.1 2
 
2.7%
5.7 2
 
2.7%
3.8 2
 
2.7%
73774 1
 
1.4%
826 1
 
1.4%
91940 1
 
1.4%
4.5 1
 
1.4%
43920 1
 
1.4%
Other values (58) 58
79.5%
2024-04-17T23:25:48.596634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.1%
% 48
15.5%
7 24
7.8%
1 23
 
7.4%
3 22
 
7.1%
2 21
 
6.8%
4 21
 
6.8%
5 21
 
6.8%
9 19
 
6.1%
6 19
 
6.1%
Other values (2) 32
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 202
65.4%
Other Punctuation 107
34.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 24
11.9%
1 23
11.4%
3 22
10.9%
2 21
10.4%
4 21
10.4%
5 21
10.4%
9 19
9.4%
6 19
9.4%
8 16
7.9%
0 16
7.9%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 309
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.1%
% 48
15.5%
7 24
7.8%
1 23
 
7.4%
3 22
 
7.1%
2 21
 
6.8%
4 21
 
6.8%
5 21
 
6.8%
9 19
 
6.1%
6 19
 
6.1%
Other values (2) 32
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 309
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.1%
% 48
15.5%
7 24
7.8%
1 23
 
7.4%
3 22
 
7.1%
2 21
 
6.8%
4 21
 
6.8%
5 21
 
6.8%
9 19
 
6.1%
6 19
 
6.1%
Other values (2) 32
10.4%
Distinct65
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:48.816880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.260274
Min length4

Characters and Unicode

Total characters311
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)82.2%

Sample

1st row4862
2nd row3135
3rd row1232
4th row8354
5th row1106
ValueCountFrequency (%)
3.5 3
 
4.1%
5.2 3
 
4.1%
7.6 3
 
4.1%
5.8 2
 
2.7%
3.7 2
 
2.7%
41873 1
 
1.4%
21.9 1
 
1.4%
1110 1
 
1.4%
80598 1
 
1.4%
6.3 1
 
1.4%
Other values (55) 55
75.3%
2024-04-17T23:25:49.154077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.0%
% 48
15.4%
5 30
9.6%
1 30
9.6%
7 23
 
7.4%
2 23
 
7.4%
4 21
 
6.8%
3 18
 
5.8%
6 17
 
5.5%
0 15
 
4.8%
Other values (2) 27
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 204
65.6%
Other Punctuation 107
34.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 30
14.7%
1 30
14.7%
7 23
11.3%
2 23
11.3%
4 21
10.3%
3 18
8.8%
6 17
8.3%
0 15
7.4%
8 14
6.9%
9 13
6.4%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 311
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.0%
% 48
15.4%
5 30
9.6%
1 30
9.6%
7 23
 
7.4%
2 23
 
7.4%
4 21
 
6.8%
3 18
 
5.8%
6 17
 
5.5%
0 15
 
4.8%
Other values (2) 27
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 311
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.0%
% 48
15.4%
5 30
9.6%
1 30
9.6%
7 23
 
7.4%
2 23
 
7.4%
4 21
 
6.8%
3 18
 
5.8%
6 17
 
5.5%
0 15
 
4.8%
Other values (2) 27
8.7%
Distinct69
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:49.380447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.1643836
Min length3

Characters and Unicode

Total characters304
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)89.0%

Sample

1st row4416
2nd row2249
3rd row488
4th row4081
5th row421
ValueCountFrequency (%)
0.0 2
 
2.7%
6.2 2
 
2.7%
421 2
 
2.7%
12.1 2
 
2.7%
21.9 1
 
1.4%
2.1 1
 
1.4%
17.3 1
 
1.4%
61205 1
 
1.4%
69131 1
 
1.4%
18059 1
 
1.4%
Other values (59) 59
80.8%
2024-04-17T23:25:49.739644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.4%
% 48
15.8%
1 32
10.5%
2 28
9.2%
5 24
7.9%
0 21
 
6.9%
4 20
 
6.6%
3 16
 
5.3%
7 16
 
5.3%
6 14
 
4.6%
Other values (2) 26
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 197
64.8%
Other Punctuation 107
35.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 32
16.2%
2 28
14.2%
5 24
12.2%
0 21
10.7%
4 20
10.2%
3 16
8.1%
7 16
8.1%
6 14
7.1%
8 13
6.6%
9 13
6.6%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 304
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.4%
% 48
15.8%
1 32
10.5%
2 28
9.2%
5 24
7.9%
0 21
 
6.9%
4 20
 
6.6%
3 16
 
5.3%
7 16
 
5.3%
6 14
 
4.6%
Other values (2) 26
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 304
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.4%
% 48
15.8%
1 32
10.5%
2 28
9.2%
5 24
7.9%
0 21
 
6.9%
4 20
 
6.6%
3 16
 
5.3%
7 16
 
5.3%
6 14
 
4.6%
Other values (2) 26
8.6%
Distinct65
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:49.953768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.2191781
Min length3

Characters and Unicode

Total characters308
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)79.5%

Sample

1st row11887
2nd row5548
3rd row1556
4th row9444
5th row557
ValueCountFrequency (%)
4.7 3
 
4.1%
12.6 2
 
2.7%
5.29 2
 
2.7%
3.9 2
 
2.7%
0.0 2
 
2.7%
3.6 2
 
2.7%
6.0 2
 
2.7%
80290 1
 
1.4%
11.9 1
 
1.4%
522 1
 
1.4%
Other values (55) 55
75.3%
2024-04-17T23:25:50.292502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
5 33
10.7%
1 27
8.8%
4 25
8.1%
2 24
7.8%
0 18
 
5.8%
3 17
 
5.5%
8 16
 
5.2%
7 14
 
4.5%
Other values (2) 27
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 201
65.3%
Other Punctuation 107
34.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 33
16.4%
1 27
13.4%
4 25
12.4%
2 24
11.9%
0 18
9.0%
3 17
8.5%
8 16
8.0%
7 14
7.0%
9 14
7.0%
6 13
 
6.5%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 308
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
5 33
10.7%
1 27
8.8%
4 25
8.1%
2 24
7.8%
0 18
 
5.8%
3 17
 
5.5%
8 16
 
5.2%
7 14
 
4.5%
Other values (2) 27
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 308
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
5 33
10.7%
1 27
8.8%
4 25
8.1%
2 24
7.8%
0 18
 
5.8%
3 17
 
5.5%
8 16
 
5.2%
7 14
 
4.5%
Other values (2) 27
8.8%
Distinct65
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:50.512779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.2328767
Min length3

Characters and Unicode

Total characters309
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)78.1%

Sample

1st row5193
2nd row3973
3rd row2729
4th row10459
5th row451
ValueCountFrequency (%)
0.0 2
 
2.7%
7.2 2
 
2.7%
5.4 2
 
2.7%
6.1 2
 
2.7%
1.8 2
 
2.7%
4.0 2
 
2.7%
20.1 2
 
2.7%
6.2 2
 
2.7%
5193 1
 
1.4%
5.0 1
 
1.4%
Other values (55) 55
75.3%
2024-04-17T23:25:50.851132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.1%
% 48
15.5%
1 33
10.7%
5 29
9.4%
2 25
8.1%
4 25
8.1%
3 21
 
6.8%
0 18
 
5.8%
9 16
 
5.2%
6 15
 
4.9%
Other values (2) 20
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 202
65.4%
Other Punctuation 107
34.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 33
16.3%
5 29
14.4%
2 25
12.4%
4 25
12.4%
3 21
10.4%
0 18
8.9%
9 16
7.9%
6 15
7.4%
7 11
 
5.4%
8 9
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 309
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.1%
% 48
15.5%
1 33
10.7%
5 29
9.4%
2 25
8.1%
4 25
8.1%
3 21
 
6.8%
0 18
 
5.8%
9 16
 
5.2%
6 15
 
4.9%
Other values (2) 20
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 309
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.1%
% 48
15.5%
1 33
10.7%
5 29
9.4%
2 25
8.1%
4 25
8.1%
3 21
 
6.8%
0 18
 
5.8%
9 16
 
5.2%
6 15
 
4.9%
Other values (2) 20
 
6.5%
Distinct62
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:51.066651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.2054795
Min length3

Characters and Unicode

Total characters307
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)72.6%

Sample

1st row8237
2nd row6399
3rd row1532
4th row16749
5th row370
ValueCountFrequency (%)
6.5 3
 
4.1%
3.8 3
 
4.1%
7.2 2
 
2.7%
3.3 2
 
2.7%
5.43 2
 
2.7%
18.0 2
 
2.7%
5.26 2
 
2.7%
0.0 2
 
2.7%
1.1 2
 
2.7%
17.6 1
 
1.4%
Other values (52) 52
71.2%
2024-04-17T23:25:51.399347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
3 30
9.8%
5 29
9.4%
2 24
7.8%
1 23
 
7.5%
6 21
 
6.8%
8 18
 
5.9%
0 15
 
4.9%
7 14
 
4.6%
Other values (2) 26
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 200
65.1%
Other Punctuation 107
34.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 30
15.0%
5 29
14.5%
2 24
12.0%
1 23
11.5%
6 21
10.5%
8 18
9.0%
0 15
7.5%
7 14
7.0%
4 14
7.0%
9 12
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 307
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
3 30
9.8%
5 29
9.4%
2 24
7.8%
1 23
 
7.5%
6 21
 
6.8%
8 18
 
5.9%
0 15
 
4.9%
7 14
 
4.6%
Other values (2) 26
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
3 30
9.8%
5 29
9.4%
2 24
7.8%
1 23
 
7.5%
6 21
 
6.8%
8 18
 
5.9%
0 15
 
4.9%
7 14
 
4.6%
Other values (2) 26
8.5%
Distinct63
Distinct (%)86.3%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:51.607930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.2054795
Min length3

Characters and Unicode

Total characters307
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)76.7%

Sample

1st row11818
2nd row5030
3rd row1394
4th row18079
5th row194
ValueCountFrequency (%)
0.5 4
 
5.5%
2.1 3
 
4.1%
5.30 2
 
2.7%
4.1 2
 
2.7%
4.7 2
 
2.7%
5.22 2
 
2.7%
3.4 2
 
2.7%
64975 1
 
1.4%
64970 1
 
1.4%
86964 1
 
1.4%
Other values (53) 53
72.6%
2024-04-17T23:25:51.934033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
1 28
9.1%
4 26
8.5%
5 25
8.1%
2 23
 
7.5%
0 21
 
6.8%
9 20
 
6.5%
7 17
 
5.5%
8 15
 
4.9%
Other values (2) 25
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 200
65.1%
Other Punctuation 107
34.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 28
14.0%
4 26
13.0%
5 25
12.5%
2 23
11.5%
0 21
10.5%
9 20
10.0%
7 17
8.5%
8 15
7.5%
3 13
6.5%
6 12
6.0%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 307
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
1 28
9.1%
4 26
8.5%
5 25
8.1%
2 23
 
7.5%
0 21
 
6.8%
9 20
 
6.5%
7 17
 
5.5%
8 15
 
4.9%
Other values (2) 25
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
1 28
9.1%
4 26
8.5%
5 25
8.1%
2 23
 
7.5%
0 21
 
6.8%
9 20
 
6.5%
7 17
 
5.5%
8 15
 
4.9%
Other values (2) 25
8.1%
Distinct64
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:52.153709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.2739726
Min length4

Characters and Unicode

Total characters312
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)75.3%

Sample

1st row8399
2nd row4479
3rd row1852
4th row12905
5th row1186
ValueCountFrequency (%)
21.4 2
 
2.7%
3.7 2
 
2.7%
5.0 2
 
2.7%
6.9 2
 
2.7%
5.19 2
 
2.7%
5.1 2
 
2.7%
7.3 2
 
2.7%
3.6 2
 
2.7%
2.0 2
 
2.7%
5.2 1
 
1.4%
Other values (54) 54
74.0%
2024-04-17T23:25:52.465867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
18.9%
% 48
15.4%
1 32
10.3%
5 29
9.3%
4 22
 
7.1%
3 21
 
6.7%
2 20
 
6.4%
0 19
 
6.1%
9 18
 
5.8%
7 17
 
5.4%
Other values (2) 27
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 205
65.7%
Other Punctuation 107
34.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 32
15.6%
5 29
14.1%
4 22
10.7%
3 21
10.2%
2 20
9.8%
0 19
9.3%
9 18
8.8%
7 17
8.3%
8 14
6.8%
6 13
6.3%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 312
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
18.9%
% 48
15.4%
1 32
10.3%
5 29
9.3%
4 22
 
7.1%
3 21
 
6.7%
2 20
 
6.4%
0 19
 
6.1%
9 18
 
5.8%
7 17
 
5.4%
Other values (2) 27
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
18.9%
% 48
15.4%
1 32
10.3%
5 29
9.3%
4 22
 
7.1%
3 21
 
6.7%
2 20
 
6.4%
0 19
 
6.1%
9 18
 
5.8%
7 17
 
5.4%
Other values (2) 27
8.7%
Distinct66
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:52.687652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.1917808
Min length3

Characters and Unicode

Total characters306
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)82.2%

Sample

1st row7181
2nd row4535
3rd row1099
4th row7462
5th row772
ValueCountFrequency (%)
4.5 3
 
4.1%
9.3 2
 
2.7%
4.1 2
 
2.7%
5.50 2
 
2.7%
772 2
 
2.7%
7.2 2
 
2.7%
71474 1
 
1.4%
7.9 1
 
1.4%
734 1
 
1.4%
3.4 1
 
1.4%
Other values (56) 56
76.7%
2024-04-17T23:25:53.015033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
2 31
10.1%
5 30
9.8%
4 26
8.5%
1 25
8.2%
7 23
 
7.5%
3 18
 
5.9%
0 16
 
5.2%
9 10
 
3.3%
Other values (2) 20
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 199
65.0%
Other Punctuation 107
35.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 31
15.6%
5 30
15.1%
4 26
13.1%
1 25
12.6%
7 23
11.6%
3 18
9.0%
0 16
8.0%
9 10
 
5.0%
8 10
 
5.0%
6 10
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 306
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
2 31
10.1%
5 30
9.8%
4 26
8.5%
1 25
8.2%
7 23
 
7.5%
3 18
 
5.9%
0 16
 
5.2%
9 10
 
3.3%
Other values (2) 20
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 306
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
2 31
10.1%
5 30
9.8%
4 26
8.5%
1 25
8.2%
7 23
 
7.5%
3 18
 
5.9%
0 16
 
5.2%
9 10
 
3.3%
Other values (2) 20
 
6.5%
Distinct48
Distinct (%)65.8%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:53.200427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.109589
Min length2

Characters and Unicode

Total characters300
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)53.4%

Sample

1st row17742
2nd row9677
3rd row2581
4th row6129
5th row34
ValueCountFrequency (%)
5.9 9
 
12.3%
0.0 6
 
8.2%
2.9 6
 
8.2%
34 3
 
4.1%
4.76 2
 
2.7%
8.8 2
 
2.7%
10.2 2
 
2.7%
38.2 2
 
2.7%
26.5 2
 
2.7%
59677 1
 
1.4%
Other values (38) 38
52.1%
2024-04-17T23:25:53.512422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.7%
% 48
16.0%
5 28
9.3%
2 25
8.3%
9 24
8.0%
0 21
 
7.0%
6 18
 
6.0%
1 18
 
6.0%
8 17
 
5.7%
3 15
 
5.0%
Other values (2) 27
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 193
64.3%
Other Punctuation 107
35.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 28
14.5%
2 25
13.0%
9 24
12.4%
0 21
10.9%
6 18
9.3%
1 18
9.3%
8 17
8.8%
3 15
7.8%
4 15
7.8%
7 12
6.2%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 300
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.7%
% 48
16.0%
5 28
9.3%
2 25
8.3%
9 24
8.0%
0 21
 
7.0%
6 18
 
6.0%
1 18
 
6.0%
8 17
 
5.7%
3 15
 
5.0%
Other values (2) 27
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.7%
% 48
16.0%
5 28
9.3%
2 25
8.3%
9 24
8.0%
0 21
 
7.0%
6 18
 
6.0%
1 18
 
6.0%
8 17
 
5.7%
3 15
 
5.0%
Other values (2) 27
9.0%
Distinct58
Distinct (%)79.5%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:53.720229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.2191781
Min length3

Characters and Unicode

Total characters308
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)61.6%

Sample

1st row20923
2nd row3692
3rd row2477
4th row17962
5th row147
ValueCountFrequency (%)
5.6 3
 
4.1%
0.7 3
 
4.1%
5.4 2
 
2.7%
18.4 2
 
2.7%
2.8 2
 
2.7%
2.0 2
 
2.7%
5.15 2
 
2.7%
3.4 2
 
2.7%
12.5 2
 
2.7%
0.0 2
 
2.7%
Other values (48) 51
69.9%
2024-04-17T23:25:54.042341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
5 28
9.1%
2 28
9.1%
1 27
8.8%
4 24
7.8%
6 18
 
5.8%
0 16
 
5.2%
7 16
 
5.2%
3 16
 
5.2%
Other values (2) 28
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 201
65.3%
Other Punctuation 107
34.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 28
13.9%
2 28
13.9%
1 27
13.4%
4 24
11.9%
6 18
9.0%
0 16
8.0%
7 16
8.0%
3 16
8.0%
9 15
7.5%
8 13
6.5%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 308
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
5 28
9.1%
2 28
9.1%
1 27
8.8%
4 24
7.8%
6 18
 
5.8%
0 16
 
5.2%
7 16
 
5.2%
3 16
 
5.2%
Other values (2) 28
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 308
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
5 28
9.1%
2 28
9.1%
1 27
8.8%
4 24
7.8%
6 18
 
5.8%
0 16
 
5.2%
7 16
 
5.2%
3 16
 
5.2%
Other values (2) 28
9.1%
Distinct62
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:54.253236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.2191781
Min length3

Characters and Unicode

Total characters308
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)75.3%

Sample

1st row6685
2nd row8332
3rd row1983
4th row12405
5th row364
ValueCountFrequency (%)
6.0 3
 
4.1%
2.5 3
 
4.1%
0.0 3
 
4.1%
4.7 3
 
4.1%
7.1 2
 
2.7%
5.6 2
 
2.7%
7.0 2
 
2.7%
343 1
 
1.4%
20.6 1
 
1.4%
27.4 1
 
1.4%
Other values (52) 52
71.2%
2024-04-17T23:25:54.586497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
2 28
9.1%
0 27
8.8%
5 25
8.1%
1 22
 
7.1%
4 20
 
6.5%
7 20
 
6.5%
3 19
 
6.2%
6 17
 
5.5%
Other values (2) 23
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 201
65.3%
Other Punctuation 107
34.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 28
13.9%
0 27
13.4%
5 25
12.4%
1 22
10.9%
4 20
10.0%
7 20
10.0%
3 19
9.5%
6 17
8.5%
8 13
6.5%
9 10
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 308
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
2 28
9.1%
0 27
8.8%
5 25
8.1%
1 22
 
7.1%
4 20
 
6.5%
7 20
 
6.5%
3 19
 
6.2%
6 17
 
5.5%
Other values (2) 23
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 308
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
2 28
9.1%
0 27
8.8%
5 25
8.1%
1 22
 
7.1%
4 20
 
6.5%
7 20
 
6.5%
3 19
 
6.2%
6 17
 
5.5%
Other values (2) 23
 
7.5%
Distinct64
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:54.798281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.1780822
Min length3

Characters and Unicode

Total characters305
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)76.7%

Sample

1st row6667
2nd row3731
3rd row898
4th row9299
5th row392
ValueCountFrequency (%)
3.4 3
 
4.1%
392 2
 
2.7%
12.2 2
 
2.7%
28.6 2
 
2.7%
3.9 2
 
2.7%
5.42 2
 
2.7%
0.3 2
 
2.7%
7.1 2
 
2.7%
24038 1
 
1.4%
4.8 1
 
1.4%
Other values (54) 54
74.0%
2024-04-17T23:25:55.131161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
3 26
8.5%
2 26
8.5%
5 25
8.2%
4 24
7.9%
1 24
7.9%
9 20
 
6.6%
8 15
 
4.9%
6 15
 
4.9%
Other values (2) 23
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 198
64.9%
Other Punctuation 107
35.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 26
13.1%
2 26
13.1%
5 25
12.6%
4 24
12.1%
1 24
12.1%
9 20
10.1%
8 15
7.6%
6 15
7.6%
7 14
7.1%
0 9
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 305
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
3 26
8.5%
2 26
8.5%
5 25
8.2%
4 24
7.9%
1 24
7.9%
9 20
 
6.6%
8 15
 
4.9%
6 15
 
4.9%
Other values (2) 23
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 305
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
3 26
8.5%
2 26
8.5%
5 25
8.2%
4 24
7.9%
1 24
7.9%
9 20
 
6.6%
8 15
 
4.9%
6 15
 
4.9%
Other values (2) 23
 
7.5%
Distinct60
Distinct (%)82.2%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:55.334264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.2191781
Min length3

Characters and Unicode

Total characters308
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)68.5%

Sample

1st row9715
2nd row7500
3rd row4146
4th row13082
5th row170
ValueCountFrequency (%)
4.1 4
 
5.5%
5.9 3
 
4.1%
0.0 2
 
2.7%
2.4 2
 
2.7%
4.7 2
 
2.7%
7.1 2
 
2.7%
1.2 2
 
2.7%
5.16 2
 
2.7%
3.5 2
 
2.7%
170 2
 
2.7%
Other values (50) 50
68.5%
2024-04-17T23:25:55.671059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
1 39
12.7%
5 28
9.1%
4 25
8.1%
0 24
7.8%
7 19
 
6.2%
9 16
 
5.2%
2 16
 
5.2%
6 12
 
3.9%
Other values (2) 22
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 201
65.3%
Other Punctuation 107
34.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 39
19.4%
5 28
13.9%
4 25
12.4%
0 24
11.9%
7 19
9.5%
9 16
8.0%
2 16
8.0%
6 12
 
6.0%
8 12
 
6.0%
3 10
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 308
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
1 39
12.7%
5 28
9.1%
4 25
8.1%
0 24
7.8%
7 19
 
6.2%
9 16
 
5.2%
2 16
 
5.2%
6 12
 
3.9%
Other values (2) 22
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 308
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
1 39
12.7%
5 28
9.1%
4 25
8.1%
0 24
7.8%
7 19
 
6.2%
9 16
 
5.2%
2 16
 
5.2%
6 12
 
3.9%
Other values (2) 22
 
7.1%
Distinct53
Distinct (%)72.6%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:55.867047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.1369863
Min length2

Characters and Unicode

Total characters302
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)60.3%

Sample

1st row4717
2nd row3113
3rd row2264
4th row10755
5th row56
ValueCountFrequency (%)
0.0 8
 
11.0%
7.1 5
 
6.8%
5.24 3
 
4.1%
3.6 3
 
4.1%
6.8 2
 
2.7%
5.02 2
 
2.7%
56 2
 
2.7%
4.9 2
 
2.7%
1.8 2
 
2.7%
8.8 1
 
1.4%
Other values (43) 43
58.9%
2024-04-17T23:25:56.183446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.5%
% 48
15.9%
1 29
9.6%
0 28
9.3%
5 25
8.3%
4 20
 
6.6%
6 20
 
6.6%
2 17
 
5.6%
3 16
 
5.3%
8 15
 
5.0%
Other values (2) 25
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 195
64.6%
Other Punctuation 107
35.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 29
14.9%
0 28
14.4%
5 25
12.8%
4 20
10.3%
6 20
10.3%
2 17
8.7%
3 16
8.2%
8 15
7.7%
7 14
7.2%
9 11
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 302
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.5%
% 48
15.9%
1 29
9.6%
0 28
9.3%
5 25
8.3%
4 20
 
6.6%
6 20
 
6.6%
2 17
 
5.6%
3 16
 
5.3%
8 15
 
5.0%
Other values (2) 25
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 302
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.5%
% 48
15.9%
1 29
9.6%
0 28
9.3%
5 25
8.3%
4 20
 
6.6%
6 20
 
6.6%
2 17
 
5.6%
3 16
 
5.3%
8 15
 
5.0%
Other values (2) 25
8.3%
Distinct42
Distinct (%)57.5%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:56.344240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.109589
Min length2

Characters and Unicode

Total characters300
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)39.7%

Sample

1st row6429
2nd row4286
3rd row6429
4th row7500
5th row16
ValueCountFrequency (%)
0.0 15
20.5%
6.3 5
 
6.8%
6.7 4
 
5.5%
5.13 2
 
2.7%
6429 2
 
2.7%
7.9 2
 
2.7%
22.2 2
 
2.7%
26.7 2
 
2.7%
3.7 2
 
2.7%
31.3 2
 
2.7%
Other values (32) 35
47.9%
2024-04-17T23:25:56.620422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.7%
% 48
16.0%
0 41
13.7%
1 23
 
7.7%
5 23
 
7.7%
6 22
 
7.3%
2 20
 
6.7%
7 17
 
5.7%
3 16
 
5.3%
4 13
 
4.3%
Other values (2) 18
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 193
64.3%
Other Punctuation 107
35.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 41
21.2%
1 23
11.9%
5 23
11.9%
6 22
11.4%
2 20
10.4%
7 17
8.8%
3 16
 
8.3%
4 13
 
6.7%
9 10
 
5.2%
8 8
 
4.1%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 300
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.7%
% 48
16.0%
0 41
13.7%
1 23
 
7.7%
5 23
 
7.7%
6 22
 
7.3%
2 20
 
6.7%
7 17
 
5.7%
3 16
 
5.3%
4 13
 
4.3%
Other values (2) 18
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.7%
% 48
16.0%
0 41
13.7%
1 23
 
7.7%
5 23
 
7.7%
6 22
 
7.3%
2 20
 
6.7%
7 17
 
5.7%
3 16
 
5.3%
4 13
 
4.3%
Other values (2) 18
 
6.0%
Distinct50
Distinct (%)68.5%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:56.803748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.1369863
Min length2

Characters and Unicode

Total characters302
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)52.1%

Sample

1st row10484
2nd row3065
3rd row968
4th row15968
5th row32
ValueCountFrequency (%)
0.0 6
 
8.2%
21.2 4
 
5.5%
9.1 4
 
5.5%
3.0 3
 
4.1%
3.1 3
 
4.1%
4.0 3
 
4.1%
6.1 2
 
2.7%
4.67 2
 
2.7%
7.6 2
 
2.7%
33 2
 
2.7%
Other values (40) 42
57.5%
2024-04-17T23:25:57.098127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.5%
% 48
15.9%
1 35
11.6%
0 27
8.9%
3 24
7.9%
2 21
 
7.0%
5 20
 
6.6%
4 19
 
6.3%
6 17
 
5.6%
9 14
 
4.6%
Other values (2) 18
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 195
64.6%
Other Punctuation 107
35.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 35
17.9%
0 27
13.8%
3 24
12.3%
2 21
10.8%
5 20
10.3%
4 19
9.7%
6 17
8.7%
9 14
 
7.2%
7 10
 
5.1%
8 8
 
4.1%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 302
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.5%
% 48
15.9%
1 35
11.6%
0 27
8.9%
3 24
7.9%
2 21
 
7.0%
5 20
 
6.6%
4 19
 
6.3%
6 17
 
5.6%
9 14
 
4.6%
Other values (2) 18
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 302
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.5%
% 48
15.9%
1 35
11.6%
0 27
8.9%
3 24
7.9%
2 21
 
7.0%
5 20
 
6.6%
4 19
 
6.3%
6 17
 
5.6%
9 14
 
4.6%
Other values (2) 18
 
6.0%
Distinct43
Distinct (%)58.9%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:57.500388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.1780822
Min length2

Characters and Unicode

Total characters305
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)43.8%

Sample

1st row12174
2nd row16087
3rd row5217
4th row28048
5th row24
ValueCountFrequency (%)
4.2 9
 
12.3%
0.0 7
 
9.6%
8.3 4
 
5.5%
12.5 4
 
5.5%
16.7 4
 
5.5%
24 3
 
4.1%
5.25 2
 
2.7%
8.1 2
 
2.7%
4.8 2
 
2.7%
4.9 2
 
2.7%
Other values (33) 34
46.6%
2024-04-17T23:25:57.810122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
2 29
9.5%
4 28
9.2%
5 28
9.2%
0 25
8.2%
1 25
8.2%
7 17
 
5.6%
3 16
 
5.2%
8 14
 
4.6%
Other values (2) 16
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 198
64.9%
Other Punctuation 107
35.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 29
14.6%
4 28
14.1%
5 28
14.1%
0 25
12.6%
1 25
12.6%
7 17
8.6%
3 16
8.1%
8 14
7.1%
6 10
 
5.1%
9 6
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 305
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
2 29
9.5%
4 28
9.2%
5 28
9.2%
0 25
8.2%
1 25
8.2%
7 17
 
5.6%
3 16
 
5.2%
8 14
 
4.6%
Other values (2) 16
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 305
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
2 29
9.5%
4 28
9.2%
5 28
9.2%
0 25
8.2%
1 25
8.2%
7 17
 
5.6%
3 16
 
5.2%
8 14
 
4.6%
Other values (2) 16
 
5.2%
Distinct38
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:57.981174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.109589
Min length1

Characters and Unicode

Total characters300
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)34.2%

Sample

1st row17333
2nd row0
3rd row0
4th row16667
5th row16
ValueCountFrequency (%)
0.0 13
17.8%
6.3 9
 
12.3%
12.5 3
 
4.1%
16 3
 
4.1%
18.8 3
 
4.1%
5.13 3
 
4.1%
4.1 2
 
2.7%
13.5 2
 
2.7%
5.38 2
 
2.7%
5.50 2
 
2.7%
Other values (28) 31
42.5%
2024-04-17T23:25:58.257898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.7%
% 48
16.0%
0 45
15.0%
1 33
11.0%
5 28
9.3%
3 24
8.0%
6 18
 
6.0%
2 13
 
4.3%
8 13
 
4.3%
4 8
 
2.7%
Other values (2) 11
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 193
64.3%
Other Punctuation 107
35.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 45
23.3%
1 33
17.1%
5 28
14.5%
3 24
12.4%
6 18
 
9.3%
2 13
 
6.7%
8 13
 
6.7%
4 8
 
4.1%
7 6
 
3.1%
9 5
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 300
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.7%
% 48
16.0%
0 45
15.0%
1 33
11.0%
5 28
9.3%
3 24
8.0%
6 18
 
6.0%
2 13
 
4.3%
8 13
 
4.3%
4 8
 
2.7%
Other values (2) 11
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.7%
% 48
16.0%
0 45
15.0%
1 33
11.0%
5 28
9.3%
3 24
8.0%
6 18
 
6.0%
2 13
 
4.3%
8 13
 
4.3%
4 8
 
2.7%
Other values (2) 11
 
3.7%
Distinct41
Distinct (%)56.2%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:58.418999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.0821918
Min length2

Characters and Unicode

Total characters298
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)43.8%

Sample

1st row4667
2nd row4000
3rd row2333
4th row7333
5th row15
ValueCountFrequency (%)
0.0 16
21.9%
6.7 7
 
9.6%
15 4
 
5.5%
13.3 3
 
4.1%
5.13 3
 
4.1%
22.2 2
 
2.7%
20.0 2
 
2.7%
5.47 2
 
2.7%
7.4 2
 
2.7%
4.3 1
 
1.4%
Other values (31) 31
42.5%
2024-04-17T23:25:58.707645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.8%
% 48
16.1%
0 47
15.8%
3 35
11.7%
7 18
 
6.0%
5 18
 
6.0%
6 17
 
5.7%
1 16
 
5.4%
4 15
 
5.0%
2 14
 
4.7%
Other values (2) 11
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 191
64.1%
Other Punctuation 107
35.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 47
24.6%
3 35
18.3%
7 18
 
9.4%
5 18
 
9.4%
6 17
 
8.9%
1 16
 
8.4%
4 15
 
7.9%
2 14
 
7.3%
9 6
 
3.1%
8 5
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 298
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.8%
% 48
16.1%
0 47
15.8%
3 35
11.7%
7 18
 
6.0%
5 18
 
6.0%
6 17
 
5.7%
1 16
 
5.4%
4 15
 
5.0%
2 14
 
4.7%
Other values (2) 11
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 298
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.8%
% 48
16.1%
0 47
15.8%
3 35
11.7%
7 18
 
6.0%
5 18
 
6.0%
6 17
 
5.7%
1 16
 
5.4%
4 15
 
5.0%
2 14
 
4.7%
Other values (2) 11
 
3.7%
Distinct63
Distinct (%)86.3%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:58.917730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.1917808
Min length3

Characters and Unicode

Total characters306
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)75.3%

Sample

1st row6510
2nd row1985
3rd row587
4th row9355
5th row371
ValueCountFrequency (%)
7.5 3
 
4.1%
5.9 3
 
4.1%
0.0 2
 
2.7%
10.8 2
 
2.7%
9.3 2
 
2.7%
5.0 2
 
2.7%
4.0 2
 
2.7%
4.1 2
 
2.7%
23.0 1
 
1.4%
370 1
 
1.4%
Other values (53) 53
72.6%
2024-04-17T23:25:59.244041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
5 35
11.4%
3 25
8.2%
1 24
7.8%
0 23
 
7.5%
4 23
 
7.5%
7 19
 
6.2%
9 18
 
5.9%
2 13
 
4.2%
Other values (2) 19
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 199
65.0%
Other Punctuation 107
35.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 35
17.6%
3 25
12.6%
1 24
12.1%
0 23
11.6%
4 23
11.6%
7 19
9.5%
9 18
9.0%
2 13
 
6.5%
8 12
 
6.0%
6 7
 
3.5%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 306
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
5 35
11.4%
3 25
8.2%
1 24
7.8%
0 23
 
7.5%
4 23
 
7.5%
7 19
 
6.2%
9 18
 
5.9%
2 13
 
4.2%
Other values (2) 19
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 306
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
5 35
11.4%
3 25
8.2%
1 24
7.8%
0 23
 
7.5%
4 23
 
7.5%
7 19
 
6.2%
9 18
 
5.9%
2 13
 
4.2%
Other values (2) 19
 
6.2%

job_student
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing73
Missing (%)100.0%
Memory size789.0 B
Distinct57
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:59.456752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.109589
Min length2

Characters and Unicode

Total characters300
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)63.0%

Sample

1st row13451
2nd row3028
3rd row423
4th row5535
5th row83
ValueCountFrequency (%)
0.0 3
 
4.1%
6.3 3
 
4.1%
1.2 3
 
4.1%
4.4 3
 
4.1%
4.8 3
 
4.1%
2.5 2
 
2.7%
5.05 2
 
2.7%
5.10 2
 
2.7%
83 2
 
2.7%
13.3 2
 
2.7%
Other values (47) 48
65.8%
2024-04-17T23:25:59.785419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.7%
% 48
16.0%
3 30
10.0%
5 26
8.7%
1 24
8.0%
0 22
 
7.3%
4 22
 
7.3%
8 19
 
6.3%
6 17
 
5.7%
2 15
 
5.0%
Other values (2) 18
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 193
64.3%
Other Punctuation 107
35.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 30
15.5%
5 26
13.5%
1 24
12.4%
0 22
11.4%
4 22
11.4%
8 19
9.8%
6 17
8.8%
2 15
7.8%
7 11
 
5.7%
9 7
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 300
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.7%
% 48
16.0%
3 30
10.0%
5 26
8.7%
1 24
8.0%
0 22
 
7.3%
4 22
 
7.3%
8 19
 
6.3%
6 17
 
5.7%
2 15
 
5.0%
Other values (2) 18
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.7%
% 48
16.0%
3 30
10.0%
5 26
8.7%
1 24
8.0%
0 22
 
7.3%
4 22
 
7.3%
8 19
 
6.3%
6 17
 
5.7%
2 15
 
5.0%
Other values (2) 18
 
6.0%
Distinct58
Distinct (%)79.5%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:25:59.989462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.1506849
Min length2

Characters and Unicode

Total characters303
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)67.1%

Sample

1st row5606
2nd row3485
3rd row242
4th row18636
5th row74
ValueCountFrequency (%)
2.7 5
 
6.8%
21.3 3
 
4.1%
4.1 3
 
4.1%
1.4 3
 
4.1%
5.6 2
 
2.7%
1.3 2
 
2.7%
0.0 2
 
2.7%
10.6 2
 
2.7%
9.2 2
 
2.7%
55179 1
 
1.4%
Other values (48) 48
65.8%
2024-04-17T23:26:00.298500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.5%
% 48
15.8%
1 36
11.9%
5 29
9.6%
2 23
 
7.6%
4 20
 
6.6%
3 18
 
5.9%
6 18
 
5.9%
0 17
 
5.6%
7 14
 
4.6%
Other values (2) 21
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 196
64.7%
Other Punctuation 107
35.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 36
18.4%
5 29
14.8%
2 23
11.7%
4 20
10.2%
3 18
9.2%
6 18
9.2%
0 17
8.7%
7 14
 
7.1%
8 11
 
5.6%
9 10
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 303
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.5%
% 48
15.8%
1 36
11.9%
5 29
9.6%
2 23
 
7.6%
4 20
 
6.6%
3 18
 
5.9%
6 18
 
5.9%
0 17
 
5.6%
7 14
 
4.6%
Other values (2) 21
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 303
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.5%
% 48
15.8%
1 36
11.9%
5 29
9.6%
2 23
 
7.6%
4 20
 
6.6%
3 18
 
5.9%
6 18
 
5.9%
0 17
 
5.6%
7 14
 
4.6%
Other values (2) 21
 
6.9%
Distinct66
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:00.519230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.1917808
Min length3

Characters and Unicode

Total characters306
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)80.8%

Sample

1st row6782
2nd row2712
3rd row569
4th row4398
5th row482
ValueCountFrequency (%)
5.55 2
 
2.7%
4.0 2
 
2.7%
4.4 2
 
2.7%
0.0 2
 
2.7%
3.7 2
 
2.7%
3.9 2
 
2.7%
6.9 2
 
2.7%
485 1
 
1.4%
7.0 1
 
1.4%
2.3 1
 
1.4%
Other values (56) 56
76.7%
2024-04-17T23:26:00.862063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
2 32
10.5%
5 26
8.5%
4 26
8.5%
6 20
 
6.5%
3 18
 
5.9%
1 18
 
5.9%
7 17
 
5.6%
8 16
 
5.2%
Other values (2) 26
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 199
65.0%
Other Punctuation 107
35.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 32
16.1%
5 26
13.1%
4 26
13.1%
6 20
10.1%
3 18
9.0%
1 18
9.0%
7 17
8.5%
8 16
8.0%
9 13
6.5%
0 13
6.5%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 306
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
2 32
10.5%
5 26
8.5%
4 26
8.5%
6 20
 
6.5%
3 18
 
5.9%
1 18
 
5.9%
7 17
 
5.6%
8 16
 
5.2%
Other values (2) 26
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 306
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
2 32
10.5%
5 26
8.5%
4 26
8.5%
6 20
 
6.5%
3 18
 
5.9%
1 18
 
5.9%
7 17
 
5.6%
8 16
 
5.2%
Other values (2) 26
8.5%

income_100
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing73
Missing (%)100.0%
Memory size789.0 B
Distinct65
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:01.083258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.1917808
Min length3

Characters and Unicode

Total characters306
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)78.1%

Sample

1st row5376
2nd row3802
3rd row1212
4th row11221
5th row465
ValueCountFrequency (%)
7.3 2
 
2.7%
4.1 2
 
2.7%
5.06 2
 
2.7%
0.2 2
 
2.7%
5.4 2
 
2.7%
4.3 2
 
2.7%
4.8 2
 
2.7%
3.9 2
 
2.7%
6.4 1
 
1.4%
90631 1
 
1.4%
Other values (55) 55
75.3%
2024-04-17T23:26:01.435072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
1 27
8.8%
5 26
8.5%
4 24
7.8%
2 24
7.8%
3 20
 
6.5%
6 18
 
5.9%
7 17
 
5.6%
0 17
 
5.6%
Other values (2) 26
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 199
65.0%
Other Punctuation 107
35.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 27
13.6%
5 26
13.1%
4 24
12.1%
2 24
12.1%
3 20
10.1%
6 18
9.0%
7 17
8.5%
0 17
8.5%
9 15
7.5%
8 11
5.5%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 306
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
1 27
8.8%
5 26
8.5%
4 24
7.8%
2 24
7.8%
3 20
 
6.5%
6 18
 
5.9%
7 17
 
5.6%
0 17
 
5.6%
Other values (2) 26
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 306
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
1 27
8.8%
5 26
8.5%
4 24
7.8%
2 24
7.8%
3 20
 
6.5%
6 18
 
5.9%
7 17
 
5.6%
0 17
 
5.6%
Other values (2) 26
8.5%
Distinct67
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:01.646112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.2328767
Min length3

Characters and Unicode

Total characters309
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)84.9%

Sample

1st row13720
2nd row7236
3rd row2047
4th row16850
5th row275
ValueCountFrequency (%)
2.2 3
 
4.1%
4.0 2
 
2.7%
2.9 2
 
2.7%
0.4 2
 
2.7%
7.0 2
 
2.7%
13720 1
 
1.4%
254 1
 
1.4%
99275 1
 
1.4%
42933 1
 
1.4%
0.0 1
 
1.4%
Other values (57) 57
78.1%
2024-04-17T23:26:01.980975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.1%
% 48
15.5%
2 36
11.7%
4 23
 
7.4%
6 23
 
7.4%
5 21
 
6.8%
1 21
 
6.8%
0 19
 
6.1%
3 19
 
6.1%
7 18
 
5.8%
Other values (2) 22
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 202
65.4%
Other Punctuation 107
34.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 36
17.8%
4 23
11.4%
6 23
11.4%
5 21
10.4%
1 21
10.4%
0 19
9.4%
3 19
9.4%
7 18
8.9%
9 13
 
6.4%
8 9
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 309
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.1%
% 48
15.5%
2 36
11.7%
4 23
 
7.4%
6 23
 
7.4%
5 21
 
6.8%
1 21
 
6.8%
0 19
 
6.1%
3 19
 
6.1%
7 18
 
5.8%
Other values (2) 22
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 309
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.1%
% 48
15.5%
2 36
11.7%
4 23
 
7.4%
6 23
 
7.4%
5 21
 
6.8%
1 21
 
6.8%
0 19
 
6.1%
3 19
 
6.1%
7 18
 
5.8%
Other values (2) 22
 
7.1%
Distinct60
Distinct (%)82.2%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:02.182312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.2465753
Min length3

Characters and Unicode

Total characters310
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)65.8%

Sample

1st row7629
2nd row4823
3rd row2651
4th row12343
5th row189
ValueCountFrequency (%)
2.1 3
 
4.1%
5.31 2
 
2.7%
3.2 2
 
2.7%
0.0 2
 
2.7%
189 2
 
2.7%
4.3 2
 
2.7%
8.6 2
 
2.7%
0.5 2
 
2.7%
3.7 2
 
2.7%
2.6 2
 
2.7%
Other values (50) 52
71.2%
2024-04-17T23:26:02.503846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.0%
% 48
15.5%
1 39
12.6%
5 27
8.7%
2 22
 
7.1%
3 20
 
6.5%
6 20
 
6.5%
8 18
 
5.8%
4 17
 
5.5%
7 16
 
5.2%
Other values (2) 24
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 203
65.5%
Other Punctuation 107
34.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 39
19.2%
5 27
13.3%
2 22
10.8%
3 20
9.9%
6 20
9.9%
8 18
8.9%
4 17
8.4%
7 16
7.9%
0 14
 
6.9%
9 10
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 310
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.0%
% 48
15.5%
1 39
12.6%
5 27
8.7%
2 22
 
7.1%
3 20
 
6.5%
6 20
 
6.5%
8 18
 
5.8%
4 17
 
5.5%
7 16
 
5.2%
Other values (2) 24
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 310
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.0%
% 48
15.5%
1 39
12.6%
5 27
8.7%
2 22
 
7.1%
3 20
 
6.5%
6 20
 
6.5%
8 18
 
5.8%
4 17
 
5.5%
7 16
 
5.2%
Other values (2) 24
7.7%
Distinct64
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:02.713592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.2328767
Min length3

Characters and Unicode

Total characters309
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)76.7%

Sample

1st row13949
2nd row8333
3rd row2964
4th row19282
5th row206
ValueCountFrequency (%)
0.0 3
 
4.1%
5.24 2
 
2.7%
206 2
 
2.7%
4.4 2
 
2.7%
1.9 2
 
2.7%
1.5 2
 
2.7%
2.4 2
 
2.7%
7.7 2
 
2.7%
13949 1
 
1.4%
16.5 1
 
1.4%
Other values (54) 54
74.0%
2024-04-17T23:26:03.031512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.1%
% 48
15.5%
5 29
9.4%
1 26
8.4%
4 23
 
7.4%
3 22
 
7.1%
0 20
 
6.5%
2 20
 
6.5%
9 20
 
6.5%
6 15
 
4.9%
Other values (2) 27
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 202
65.4%
Other Punctuation 107
34.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 29
14.4%
1 26
12.9%
4 23
11.4%
3 22
10.9%
0 20
9.9%
2 20
9.9%
9 20
9.9%
6 15
7.4%
7 14
6.9%
8 13
6.4%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 309
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.1%
% 48
15.5%
5 29
9.4%
1 26
8.4%
4 23
 
7.4%
3 22
 
7.1%
0 20
 
6.5%
2 20
 
6.5%
9 20
 
6.5%
6 15
 
4.9%
Other values (2) 27
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 309
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.1%
% 48
15.5%
5 29
9.4%
1 26
8.4%
4 23
 
7.4%
3 22
 
7.1%
0 20
 
6.5%
2 20
 
6.5%
9 20
 
6.5%
6 15
 
4.9%
Other values (2) 27
8.7%
Distinct65
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:03.291092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.1369863
Min length1

Characters and Unicode

Total characters302
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)78.1%

Sample

1st row2234
2nd row648
3rd row0
4th row7664
5th row334
ValueCountFrequency (%)
2.9 2
 
2.7%
2.1 2
 
2.7%
8.1 2
 
2.7%
6.0 2
 
2.7%
3.6 2
 
2.7%
8.4 2
 
2.7%
334 2
 
2.7%
6.4 2
 
2.7%
653 1
 
1.4%
5.8 1
 
1.4%
Other values (55) 55
75.3%
2024-04-17T23:26:03.642383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.5%
% 48
15.9%
4 27
8.9%
2 25
8.3%
1 25
8.3%
5 24
7.9%
3 23
 
7.6%
8 18
 
6.0%
6 17
 
5.6%
9 14
 
4.6%
Other values (2) 22
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 195
64.6%
Other Punctuation 107
35.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 27
13.8%
2 25
12.8%
1 25
12.8%
5 24
12.3%
3 23
11.8%
8 18
9.2%
6 17
8.7%
9 14
7.2%
0 12
6.2%
7 10
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 302
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.5%
% 48
15.9%
4 27
8.9%
2 25
8.3%
1 25
8.3%
5 24
7.9%
3 23
 
7.6%
8 18
 
6.0%
6 17
 
5.6%
9 14
 
4.6%
Other values (2) 22
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 302
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.5%
% 48
15.9%
4 27
8.9%
2 25
8.3%
1 25
8.3%
5 24
7.9%
3 23
 
7.6%
8 18
 
6.0%
6 17
 
5.6%
9 14
 
4.6%
Other values (2) 22
 
7.3%
Distinct68
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:03.856220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.1780822
Min length3

Characters and Unicode

Total characters305
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)87.7%

Sample

1st row6138
2nd row3077
3rd row1736
4th row6423
5th row750
ValueCountFrequency (%)
5.6 3
 
4.1%
3.8 2
 
2.7%
3.9 2
 
2.7%
0.0 2
 
2.7%
3.4 1
 
1.4%
746 1
 
1.4%
6138 1
 
1.4%
29785 1
 
1.4%
28.1 1
 
1.4%
752 1
 
1.4%
Other values (58) 58
79.5%
2024-04-17T23:26:04.192875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
5 34
11.1%
2 25
8.2%
6 22
 
7.2%
7 20
 
6.6%
0 19
 
6.2%
3 17
 
5.6%
1 17
 
5.6%
4 16
 
5.2%
Other values (2) 28
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 198
64.9%
Other Punctuation 107
35.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 34
17.2%
2 25
12.6%
6 22
11.1%
7 20
10.1%
0 19
9.6%
3 17
8.6%
1 17
8.6%
4 16
8.1%
8 15
7.6%
9 13
 
6.6%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 305
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
5 34
11.1%
2 25
8.2%
6 22
 
7.2%
7 20
 
6.6%
0 19
 
6.2%
3 17
 
5.6%
1 17
 
5.6%
4 16
 
5.2%
Other values (2) 28
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 305
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
5 34
11.1%
2 25
8.2%
6 22
 
7.2%
7 20
 
6.6%
0 19
 
6.2%
3 17
 
5.6%
1 17
 
5.6%
4 16
 
5.2%
Other values (2) 28
9.2%
Distinct66
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:04.416965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.2328767
Min length3

Characters and Unicode

Total characters309
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)80.8%

Sample

1st row11856
2nd row4217
3rd row1293
4th row14882
5th row445
ValueCountFrequency (%)
5.07 2
 
2.7%
19.8 2
 
2.7%
3.9 2
 
2.7%
0.0 2
 
2.7%
4.0 2
 
2.7%
5.3 2
 
2.7%
5.25 2
 
2.7%
1.8 1
 
1.4%
396 1
 
1.4%
6.2 1
 
1.4%
Other values (56) 56
76.7%
2024-04-17T23:26:04.749175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.1%
% 48
15.5%
5 30
9.7%
8 25
8.1%
2 22
 
7.1%
1 22
 
7.1%
0 19
 
6.1%
3 19
 
6.1%
4 19
 
6.1%
9 16
 
5.2%
Other values (2) 30
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 202
65.4%
Other Punctuation 107
34.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 30
14.9%
8 25
12.4%
2 22
10.9%
1 22
10.9%
0 19
9.4%
3 19
9.4%
4 19
9.4%
9 16
7.9%
7 15
7.4%
6 15
7.4%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 309
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.1%
% 48
15.5%
5 30
9.7%
8 25
8.1%
2 22
 
7.1%
1 22
 
7.1%
0 19
 
6.1%
3 19
 
6.1%
4 19
 
6.1%
9 16
 
5.2%
Other values (2) 30
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 309
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.1%
% 48
15.5%
5 30
9.7%
8 25
8.1%
2 22
 
7.1%
1 22
 
7.1%
0 19
 
6.1%
3 19
 
6.1%
4 19
 
6.1%
9 16
 
5.2%
Other values (2) 30
9.7%
Distinct66
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:04.975691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.2465753
Min length3

Characters and Unicode

Total characters310
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)80.8%

Sample

1st row11970
2nd row10194
3rd row2683
4th row15638
5th row464
ValueCountFrequency (%)
2.8 2
 
2.7%
16.2 2
 
2.7%
1.5 2
 
2.7%
5.0 2
 
2.7%
20.9 2
 
2.7%
6.9 2
 
2.7%
464 2
 
2.7%
65850 1
 
1.4%
16.6 1
 
1.4%
439 1
 
1.4%
Other values (56) 56
76.7%
2024-04-17T23:26:05.330204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.0%
% 48
15.5%
1 30
9.7%
5 29
9.4%
6 26
8.4%
4 22
 
7.1%
0 20
 
6.5%
2 19
 
6.1%
3 18
 
5.8%
8 16
 
5.2%
Other values (2) 23
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 203
65.5%
Other Punctuation 107
34.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 30
14.8%
5 29
14.3%
6 26
12.8%
4 22
10.8%
0 20
9.9%
2 19
9.4%
3 18
8.9%
8 16
7.9%
9 13
6.4%
7 10
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 310
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.0%
% 48
15.5%
1 30
9.7%
5 29
9.4%
6 26
8.4%
4 22
 
7.1%
0 20
 
6.5%
2 19
 
6.1%
3 18
 
5.8%
8 16
 
5.2%
Other values (2) 23
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 310
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.0%
% 48
15.5%
1 30
9.7%
5 29
9.4%
6 26
8.4%
4 22
 
7.1%
0 20
 
6.5%
2 19
 
6.1%
3 18
 
5.8%
8 16
 
5.2%
Other values (2) 23
 
7.4%
Distinct64
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:05.534963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.2054795
Min length3

Characters and Unicode

Total characters307
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)76.7%

Sample

1st row6905
2nd row3940
3rd row1547
4th row10745
5th row381
ValueCountFrequency (%)
3.7 3
 
4.1%
381 2
 
2.7%
3.4 2
 
2.7%
6.8 2
 
2.7%
4.2 2
 
2.7%
3.1 2
 
2.7%
0.8 2
 
2.7%
6.4 2
 
2.7%
6905 1
 
1.4%
349 1
 
1.4%
Other values (54) 54
74.0%
2024-04-17T23:26:05.869168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
5 26
8.5%
3 25
8.1%
1 24
7.8%
2 23
 
7.5%
4 21
 
6.8%
7 18
 
5.9%
9 18
 
5.9%
0 17
 
5.5%
Other values (2) 28
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 200
65.1%
Other Punctuation 107
34.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 26
13.0%
3 25
12.5%
1 24
12.0%
2 23
11.5%
4 21
10.5%
7 18
9.0%
9 18
9.0%
0 17
8.5%
6 14
7.0%
8 14
7.0%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 307
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
5 26
8.5%
3 25
8.1%
1 24
7.8%
2 23
 
7.5%
4 21
 
6.8%
7 18
 
5.9%
9 18
 
5.9%
0 17
 
5.5%
Other values (2) 28
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
5 26
8.5%
3 25
8.1%
1 24
7.8%
2 23
 
7.5%
4 21
 
6.8%
7 18
 
5.9%
9 18
 
5.9%
0 17
 
5.5%
Other values (2) 28
9.1%
Distinct62
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:06.092238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.1369863
Min length2

Characters and Unicode

Total characters302
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)74.0%

Sample

1st row3226
2nd row2761
3rd row65
4th row7581
5th row164
ValueCountFrequency (%)
4.7 3
 
4.1%
0.0 3
 
4.1%
2.5 3
 
4.1%
3.7 2
 
2.7%
6.7 2
 
2.7%
12.9 2
 
2.7%
5.20 2
 
2.7%
3.6 2
 
2.7%
0.6 1
 
1.4%
16.4 1
 
1.4%
Other values (52) 52
71.2%
2024-04-17T23:26:06.421983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.5%
% 48
15.9%
5 30
9.9%
1 25
8.3%
7 23
 
7.6%
4 21
 
7.0%
2 21
 
7.0%
6 21
 
7.0%
0 16
 
5.3%
9 16
 
5.3%
Other values (2) 22
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 195
64.6%
Other Punctuation 107
35.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 30
15.4%
1 25
12.8%
7 23
11.8%
4 21
10.8%
2 21
10.8%
6 21
10.8%
0 16
8.2%
9 16
8.2%
3 14
7.2%
8 8
 
4.1%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 302
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.5%
% 48
15.9%
5 30
9.9%
1 25
8.3%
7 23
 
7.6%
4 21
 
7.0%
2 21
 
7.0%
6 21
 
7.0%
0 16
 
5.3%
9 16
 
5.3%
Other values (2) 22
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 302
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.5%
% 48
15.9%
5 30
9.9%
1 25
8.3%
7 23
 
7.6%
4 21
 
7.0%
2 21
 
7.0%
6 21
 
7.0%
0 16
 
5.3%
9 16
 
5.3%
Other values (2) 22
 
7.3%
Distinct60
Distinct (%)82.2%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:06.634393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.2328767
Min length3

Characters and Unicode

Total characters309
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)67.1%

Sample

1st row4588
2nd row3529
3rd row1373
4th row14412
5th row105
ValueCountFrequency (%)
0.0 3
 
4.1%
2.1 3
 
4.1%
6.7 2
 
2.7%
8.6 2
 
2.7%
7.8 2
 
2.7%
2.9 2
 
2.7%
4.9 2
 
2.7%
3.8 2
 
2.7%
21.9 2
 
2.7%
105 2
 
2.7%
Other values (50) 51
69.9%
2024-04-17T23:26:06.969433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.1%
% 48
15.5%
1 29
9.4%
5 28
9.1%
2 25
8.1%
0 23
 
7.4%
3 20
 
6.5%
7 17
 
5.5%
8 17
 
5.5%
4 17
 
5.5%
Other values (2) 26
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 202
65.4%
Other Punctuation 107
34.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 29
14.4%
5 28
13.9%
2 25
12.4%
0 23
11.4%
3 20
9.9%
7 17
8.4%
8 17
8.4%
4 17
8.4%
9 15
7.4%
6 11
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 309
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.1%
% 48
15.5%
1 29
9.4%
5 28
9.1%
2 25
8.1%
0 23
 
7.4%
3 20
 
6.5%
7 17
 
5.5%
8 17
 
5.5%
4 17
 
5.5%
Other values (2) 26
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 309
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.1%
% 48
15.5%
1 29
9.4%
5 28
9.1%
2 25
8.1%
0 23
 
7.4%
3 20
 
6.5%
7 17
 
5.5%
8 17
 
5.5%
4 17
 
5.5%
Other values (2) 26
8.4%
Distinct57
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:07.163901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.1506849
Min length2

Characters and Unicode

Total characters303
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)68.5%

Sample

1st row6037
2nd row17154
3rd row2000
4th row13077
5th row73
ValueCountFrequency (%)
4.1 6
 
8.2%
0.0 5
 
6.8%
6.8 4
 
5.5%
5.8 2
 
2.7%
73 2
 
2.7%
16.4 2
 
2.7%
8.2 2
 
2.7%
82415 1
 
1.4%
65 1
 
1.4%
93224 1
 
1.4%
Other values (47) 47
64.4%
2024-04-17T23:26:07.488392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.5%
% 48
15.8%
4 30
9.9%
5 27
8.9%
1 26
8.6%
0 22
 
7.3%
2 20
 
6.6%
8 18
 
5.9%
3 17
 
5.6%
7 16
 
5.3%
Other values (2) 20
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 196
64.7%
Other Punctuation 107
35.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 30
15.3%
5 27
13.8%
1 26
13.3%
0 22
11.2%
2 20
10.2%
8 18
9.2%
3 17
8.7%
7 16
8.2%
6 14
7.1%
9 6
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 303
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.5%
% 48
15.8%
4 30
9.9%
5 27
8.9%
1 26
8.6%
0 22
 
7.3%
2 20
 
6.6%
8 18
 
5.9%
3 17
 
5.6%
7 16
 
5.3%
Other values (2) 20
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 303
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.5%
% 48
15.8%
4 30
9.9%
5 27
8.9%
1 26
8.6%
0 22
 
7.3%
2 20
 
6.6%
8 18
 
5.9%
3 17
 
5.6%
7 16
 
5.3%
Other values (2) 20
 
6.6%
Distinct57
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:07.678189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.1369863
Min length2

Characters and Unicode

Total characters302
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)61.6%

Sample

1st row6628
2nd row2116
3rd row1581
4th row8395
5th row94
ValueCountFrequency (%)
1.1 5
 
6.8%
0.0 3
 
4.1%
5.70 2
 
2.7%
7.9 2
 
2.7%
6.4 2
 
2.7%
20.2 2
 
2.7%
3.2 2
 
2.7%
4.7 2
 
2.7%
7.4 2
 
2.7%
2.2 2
 
2.7%
Other values (47) 49
67.1%
2024-04-17T23:26:07.977743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.5%
% 48
15.9%
1 35
11.6%
5 27
8.9%
2 25
8.3%
4 22
 
7.3%
7 17
 
5.6%
3 16
 
5.3%
9 16
 
5.3%
0 15
 
5.0%
Other values (2) 22
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 195
64.6%
Other Punctuation 107
35.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 35
17.9%
5 27
13.8%
2 25
12.8%
4 22
11.3%
7 17
8.7%
3 16
8.2%
9 16
8.2%
0 15
7.7%
8 13
 
6.7%
6 9
 
4.6%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 302
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.5%
% 48
15.9%
1 35
11.6%
5 27
8.9%
2 25
8.3%
4 22
 
7.3%
7 17
 
5.6%
3 16
 
5.3%
9 16
 
5.3%
0 15
 
5.0%
Other values (2) 22
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 302
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.5%
% 48
15.9%
1 35
11.6%
5 27
8.9%
2 25
8.3%
4 22
 
7.3%
7 17
 
5.6%
3 16
 
5.3%
9 16
 
5.3%
0 15
 
5.0%
Other values (2) 22
 
7.3%
Distinct58
Distinct (%)79.5%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:08.189626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.0958904
Min length2

Characters and Unicode

Total characters299
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)67.1%

Sample

1st row10794
2nd row5952
3rd row5159
4th row5206
5th row68
ValueCountFrequency (%)
1.5 5
 
6.8%
0.0 3
 
4.1%
4.4 3
 
4.1%
4.5 3
 
4.1%
68 2
 
2.7%
2.9 2
 
2.7%
5.2 2
 
2.7%
8.8 2
 
2.7%
3.0 2
 
2.7%
10794 1
 
1.4%
Other values (48) 48
65.8%
2024-04-17T23:26:08.500405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.7%
% 48
16.1%
5 35
11.7%
4 26
8.7%
1 25
8.4%
0 21
 
7.0%
2 19
 
6.4%
3 17
 
5.7%
6 16
 
5.4%
8 13
 
4.3%
Other values (2) 20
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 192
64.2%
Other Punctuation 107
35.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 35
18.2%
4 26
13.5%
1 25
13.0%
0 21
10.9%
2 19
9.9%
3 17
8.9%
6 16
8.3%
8 13
 
6.8%
9 10
 
5.2%
7 10
 
5.2%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 299
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.7%
% 48
16.1%
5 35
11.7%
4 26
8.7%
1 25
8.4%
0 21
 
7.0%
2 19
 
6.4%
3 17
 
5.7%
6 16
 
5.4%
8 13
 
4.3%
Other values (2) 20
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 299
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.7%
% 48
16.1%
5 35
11.7%
4 26
8.7%
1 25
8.4%
0 21
 
7.0%
2 19
 
6.4%
3 17
 
5.7%
6 16
 
5.4%
8 13
 
4.3%
Other values (2) 20
 
6.7%
Distinct64
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:08.720320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.2054795
Min length3

Characters and Unicode

Total characters307
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)75.3%

Sample

1st row11099
2nd row4074
3rd row1089
4th row10776
5th row435
ValueCountFrequency (%)
4.4 2
 
2.7%
4.5 2
 
2.7%
5.7 2
 
2.7%
3.9 2
 
2.7%
2.8 2
 
2.7%
8.4 2
 
2.7%
8.7 2
 
2.7%
5.47 2
 
2.7%
0.0 2
 
2.7%
91766 1
 
1.4%
Other values (54) 54
74.0%
2024-04-17T23:26:09.059847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
4 27
8.8%
3 23
 
7.5%
5 22
 
7.2%
0 21
 
6.8%
7 21
 
6.8%
1 20
 
6.5%
6 18
 
5.9%
2 17
 
5.5%
Other values (2) 31
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 200
65.1%
Other Punctuation 107
34.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 27
13.5%
3 23
11.5%
5 22
11.0%
0 21
10.5%
7 21
10.5%
1 20
10.0%
6 18
9.0%
2 17
8.5%
8 17
8.5%
9 14
7.0%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 307
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
4 27
8.8%
3 23
 
7.5%
5 22
 
7.2%
0 21
 
6.8%
7 21
 
6.8%
1 20
 
6.5%
6 18
 
5.9%
2 17
 
5.5%
Other values (2) 31
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.2%
% 48
15.6%
4 27
8.8%
3 23
 
7.5%
5 22
 
7.2%
0 21
 
6.8%
7 21
 
6.8%
1 20
 
6.5%
6 18
 
5.9%
2 17
 
5.5%
Other values (2) 31
10.1%
Distinct56
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:09.249656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.1643836
Min length2

Characters and Unicode

Total characters304
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)63.0%

Sample

1st row11127
2nd row7239
3rd row2958
4th row18451
5th row78
ValueCountFrequency (%)
2.6 6
 
8.2%
0.0 4
 
5.5%
5.2 3
 
4.1%
3.8 2
 
2.7%
5.22 2
 
2.7%
5.1 2
 
2.7%
16.7 2
 
2.7%
7.7 2
 
2.7%
78 2
 
2.7%
6.2 2
 
2.7%
Other values (46) 46
63.0%
2024-04-17T23:26:09.560345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.4%
% 48
15.8%
1 30
9.9%
2 28
9.2%
5 25
8.2%
6 24
7.9%
4 19
 
6.2%
7 18
 
5.9%
9 16
 
5.3%
0 13
 
4.3%
Other values (2) 24
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 197
64.8%
Other Punctuation 107
35.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 30
15.2%
2 28
14.2%
5 25
12.7%
6 24
12.2%
4 19
9.6%
7 18
9.1%
9 16
8.1%
0 13
6.6%
3 13
6.6%
8 11
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 304
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.4%
% 48
15.8%
1 30
9.9%
2 28
9.2%
5 25
8.2%
6 24
7.9%
4 19
 
6.2%
7 18
 
5.9%
9 16
 
5.3%
0 13
 
4.3%
Other values (2) 24
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 304
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.4%
% 48
15.8%
1 30
9.9%
2 28
9.2%
5 25
8.2%
6 24
7.9%
4 19
 
6.2%
7 18
 
5.9%
9 16
 
5.3%
0 13
 
4.3%
Other values (2) 24
7.9%
Distinct56
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:09.759146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.109589
Min length1

Characters and Unicode

Total characters300
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)57.5%

Sample

1st row2333
2nd row2833
3rd row0
4th row12667
5th row68
ValueCountFrequency (%)
2.9 4
 
5.5%
0.0 3
 
4.1%
6.0 2
 
2.7%
1.5 2
 
2.7%
13.2 2
 
2.7%
7.5 2
 
2.7%
9.0 2
 
2.7%
6.5 2
 
2.7%
68 2
 
2.7%
5.9 2
 
2.7%
Other values (46) 50
68.5%
2024-04-17T23:26:10.081023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.7%
% 48
16.0%
2 29
9.7%
5 28
9.3%
1 24
8.0%
0 22
 
7.3%
9 17
 
5.7%
6 17
 
5.7%
7 16
 
5.3%
8 14
 
4.7%
Other values (2) 26
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 193
64.3%
Other Punctuation 107
35.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 29
15.0%
5 28
14.5%
1 24
12.4%
0 22
11.4%
9 17
8.8%
6 17
8.8%
7 16
8.3%
8 14
7.3%
4 14
7.3%
3 12
6.2%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 300
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.7%
% 48
16.0%
2 29
9.7%
5 28
9.3%
1 24
8.0%
0 22
 
7.3%
9 17
 
5.7%
6 17
 
5.7%
7 16
 
5.3%
8 14
 
4.7%
Other values (2) 26
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.7%
% 48
16.0%
2 29
9.7%
5 28
9.3%
1 24
8.0%
0 22
 
7.3%
9 17
 
5.7%
6 17
 
5.7%
7 16
 
5.3%
8 14
 
4.7%
Other values (2) 26
8.7%
Distinct62
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:10.299761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.109589
Min length2

Characters and Unicode

Total characters300
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)75.3%

Sample

1st row6938
2nd row3450
3rd row4588
4th row9000
5th row85
ValueCountFrequency (%)
3.6 3
 
4.1%
0.0 3
 
4.1%
4.7 3
 
4.1%
2.4 3
 
4.1%
20.9 2
 
2.7%
5.32 2
 
2.7%
7.1 2
 
2.7%
6938 1
 
1.4%
57738 1
 
1.4%
39500 1
 
1.4%
Other values (52) 52
71.2%
2024-04-17T23:26:10.628865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.7%
% 48
16.0%
5 25
8.3%
4 23
 
7.7%
3 22
 
7.3%
2 21
 
7.0%
0 21
 
7.0%
1 20
 
6.7%
8 18
 
6.0%
9 16
 
5.3%
Other values (2) 27
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 193
64.3%
Other Punctuation 107
35.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 25
13.0%
4 23
11.9%
3 22
11.4%
2 21
10.9%
0 21
10.9%
1 20
10.4%
8 18
9.3%
9 16
8.3%
7 14
7.3%
6 13
6.7%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 300
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.7%
% 48
16.0%
5 25
8.3%
4 23
 
7.7%
3 22
 
7.3%
2 21
 
7.0%
0 21
 
7.0%
1 20
 
6.7%
8 18
 
6.0%
9 16
 
5.3%
Other values (2) 27
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.7%
% 48
16.0%
5 25
8.3%
4 23
 
7.7%
3 22
 
7.3%
2 21
 
7.0%
0 21
 
7.0%
1 20
 
6.7%
8 18
 
6.0%
9 16
 
5.3%
Other values (2) 27
9.0%
Distinct58
Distinct (%)79.5%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:10.852321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.1780822
Min length2

Characters and Unicode

Total characters305
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)65.8%

Sample

1st row7590
2nd row7229
3rd row964
4th row21627
5th row89
ValueCountFrequency (%)
1.1 4
 
5.5%
5.6 4
 
5.5%
3.4 3
 
4.1%
5.02 2
 
2.7%
12.5 2
 
2.7%
89 2
 
2.7%
9.0 2
 
2.7%
13.5 2
 
2.7%
19.1 2
 
2.7%
0.0 2
 
2.7%
Other values (48) 48
65.8%
2024-04-17T23:26:11.186544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
1 37
12.1%
5 26
8.5%
2 23
 
7.5%
0 20
 
6.6%
4 19
 
6.2%
6 18
 
5.9%
3 16
 
5.2%
9 16
 
5.2%
Other values (2) 23
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 198
64.9%
Other Punctuation 107
35.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 37
18.7%
5 26
13.1%
2 23
11.6%
0 20
10.1%
4 19
9.6%
6 18
9.1%
3 16
8.1%
9 16
8.1%
7 12
 
6.1%
8 11
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 305
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
1 37
12.1%
5 26
8.5%
2 23
 
7.5%
0 20
 
6.6%
4 19
 
6.2%
6 18
 
5.9%
3 16
 
5.2%
9 16
 
5.2%
Other values (2) 23
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 305
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
1 37
12.1%
5 26
8.5%
2 23
 
7.5%
0 20
 
6.6%
4 19
 
6.2%
6 18
 
5.9%
3 16
 
5.2%
9 16
 
5.2%
Other values (2) 23
 
7.5%
Distinct49
Distinct (%)67.1%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:11.372534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.1232877
Min length2

Characters and Unicode

Total characters301
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)53.4%

Sample

1st row7500
2nd row10577
3rd row3942
4th row22692
5th row53
ValueCountFrequency (%)
5.7 6
 
8.2%
3.8 5
 
6.8%
0.0 4
 
5.5%
30.2 3
 
4.1%
7.5 3
 
4.1%
1.9 3
 
4.1%
53 3
 
4.1%
20.8 3
 
4.1%
6.8 2
 
2.7%
16.5 2
 
2.7%
Other values (39) 39
53.4%
2024-04-17T23:26:11.681447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.6%
% 48
15.9%
5 34
11.3%
0 24
8.0%
1 21
 
7.0%
7 20
 
6.6%
3 20
 
6.6%
2 20
 
6.6%
4 15
 
5.0%
8 14
 
4.7%
Other values (2) 26
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 194
64.5%
Other Punctuation 107
35.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 34
17.5%
0 24
12.4%
1 21
10.8%
7 20
10.3%
3 20
10.3%
2 20
10.3%
4 15
7.7%
8 14
7.2%
9 14
7.2%
6 12
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 301
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.6%
% 48
15.9%
5 34
11.3%
0 24
8.0%
1 21
 
7.0%
7 20
 
6.6%
3 20
 
6.6%
2 20
 
6.6%
4 15
 
5.0%
8 14
 
4.7%
Other values (2) 26
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 301
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.6%
% 48
15.9%
5 34
11.3%
0 24
8.0%
1 21
 
7.0%
7 20
 
6.6%
3 20
 
6.6%
2 20
 
6.6%
4 15
 
5.0%
8 14
 
4.7%
Other values (2) 26
8.6%
Distinct58
Distinct (%)79.5%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:11.913069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.1506849
Min length3

Characters and Unicode

Total characters303
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)65.8%

Sample

1st row7493
2nd row2603
3rd row353
4th row4633
5th row143
ValueCountFrequency (%)
0.0 4
 
5.5%
6.3 3
 
4.1%
7.7 3
 
4.1%
4.3 3
 
4.1%
4.8 2
 
2.7%
2.9 2
 
2.7%
21.0 2
 
2.7%
3.5 2
 
2.7%
2.1 2
 
2.7%
143 2
 
2.7%
Other values (48) 48
65.8%
2024-04-17T23:26:12.563136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.5%
% 48
15.8%
3 32
10.6%
1 26
8.6%
4 22
 
7.3%
5 21
 
6.9%
2 18
 
5.9%
7 17
 
5.6%
8 17
 
5.6%
0 16
 
5.3%
Other values (2) 27
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 196
64.7%
Other Punctuation 107
35.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 32
16.3%
1 26
13.3%
4 22
11.2%
5 21
10.7%
2 18
9.2%
7 17
8.7%
8 17
8.7%
0 16
8.2%
6 14
7.1%
9 13
6.6%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 303
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.5%
% 48
15.8%
3 32
10.6%
1 26
8.6%
4 22
 
7.3%
5 21
 
6.9%
2 18
 
5.9%
7 17
 
5.6%
8 17
 
5.6%
0 16
 
5.3%
Other values (2) 27
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 303
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.5%
% 48
15.8%
3 32
10.6%
1 26
8.6%
4 22
 
7.3%
5 21
 
6.9%
2 18
 
5.9%
7 17
 
5.6%
8 17
 
5.6%
0 16
 
5.3%
Other values (2) 27
8.9%
Distinct58
Distinct (%)79.5%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:12.775343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.1780822
Min length3

Characters and Unicode

Total characters305
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)65.8%

Sample

1st row13131
2nd row3759
3rd row1841
4th row4345
5th row157
ValueCountFrequency (%)
6.7 3
 
4.1%
1.9 3
 
4.1%
0.6 3
 
4.1%
0.0 3
 
4.1%
8.9 3
 
4.1%
7.0 2
 
2.7%
158 2
 
2.7%
5.1 2
 
2.7%
5.18 2
 
2.7%
5.7 2
 
2.7%
Other values (48) 48
65.8%
2024-04-17T23:26:13.106011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
1 35
11.5%
5 22
 
7.2%
4 22
 
7.2%
7 21
 
6.9%
6 20
 
6.6%
9 20
 
6.6%
0 18
 
5.9%
8 15
 
4.9%
Other values (2) 25
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 198
64.9%
Other Punctuation 107
35.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 35
17.7%
5 22
11.1%
4 22
11.1%
7 21
10.6%
6 20
10.1%
9 20
10.1%
0 18
9.1%
8 15
7.6%
3 13
 
6.6%
2 12
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 59
55.1%
% 48
44.9%

Most occurring scripts

ValueCountFrequency (%)
Common 305
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
1 35
11.5%
5 22
 
7.2%
4 22
 
7.2%
7 21
 
6.9%
6 20
 
6.6%
9 20
 
6.6%
0 18
 
5.9%
8 15
 
4.9%
Other values (2) 25
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 305
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59
19.3%
% 48
15.7%
1 35
11.5%
5 22
 
7.2%
4 22
 
7.2%
7 21
 
6.9%
6 20
 
6.6%
9 20
 
6.6%
0 18
 
5.9%
8 15
 
4.9%
Other values (2) 25
8.2%

question_gubun
Categorical

Distinct7
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size716.0 B
1-5
12 
1-19
11 
1-7
11 
1-6
11 
1-9-1
10 
Other values (2)
18 

Length

Max length6
Median length5
Mean length3.9178082
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1-13-1
2nd row1-13-1
3rd row1-13-1
4th row1-13-1
5th row1-18

Common Values

ValueCountFrequency (%)
1-5 12
16.4%
1-19 11
15.1%
1-7 11
15.1%
1-6 11
15.1%
1-9-1 10
13.7%
1-13-1 9
12.3%
1-18 9
12.3%

Length

2024-04-17T23:26:13.254966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:26:13.367185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1-5 12
16.4%
1-19 11
15.1%
1-7 11
15.1%
1-6 11
15.1%
1-9-1 10
13.7%
1-13-1 9
12.3%
1-18 9
12.3%
Distinct62
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-17T23:26:13.555617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length4.9452055
Min length2

Characters and Unicode

Total characters361
Distinct characters153
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)71.2%

Sample

1st row오락관련지출
2nd row문화관련지출
3rd row운동.레포츠비용
4th row기타비용
5th row사례수
ValueCountFrequency (%)
사례수 3
 
4.1%
다중응답(n≥2000 2
 
2.7%
해운대해수욕장 2
 
2.7%
국제시장 2
 
2.7%
해동용궁사 2
 
2.7%
광안대교 2
 
2.7%
태종대 2
 
2.7%
기타 2
 
2.7%
자갈치시장 2
 
2.7%
광안리해수욕장 2
 
2.7%
Other values (52) 52
71.2%
2024-04-17T23:26:13.900179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13
 
3.6%
11
 
3.0%
10
 
2.8%
9
 
2.5%
8
 
2.2%
8
 
2.2%
8
 
2.2%
7
 
1.9%
7
 
1.9%
0 6
 
1.7%
Other values (143) 274
75.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 318
88.1%
Uppercase Letter 16
 
4.4%
Decimal Number 8
 
2.2%
Other Punctuation 7
 
1.9%
Open Punctuation 4
 
1.1%
Close Punctuation 4
 
1.1%
Math Symbol 2
 
0.6%
Lowercase Letter 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
13
 
4.1%
11
 
3.5%
10
 
3.1%
9
 
2.8%
8
 
2.5%
8
 
2.5%
8
 
2.5%
7
 
2.2%
7
 
2.2%
5
 
1.6%
Other values (128) 232
73.0%
Uppercase Letter
ValueCountFrequency (%)
F 4
25.0%
P 2
12.5%
C 2
12.5%
A 2
12.5%
E 2
12.5%
B 2
12.5%
I 2
12.5%
Decimal Number
ValueCountFrequency (%)
0 6
75.0%
2 2
 
25.0%
Other Punctuation
ValueCountFrequency (%)
/ 6
85.7%
. 1
 
14.3%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Math Symbol
ValueCountFrequency (%)
2
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 318
88.1%
Common 25
 
6.9%
Latin 18
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
13
 
4.1%
11
 
3.5%
10
 
3.1%
9
 
2.8%
8
 
2.5%
8
 
2.5%
8
 
2.5%
7
 
2.2%
7
 
2.2%
5
 
1.6%
Other values (128) 232
73.0%
Latin
ValueCountFrequency (%)
F 4
22.2%
P 2
11.1%
C 2
11.1%
A 2
11.1%
E 2
11.1%
B 2
11.1%
I 2
11.1%
n 2
11.1%
Common
ValueCountFrequency (%)
0 6
24.0%
/ 6
24.0%
( 4
16.0%
) 4
16.0%
2
 
8.0%
2 2
 
8.0%
. 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 318
88.1%
ASCII 41
 
11.4%
Math Operators 2
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
13
 
4.1%
11
 
3.5%
10
 
3.1%
9
 
2.8%
8
 
2.5%
8
 
2.5%
8
 
2.5%
7
 
2.2%
7
 
2.2%
5
 
1.6%
Other values (128) 232
73.0%
ASCII
ValueCountFrequency (%)
0 6
14.6%
/ 6
14.6%
( 4
9.8%
F 4
9.8%
) 4
9.8%
P 2
 
4.9%
C 2
 
4.9%
A 2
 
4.9%
E 2
 
4.9%
B 2
 
4.9%
Other values (4) 7
17.1%
Math Operators
ValueCountFrequency (%)
2
100.0%

question_cont
Categorical

Distinct7
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size716.0 B
부산 방문시 숙박 장소
12 
관광지로서 부산의 이미지
11 
부산 여행시 가장 기억에 남는 방문지 1순위_상위 10순위
11 
부산 여행 방문한 방문지_상위10순위
11 
부산에서 맛본 특색 먹거리_복수응답
10 
Other values (2)
18 

Length

Max length32
Median length20
Mean length20.287671
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산 방문시 1인당 여행 지출액_개별여행
2nd row부산 방문시 1인당 여행 지출액_개별여행
3rd row부산 방문시 1인당 여행 지출액_개별여행
4th row부산 방문시 1인당 여행 지출액_개별여행
5th row부산여행에서 떠오르는 부산의 도시 이미지_1순위

Common Values

ValueCountFrequency (%)
부산 방문시 숙박 장소 12
16.4%
관광지로서 부산의 이미지 11
15.1%
부산 여행시 가장 기억에 남는 방문지 1순위_상위 10순위 11
15.1%
부산 여행 방문한 방문지_상위10순위 11
15.1%
부산에서 맛본 특색 먹거리_복수응답 10
13.7%
부산 방문시 1인당 여행 지출액_개별여행 9
12.3%
부산여행에서 떠오르는 부산의 도시 이미지_1순위 9
12.3%

Length

2024-04-17T23:26:14.040447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:26:14.173458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산 43
 
12.5%
방문시 21
 
6.1%
부산의 20
 
5.8%
여행 20
 
5.8%
숙박 12
 
3.5%
장소 12
 
3.5%
방문지 11
 
3.2%
방문지_상위10순위 11
 
3.2%
방문한 11
 
3.2%
1순위_상위 11
 
3.2%
Other values (17) 171
49.9%

answer_gubun
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size716.0 B
D
66 
T

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowD
2nd rowD
3rd rowD
4th rowD
5th rowT

Common Values

ValueCountFrequency (%)
D 66
90.4%
T 7
 
9.6%

Length

2024-04-17T23:26:14.310349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:26:14.409141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
d 66
90.4%
t 7
 
9.6%

last_load_dttm
Date

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
Minimum2021-03-01 06:05:03
Maximum2021-03-01 06:05:03
2024-04-17T23:26:14.482490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:26:14.568617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Sample

totalgender_malegender_femaleage_twentiesage_thirtiesage_fortiesage_fiftiesage_sixtiesmarriage_marriedmarriage_singlemarriage_etcjob_managementjob_professionaljob_officejob_servicejob_salejob_agriculturejob_technicaljob_machineryjob_manufacturaljob_militaryjob_housewifejob_studentjob_unemployedjob_etcincome_u100income_100income_200income_300income_400income_500season_springseason_summerseason_autumnseason_winterprovince_seoulprovince_daeguprovince_incheonprovince_gwangjuprovince_daejeonprovince_ulsanprovince_gyeonggiprovince_gangwonprovince_chungbukprovince_chungnamprovince_jeonbukprovince_jeonnamprovince_gyeongbukprovince_gyeongnamquestion_gubunanswer_contquestion_contanswer_gubunlast_load_dttm
08069.012053486244161188751938237118188399718117742209236685666797154717642910484121741733346676510<NA>1345156066782<NA>5376137207629139492234613811856119706905322645886037662810794110991112723336938759075007493131311-13-1오락관련지출부산 방문시 1인당 여행 지출액_개별여행D2021-03-01 06:05:03
14586.06390313522495548397363995030447945359677369283323731750031134286306516087040001985<NA>302834852712<NA>3802723648238333648307742171019439402761352917154211659524074723928333450722910577260337591-13-1문화관련지출부산 방문시 1인당 여행 지출액_개별여행D2021-03-01 06:05:03
21565.019791232488155627291532139418521099258124771983898414622646429968521702333587<NA>423242569<NA>1212204726512964017361293268315476513732000158151591089295804588964394235318411-13-1운동.레포츠비용부산 방문시 1인당 여행 지출액_개별여행D2021-03-01 06:05:03
310629.0134578354408194441045916749180791290574626129179621240592991308210755750015968280481666773339355<NA>5535186364398<NA>1122116850123431928276646423148821563810745758114412130778395520610776184511266790002162722692463343451-13-1기타비용부산 방문시 1인당 여행 지출액_개별여행D2021-03-01 06:05:03
41993.08871106421557451370194118677234147364392170561632241615371<NA>8374482<NA>46527518920633475044546438116410573946843578688589531431571-18사례수부산여행에서 떠오르는 부산의 도시 이미지_1순위T2021-03-01 06:05:03
5123.07.3%5.2%2.9%6.8%6.2%6.5%10.8%7.1%4.9%2.9%5.4%7.1%6.9%5.9%3.6%6.3%9.4%4.2%6.3%0.0%5.9%<NA>4.8%13.5%3.7%<NA>8.0%6.2%8.5%8.7%3.0%4.3%4.0%13.6%3.4%5.5%5.7%2.7%11.7%10.3%5.7%6.4%2.9%4.7%9.0%9.4%8.4%8.9%1-18컨벤션도시부산여행에서 떠오르는 부산의 도시 이미지_1순위D2021-03-01 06:05:03
6244.012.7%11.8%7.6%14.4%13.3%12.2%13.9%12.8%11.0%20.6%16.3%12.1%12.0%13.5%10.7%25.0%12.5%16.7%6.3%6.7%13.7%<NA>13.3%10.8%12.9%<NA>9.9%15.6%10.6%10.7%8.7%8.3%17.5%16.2%6.8%13.4%11.4%16.4%10.6%14.7%11.7%15.4%7.4%14.1%13.5%20.8%18.9%14.0%1-18영화도시부산여행에서 떠오르는 부산의 도시 이미지_1순위D2021-03-01 06:05:03
777.03.8%3.9%4.0%3.9%4.0%4.3%2.1%3.6%4.4%0.0%6.1%4.7%3.6%3.5%0.0%0.0%0.0%0.0%0.0%6.7%4.0%<NA>4.8%4.1%3.9%<NA>4.3%4.0%3.2%4.4%2.1%6.0%4.0%1.5%4.2%6.7%5.7%4.1%5.3%2.9%3.9%3.8%2.9%2.4%2.2%0.0%0.7%4.5%1-18레저/스포츠도시부산여행에서 떠오르는 부산의 도시 이미지_1순위D2021-03-01 06:05:03
8892.045.4%44.2%45.4%43.4%47.7%45.4%39.2%45.4%44.0%38.2%44.2%51.4%42.1%47.1%60.7%37.5%31.3%37.5%37.5%46.7%42.3%<NA>31.3%39.2%43.2%<NA>40.9%48.4%51.9%46.6%44.6%50.7%39.6%40.3%54.1%43.3%38.1%50.7%44.7%36.8%43.2%35.9%52.9%49.4%37.1%30.2%44.1%41.4%1-18해양도시부산여행에서 떠오르는 부산의 도시 이미지_1순위D2021-03-01 06:05:03
975.04.1%3.5%4.8%3.9%1.8%3.8%5.7%3.0%4.8%5.9%5.4%1.9%4.6%4.1%5.4%0.0%3.1%12.5%0.0%13.3%3.0%<NA>2.4%2.7%3.7%<NA>5.6%2.9%3.2%1.9%4.5%2.4%4.9%4.3%2.6%3.7%6.7%5.5%1.1%4.4%3.7%0.0%5.9%2.4%3.4%5.7%3.5%7.0%1-18문화도시부산여행에서 떠오르는 부산의 도시 이미지_1순위D2021-03-01 06:05:03
totalgender_malegender_femaleage_twentiesage_thirtiesage_fortiesage_fiftiesage_sixtiesmarriage_marriedmarriage_singlemarriage_etcjob_managementjob_professionaljob_officejob_servicejob_salejob_agriculturejob_technicaljob_machineryjob_manufacturaljob_militaryjob_housewifejob_studentjob_unemployedjob_etcincome_u100income_100income_200income_300income_400income_500season_springseason_summerseason_autumnseason_winterprovince_seoulprovince_daeguprovince_incheonprovince_gwangjuprovince_daejeonprovince_ulsanprovince_gyeonggiprovince_gangwonprovince_chungbukprovince_chungnamprovince_jeonbukprovince_jeonnamprovince_gyeongbukprovince_gyeongnamquestion_gubunanswer_contquestion_contanswer_gubunlast_load_dttm
631056.09.4%8.7%8.9%9.5%9.2%8.3%8.7%8.8%9.3%6.9%8.9%8.7%9.1%9.9%6.8%6.7%8.9%11.4%13.5%6.4%9.3%<NA>8.3%9.4%8.4%<NA>9.3%9.2%8.6%9.5%9.9%9.0%9.6%7.9%9.5%9.3%9.6%8.0%9.9%8.4%8.7%8.4%7.7%9.7%9.2%8.0%9.8%7.9%1-6광안리해수욕장부산 여행 방문한 방문지_상위10순위D2021-03-01 06:05:03
64869.06.8%7.9%8.0%7.3%7.2%7.0%7.2%7.3%7.5%8.8%8.6%7.0%7.0%7.5%7.3%5.6%6.2%7.3%13.5%10.6%7.5%<NA>7.6%8.6%7.2%<NA>7.7%6.8%7.0%7.7%8.4%7.7%6.7%6.8%7.6%6.4%7.8%6.1%7.7%5.7%7.9%7.5%7.9%7.9%7.5%6.1%7.7%6.9%1-6국제시장부산 여행 방문한 방문지_상위10순위D2021-03-01 06:05:03
65868.07.4%7.4%7.0%7.5%7.2%7.9%7.8%7.9%6.8%4.4%6.2%6.5%7.4%8.5%7.1%10.1%7.6%8.1%6.8%4.3%8.2%<NA>8.6%10.6%7.6%<NA>7.3%7.0%6.9%7.7%8.4%7.3%6.9%7.3%7.5%6.8%8.5%5.9%7.2%5.2%8.4%7.7%7.4%8.6%8.7%7.0%6.3%5.6%1-6태종대부산 여행 방문한 방문지_상위10순위D2021-03-01 06:05:03
66823.06.7%7.2%7.1%7.2%7.6%7.2%4.5%6.9%7.2%6.3%6.2%7.1%7.5%6.8%8.4%6.7%7.6%6.5%5.4%8.5%7.4%<NA>5.6%5.6%6.6%<NA>6.8%7.1%8.1%7.3%8.1%7.6%5.8%6.3%7.9%8.5%7.4%6.6%7.9%4.4%6.5%6.1%6.0%7.1%6.0%6.4%6.3%7.4%1-6광안대교부산 여행 방문한 방문지_상위10순위D2021-03-01 06:05:03
67795.05.7%7.6%7.3%6.0%8.0%6.5%5.4%7.3%6.2%3.1%4.6%7.0%7.7%4.1%5.2%4.5%4.0%4.1%9.5%5.3%9.5%<NA>4.4%6.4%7.5%<NA>6.1%6.3%7.8%8.1%9.4%8.0%4.1%5.1%8.1%9.0%7.9%6.8%8.3%5.2%7.0%4.5%7.2%7.1%5.6%3.2%4.8%4.1%1-6누리마루APEC하우스부산 여행 방문한 방문지_상위10순위D2021-03-01 06:05:03
68680.05.3%6.2%7.7%5.8%5.0%5.0%4.3%5.0%7.0%5.0%5.2%5.6%6.5%5.9%6.5%7.9%4.0%5.7%4.1%7.4%4.5%<NA>4.9%5.6%6.1%<NA>6.0%5.4%3.7%5.1%6.0%6.2%5.0%5.7%6.4%4.9%5.9%4.8%5.4%3.5%6.2%5.2%6.9%4.9%5.6%4.0%6.3%6.1%1-6BIFF광장(남포동일원)부산 여행 방문한 방문지_상위10순위D2021-03-01 06:05:03
69456.04.1%3.7%5.1%3.4%3.0%3.8%4.6%3.4%4.5%5.6%4.4%3.9%3.4%4.5%3.8%4.5%4.0%4.9%4.1%3.2%2.4%<NA>6.4%3.9%4.4%<NA>3.9%3.9%2.8%2.8%3.6%3.4%5.2%3.8%3.1%3.6%4.3%4.5%3.2%4.1%4.5%5.2%5.0%2.9%3.1%5.1%3.8%3.7%1-6용두산공원부산 여행 방문한 방문지_상위10순위D2021-03-01 06:05:03
70383.02.7%3.7%2.0%3.6%4.1%3.3%3.4%3.7%2.8%1.3%3.9%3.2%3.5%2.8%4.6%1.1%3.1%4.9%1.4%2.1%4.0%<NA>3.2%1.9%2.7%<NA>3.4%3.2%4.3%3.2%2.5%3.8%3.1%3.1%3.4%2.5%3.5%3.2%4.1%1.4%3.3%3.6%3.2%3.1%4.2%2.7%2.9%3.5%1-6해동용궁사부산 여행 방문한 방문지_상위10순위D2021-03-01 06:05:03
711971.08771094415554445367190117376334144359385169561533241615370<NA>8073479<NA>46027218720233274643246137716310373896743277678488531401581-7순위응답부산 여행시 가장 기억에 남는 방문지 1순위_상위 10순위T2021-03-01 06:05:03
72527.027.7%26.0%25.3%24.4%31.5%25.9%27.4%27.8%25.2%26.5%27.8%27.9%28.6%17.8%25.0%26.7%21.2%25.0%25.0%20.0%30.0%<NA>22.5%31.5%24.6%<NA>25.9%29.0%35.3%30.7%24.1%27.5%32.9%21.7%24.9%27.0%24.3%23.3%31.5%46.3%27.3%29.9%20.9%28.6%22.7%20.8%25.7%26.6%1-7해운대해수욕장부산 여행시 가장 기억에 남는 방문지 1순위_상위 10순위D2021-03-01 06:05:03