Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells9
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory113.0 B

Variable types

Categorical1
DateTime1
Text11

Dataset

Description부산광역시_대기질진단평가이온물질_20240307
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15120955

Reproduction

Analysis started2024-03-23 07:03:40.518266
Analysis finished2024-03-23 07:03:44.382730
Duration3.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
221121
3397 
221105
3333 
221102
3270 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row221105
2nd row221102
3rd row221105
4th row221121
5th row221105

Common Values

ValueCountFrequency (%)
221121 3397
34.0%
221105 3333
33.3%
221102 3270
32.7%

Length

2024-03-23T07:03:44.591594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:03:44.911756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
221121 3397
34.0%
221105 3333
33.3%
221102 3270
32.7%
Distinct6712
Distinct (%)67.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-01-01 02:00:00
Maximum2024-01-01 00:00:00
2024-03-23T07:03:45.338040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:03:45.991508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct1736
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-23T07:03:47.094467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.6151
Min length2

Characters and Unicode

Total characters46151
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique842 ?
Unique (%)8.4%

Sample

1st row0.088
2nd row0.059
3rd row0.133
4th row0.145
5th row0.071
ValueCountFrequency (%)
보수 820
 
8.2%
교정 626
 
6.3%
동불 330
 
3.3%
0.068 61
 
0.6%
0.051 60
 
0.6%
0.071 57
 
0.6%
0.05 55
 
0.5%
0.065 55
 
0.5%
0.035 53
 
0.5%
0.039 52
 
0.5%
Other values (1726) 7831
78.3%
2024-03-23T07:03:48.989693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13930
30.2%
. 8178
17.7%
1 3859
 
8.4%
2 2846
 
6.2%
3 2400
 
5.2%
4 2151
 
4.7%
5 2075
 
4.5%
6 1937
 
4.2%
7 1779
 
3.9%
8 1753
 
3.8%
Other values (9) 5243
 
11.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34329
74.4%
Other Punctuation 8178
 
17.7%
Other Letter 3644
 
7.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13930
40.6%
1 3859
 
11.2%
2 2846
 
8.3%
3 2400
 
7.0%
4 2151
 
6.3%
5 2075
 
6.0%
6 1937
 
5.6%
7 1779
 
5.2%
8 1753
 
5.1%
9 1599
 
4.7%
Other Letter
ValueCountFrequency (%)
820
22.5%
820
22.5%
626
17.2%
626
17.2%
330
9.1%
330
9.1%
46
 
1.3%
46
 
1.3%
Other Punctuation
ValueCountFrequency (%)
. 8178
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42507
92.1%
Hangul 3644
 
7.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13930
32.8%
. 8178
19.2%
1 3859
 
9.1%
2 2846
 
6.7%
3 2400
 
5.6%
4 2151
 
5.1%
5 2075
 
4.9%
6 1937
 
4.6%
7 1779
 
4.2%
8 1753
 
4.1%
Hangul
ValueCountFrequency (%)
820
22.5%
820
22.5%
626
17.2%
626
17.2%
330
9.1%
330
9.1%
46
 
1.3%
46
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42507
92.1%
Hangul 3644
 
7.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13930
32.8%
. 8178
19.2%
1 3859
 
9.1%
2 2846
 
6.7%
3 2400
 
5.6%
4 2151
 
5.1%
5 2075
 
4.9%
6 1937
 
4.6%
7 1779
 
4.2%
8 1753
 
4.1%
Hangul
ValueCountFrequency (%)
820
22.5%
820
22.5%
626
17.2%
626
17.2%
330
9.1%
330
9.1%
46
 
1.3%
46
 
1.3%
Distinct5035
Distinct (%)50.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-23T07:03:50.356089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.5651
Min length1

Characters and Unicode

Total characters45651
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3380 ?
Unique (%)33.8%

Sample

1st row2.712
2nd row6.833
3rd row1.791
4th row1.926
5th row2.319
ValueCountFrequency (%)
보수 820
 
8.2%
교정 626
 
6.3%
동불 390
 
3.9%
전단 46
 
0.5%
0.413 11
 
0.1%
0.67 10
 
0.1%
1.21 9
 
0.1%
0.959 8
 
0.1%
0.774 8
 
0.1%
0.691 8
 
0.1%
Other values (5025) 8064
80.6%
2024-03-23T07:03:52.270890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 8109
17.8%
1 5300
11.6%
0 4834
10.6%
2 3934
8.6%
3 3329
7.3%
4 2955
 
6.5%
5 2771
 
6.1%
7 2735
 
6.0%
6 2695
 
5.9%
9 2619
 
5.7%
Other values (9) 6370
14.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33778
74.0%
Other Punctuation 8109
 
17.8%
Other Letter 3764
 
8.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5300
15.7%
0 4834
14.3%
2 3934
11.6%
3 3329
9.9%
4 2955
8.7%
5 2771
8.2%
7 2735
8.1%
6 2695
8.0%
9 2619
7.8%
8 2606
7.7%
Other Letter
ValueCountFrequency (%)
820
21.8%
820
21.8%
626
16.6%
626
16.6%
390
10.4%
390
10.4%
46
 
1.2%
46
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 8109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41887
91.8%
Hangul 3764
 
8.2%

Most frequent character per script

Common
ValueCountFrequency (%)
. 8109
19.4%
1 5300
12.7%
0 4834
11.5%
2 3934
9.4%
3 3329
7.9%
4 2955
 
7.1%
5 2771
 
6.6%
7 2735
 
6.5%
6 2695
 
6.4%
9 2619
 
6.3%
Hangul
ValueCountFrequency (%)
820
21.8%
820
21.8%
626
16.6%
626
16.6%
390
10.4%
390
10.4%
46
 
1.2%
46
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41887
91.8%
Hangul 3764
 
8.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 8109
19.4%
1 5300
12.7%
0 4834
11.5%
2 3934
9.4%
3 3329
7.9%
4 2955
 
7.1%
5 2771
 
6.6%
7 2735
 
6.5%
6 2695
 
6.4%
9 2619
 
6.3%
Hangul
ValueCountFrequency (%)
820
21.8%
820
21.8%
626
16.6%
626
16.6%
390
10.4%
390
10.4%
46
 
1.2%
46
 
1.2%
Distinct1470
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-23T07:03:53.427190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.7077
Min length1

Characters and Unicode

Total characters47077
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique507 ?
Unique (%)5.1%

Sample

1st row0.093
2nd row0.228
3rd row0.1886
4th row0.198
5th row0.239
ValueCountFrequency (%)
보수 820
 
8.2%
교정 627
 
6.3%
동불 368
 
3.7%
0.086 47
 
0.5%
전단 46
 
0.5%
0.077 43
 
0.4%
0.084 43
 
0.4%
0.081 43
 
0.4%
0.109 42
 
0.4%
0.091 41
 
0.4%
Other values (1460) 7880
78.8%
2024-03-23T07:03:55.216215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14992
31.8%
. 8108
17.2%
1 4494
 
9.5%
2 2740
 
5.8%
3 2166
 
4.6%
4 1931
 
4.1%
5 1823
 
3.9%
7 1816
 
3.9%
8 1783
 
3.8%
6 1773
 
3.8%
Other values (9) 5451
 
11.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35247
74.9%
Other Punctuation 8108
 
17.2%
Other Letter 3722
 
7.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14992
42.5%
1 4494
 
12.8%
2 2740
 
7.8%
3 2166
 
6.1%
4 1931
 
5.5%
5 1823
 
5.2%
7 1816
 
5.2%
8 1783
 
5.1%
6 1773
 
5.0%
9 1729
 
4.9%
Other Letter
ValueCountFrequency (%)
820
22.0%
820
22.0%
627
16.8%
627
16.8%
368
9.9%
368
9.9%
46
 
1.2%
46
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 8108
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 43355
92.1%
Hangul 3722
 
7.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14992
34.6%
. 8108
18.7%
1 4494
 
10.4%
2 2740
 
6.3%
3 2166
 
5.0%
4 1931
 
4.5%
5 1823
 
4.2%
7 1816
 
4.2%
8 1783
 
4.1%
6 1773
 
4.1%
Hangul
ValueCountFrequency (%)
820
22.0%
820
22.0%
627
16.8%
627
16.8%
368
9.9%
368
9.9%
46
 
1.2%
46
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43355
92.1%
Hangul 3722
 
7.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14992
34.6%
. 8108
18.7%
1 4494
 
10.4%
2 2740
 
6.3%
3 2166
 
5.0%
4 1931
 
4.5%
5 1823
 
4.2%
7 1816
 
4.2%
8 1783
 
4.1%
6 1773
 
4.1%
Hangul
ValueCountFrequency (%)
820
22.0%
820
22.0%
627
16.8%
627
16.8%
368
9.9%
368
9.9%
46
 
1.2%
46
 
1.2%
Distinct1091
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-23T07:03:56.364096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.7759
Min length1

Characters and Unicode

Total characters47759
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique475 ?
Unique (%)4.8%

Sample

1st row0.021
2nd row0.023
3rd row0.078
4th row0.034
5th row0.034
ValueCountFrequency (%)
보수 820
 
8.2%
교정 626
 
6.3%
동불 364
 
3.6%
0.016 132
 
1.3%
0.017 130
 
1.3%
0.014 129
 
1.3%
0.018 117
 
1.2%
0.012 115
 
1.1%
0.02 109
 
1.1%
0.015 109
 
1.1%
Other values (1081) 7349
73.5%
2024-03-23T07:03:58.067635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17807
37.3%
. 8143
17.1%
1 3841
 
8.0%
2 2674
 
5.6%
3 2113
 
4.4%
4 1852
 
3.9%
5 1731
 
3.6%
6 1618
 
3.4%
7 1468
 
3.1%
9 1410
 
3.0%
Other values (9) 5102
 
10.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35904
75.2%
Other Punctuation 8143
 
17.1%
Other Letter 3712
 
7.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17807
49.6%
1 3841
 
10.7%
2 2674
 
7.4%
3 2113
 
5.9%
4 1852
 
5.2%
5 1731
 
4.8%
6 1618
 
4.5%
7 1468
 
4.1%
9 1410
 
3.9%
8 1390
 
3.9%
Other Letter
ValueCountFrequency (%)
820
22.1%
820
22.1%
626
16.9%
626
16.9%
364
9.8%
364
9.8%
46
 
1.2%
46
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 8143
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44047
92.2%
Hangul 3712
 
7.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 17807
40.4%
. 8143
18.5%
1 3841
 
8.7%
2 2674
 
6.1%
3 2113
 
4.8%
4 1852
 
4.2%
5 1731
 
3.9%
6 1618
 
3.7%
7 1468
 
3.3%
9 1410
 
3.2%
Hangul
ValueCountFrequency (%)
820
22.1%
820
22.1%
626
16.9%
626
16.9%
364
9.8%
364
9.8%
46
 
1.2%
46
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44047
92.2%
Hangul 3712
 
7.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17807
40.4%
. 8143
18.5%
1 3841
 
8.7%
2 2674
 
6.1%
3 2113
 
4.8%
4 1852
 
4.2%
5 1731
 
3.9%
6 1618
 
3.7%
7 1468
 
3.3%
9 1410
 
3.2%
Hangul
ValueCountFrequency (%)
820
22.1%
820
22.1%
626
16.9%
626
16.9%
364
9.8%
364
9.8%
46
 
1.2%
46
 
1.2%
Distinct1561
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-23T07:03:59.265656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.7385
Min length2

Characters and Unicode

Total characters47385
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique629 ?
Unique (%)6.3%

Sample

1st row0.16
2nd row0.038
3rd row0.245
4th row0.093
5th row0.077
ValueCountFrequency (%)
보수 820
 
8.2%
교정 626
 
6.3%
동불 338
 
3.4%
0.042 61
 
0.6%
0.049 50
 
0.5%
0.045 47
 
0.5%
0.048 47
 
0.5%
전단 46
 
0.5%
0.037 44
 
0.4%
0.041 44
 
0.4%
Other values (1551) 7877
78.8%
2024-03-23T07:04:01.254235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14692
31.0%
. 8170
17.2%
1 3868
 
8.2%
2 3036
 
6.4%
3 2657
 
5.6%
4 2388
 
5.0%
5 2086
 
4.4%
6 1795
 
3.8%
7 1753
 
3.7%
8 1690
 
3.6%
Other values (9) 5250
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35555
75.0%
Other Punctuation 8170
 
17.2%
Other Letter 3660
 
7.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14692
41.3%
1 3868
 
10.9%
2 3036
 
8.5%
3 2657
 
7.5%
4 2388
 
6.7%
5 2086
 
5.9%
6 1795
 
5.0%
7 1753
 
4.9%
8 1690
 
4.8%
9 1590
 
4.5%
Other Letter
ValueCountFrequency (%)
820
22.4%
820
22.4%
626
17.1%
626
17.1%
338
9.2%
338
9.2%
46
 
1.3%
46
 
1.3%
Other Punctuation
ValueCountFrequency (%)
. 8170
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 43725
92.3%
Hangul 3660
 
7.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14692
33.6%
. 8170
18.7%
1 3868
 
8.8%
2 3036
 
6.9%
3 2657
 
6.1%
4 2388
 
5.5%
5 2086
 
4.8%
6 1795
 
4.1%
7 1753
 
4.0%
8 1690
 
3.9%
Hangul
ValueCountFrequency (%)
820
22.4%
820
22.4%
626
17.1%
626
17.1%
338
9.2%
338
9.2%
46
 
1.3%
46
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43725
92.3%
Hangul 3660
 
7.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14692
33.6%
. 8170
18.7%
1 3868
 
8.8%
2 3036
 
6.9%
3 2657
 
6.1%
4 2388
 
5.5%
5 2086
 
4.8%
6 1795
 
4.1%
7 1753
 
4.0%
8 1690
 
3.9%
Hangul
ValueCountFrequency (%)
820
22.4%
820
22.4%
626
17.1%
626
17.1%
338
9.2%
338
9.2%
46
 
1.3%
46
 
1.3%
Distinct1944
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-23T07:04:02.694453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.4353
Min length1

Characters and Unicode

Total characters44353
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1109 ?
Unique (%)11.1%

Sample

1st row0.376
2nd row0.791
3rd row0.0564
4th row0.151
5th row0.249
ValueCountFrequency (%)
보수 820
 
8.2%
교정 626
 
6.3%
동불 368
 
3.7%
전단 46
 
0.5%
0.13 38
 
0.4%
0.118 38
 
0.4%
0.116 38
 
0.4%
0.15 36
 
0.4%
0.142 35
 
0.4%
0.136 35
 
0.4%
Other values (1934) 7920
79.2%
2024-03-23T07:04:05.177280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9057
20.4%
. 8137
18.3%
1 4733
10.7%
2 3549
 
8.0%
3 2831
 
6.4%
4 2411
 
5.4%
5 2204
 
5.0%
6 2010
 
4.5%
9 1925
 
4.3%
8 1889
 
4.3%
Other values (9) 5607
12.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32496
73.3%
Other Punctuation 8137
 
18.3%
Other Letter 3720
 
8.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9057
27.9%
1 4733
14.6%
2 3549
 
10.9%
3 2831
 
8.7%
4 2411
 
7.4%
5 2204
 
6.8%
6 2010
 
6.2%
9 1925
 
5.9%
8 1889
 
5.8%
7 1887
 
5.8%
Other Letter
ValueCountFrequency (%)
820
22.0%
820
22.0%
626
16.8%
626
16.8%
368
9.9%
368
9.9%
46
 
1.2%
46
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 8137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 40633
91.6%
Hangul 3720
 
8.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9057
22.3%
. 8137
20.0%
1 4733
11.6%
2 3549
 
8.7%
3 2831
 
7.0%
4 2411
 
5.9%
5 2204
 
5.4%
6 2010
 
4.9%
9 1925
 
4.7%
8 1889
 
4.6%
Hangul
ValueCountFrequency (%)
820
22.0%
820
22.0%
626
16.8%
626
16.8%
368
9.9%
368
9.9%
46
 
1.2%
46
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40633
91.6%
Hangul 3720
 
8.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9057
22.3%
. 8137
20.0%
1 4733
11.6%
2 3549
 
8.7%
3 2831
 
7.0%
4 2411
 
5.9%
5 2204
 
5.4%
6 2010
 
4.9%
9 1925
 
4.7%
8 1889
 
4.6%
Hangul
ValueCountFrequency (%)
820
22.0%
820
22.0%
626
16.8%
626
16.8%
368
9.9%
368
9.9%
46
 
1.2%
46
 
1.2%
Distinct4714
Distinct (%)47.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-23T07:04:06.314198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.4524
Min length1

Characters and Unicode

Total characters44524
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3044 ?
Unique (%)30.4%

Sample

1st row6.505
2nd row12.672
3rd row0.866
4th row1.586
5th row5.439
ValueCountFrequency (%)
보수 820
 
8.2%
교정 626
 
6.3%
동불 380
 
3.8%
전단 46
 
0.5%
0.431 10
 
0.1%
0.329 10
 
0.1%
0.36 10
 
0.1%
0.443 9
 
0.1%
0.308 9
 
0.1%
0.666 9
 
0.1%
Other values (4704) 8071
80.7%
2024-03-23T07:04:07.750180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 8123
18.2%
1 4626
10.4%
0 4566
10.3%
2 3602
8.1%
4 3195
 
7.2%
3 3175
 
7.1%
5 2961
 
6.7%
6 2778
 
6.2%
7 2638
 
5.9%
8 2561
 
5.8%
Other values (9) 6299
14.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32657
73.3%
Other Punctuation 8123
 
18.2%
Other Letter 3744
 
8.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4626
14.2%
0 4566
14.0%
2 3602
11.0%
4 3195
9.8%
3 3175
9.7%
5 2961
9.1%
6 2778
8.5%
7 2638
8.1%
8 2561
7.8%
9 2555
7.8%
Other Letter
ValueCountFrequency (%)
820
21.9%
820
21.9%
626
16.7%
626
16.7%
380
10.1%
380
10.1%
46
 
1.2%
46
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 8123
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 40780
91.6%
Hangul 3744
 
8.4%

Most frequent character per script

Common
ValueCountFrequency (%)
. 8123
19.9%
1 4626
11.3%
0 4566
11.2%
2 3602
8.8%
4 3195
 
7.8%
3 3175
 
7.8%
5 2961
 
7.3%
6 2778
 
6.8%
7 2638
 
6.5%
8 2561
 
6.3%
Hangul
ValueCountFrequency (%)
820
21.9%
820
21.9%
626
16.7%
626
16.7%
380
10.1%
380
10.1%
46
 
1.2%
46
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40780
91.6%
Hangul 3744
 
8.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 8123
19.9%
1 4626
11.3%
0 4566
11.2%
2 3602
8.8%
4 3195
 
7.8%
3 3175
 
7.8%
5 2961
 
7.3%
6 2778
 
6.8%
7 2638
 
6.5%
8 2561
 
6.3%
Hangul
ValueCountFrequency (%)
820
21.9%
820
21.9%
626
16.7%
626
16.7%
380
10.1%
380
10.1%
46
 
1.2%
46
 
1.2%
Distinct4404
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-23T07:04:09.015376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.3865
Min length1

Characters and Unicode

Total characters43865
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2437 ?
Unique (%)24.4%

Sample

1st row1.491
2nd row3.988
3rd row0.91
4th row2.496
5th row2.9
ValueCountFrequency (%)
보수 820
 
8.2%
교정 629
 
6.3%
동불 509
 
5.1%
전단 46
 
0.5%
0.978 9
 
0.1%
1.518 9
 
0.1%
1.781 8
 
0.1%
1.555 8
 
0.1%
0.615 7
 
0.1%
0.77 7
 
0.1%
Other values (4394) 7948
79.5%
2024-03-23T07:04:10.762468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7992
18.2%
1 5144
11.7%
2 3954
9.0%
0 3484
7.9%
3 3461
7.9%
4 2932
 
6.7%
5 2772
 
6.3%
6 2672
 
6.1%
7 2560
 
5.8%
8 2454
 
5.6%
Other values (9) 6440
14.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31865
72.6%
Other Punctuation 7992
 
18.2%
Other Letter 4008
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5144
16.1%
2 3954
12.4%
0 3484
10.9%
3 3461
10.9%
4 2932
9.2%
5 2772
8.7%
6 2672
8.4%
7 2560
8.0%
8 2454
7.7%
9 2432
7.6%
Other Letter
ValueCountFrequency (%)
820
20.5%
820
20.5%
629
15.7%
629
15.7%
509
12.7%
509
12.7%
46
 
1.1%
46
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 7992
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39857
90.9%
Hangul 4008
 
9.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7992
20.1%
1 5144
12.9%
2 3954
9.9%
0 3484
8.7%
3 3461
8.7%
4 2932
 
7.4%
5 2772
 
7.0%
6 2672
 
6.7%
7 2560
 
6.4%
8 2454
 
6.2%
Hangul
ValueCountFrequency (%)
820
20.5%
820
20.5%
629
15.7%
629
15.7%
509
12.7%
509
12.7%
46
 
1.1%
46
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39857
90.9%
Hangul 4008
 
9.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7992
20.1%
1 5144
12.9%
2 3954
9.9%
0 3484
8.7%
3 3461
8.7%
4 2932
 
7.4%
5 2772
 
7.0%
6 2672
 
6.7%
7 2560
 
6.4%
8 2454
 
6.2%
Hangul
ValueCountFrequency (%)
820
20.5%
820
20.5%
629
15.7%
629
15.7%
509
12.7%
509
12.7%
46
 
1.1%
46
 
1.1%
Distinct6799
Distinct (%)68.0%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-23T07:04:11.798707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.526558
Min length2

Characters and Unicode

Total characters55249
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5045 ?
Unique (%)50.5%

Sample

1st row1.6148
2nd row0.9251
3rd row0.3747
4th row0.5062
5th row0.5947
ValueCountFrequency (%)
교정 614
 
6.1%
동불 221
 
2.2%
전단 95
 
1.0%
0.0012 8
 
0.1%
0.0014 7
 
0.1%
0.0018 7
 
0.1%
0.9251 5
 
0.1%
0.6093 5
 
0.1%
0.6493 5
 
0.1%
0.0021 5
 
0.1%
Other values (6789) 9025
90.3%
2024-03-23T07:04:13.588297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9652
17.5%
. 9067
16.4%
1 5327
9.6%
2 4137
7.5%
3 3936
7.1%
4 3812
 
6.9%
5 3758
 
6.8%
6 3603
 
6.5%
7 3484
 
6.3%
8 3354
 
6.1%
Other values (7) 5119
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44322
80.2%
Other Punctuation 9067
 
16.4%
Other Letter 1860
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9652
21.8%
1 5327
12.0%
2 4137
9.3%
3 3936
8.9%
4 3812
 
8.6%
5 3758
 
8.5%
6 3603
 
8.1%
7 3484
 
7.9%
8 3354
 
7.6%
9 3259
 
7.4%
Other Letter
ValueCountFrequency (%)
614
33.0%
614
33.0%
221
 
11.9%
221
 
11.9%
95
 
5.1%
95
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 9067
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53389
96.6%
Hangul 1860
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9652
18.1%
. 9067
17.0%
1 5327
10.0%
2 4137
7.7%
3 3936
7.4%
4 3812
 
7.1%
5 3758
 
7.0%
6 3603
 
6.7%
7 3484
 
6.5%
8 3354
 
6.3%
Hangul
ValueCountFrequency (%)
614
33.0%
614
33.0%
221
 
11.9%
221
 
11.9%
95
 
5.1%
95
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53389
96.6%
Hangul 1860
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9652
18.1%
. 9067
17.0%
1 5327
10.0%
2 4137
7.7%
3 3936
7.4%
4 3812
 
7.1%
5 3758
 
7.0%
6 3603
 
6.7%
7 3484
 
6.5%
8 3354
 
6.3%
Hangul
ValueCountFrequency (%)
614
33.0%
614
33.0%
221
 
11.9%
221
 
11.9%
95
 
5.1%
95
 
5.1%
Distinct8360
Distinct (%)83.6%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-23T07:04:14.532507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.5295589
Min length1

Characters and Unicode

Total characters55279
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7698 ?
Unique (%)77.0%

Sample

1st row4.2854
2nd row8.3529
3rd row1.3154
4th row2.3803
5th row2.478
ValueCountFrequency (%)
교정 614
 
6.1%
동불 217
 
2.2%
전단 95
 
1.0%
2.5271 5
 
0.1%
1.3794 4
 
< 0.1%
2.6911 4
 
< 0.1%
3.1499 4
 
< 0.1%
2.1874 4
 
< 0.1%
0 4
 
< 0.1%
3.8733 3
 
< 0.1%
Other values (8350) 9043
90.5%
2024-03-23T07:04:15.970103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9066
16.4%
2 6236
11.3%
3 5545
10.0%
1 5310
9.6%
4 4855
8.8%
5 4274
7.7%
6 4008
7.3%
7 3962
7.2%
8 3728
6.7%
9 3612
 
6.5%
Other values (7) 4683
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44361
80.2%
Other Punctuation 9066
 
16.4%
Other Letter 1852
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 6236
14.1%
3 5545
12.5%
1 5310
12.0%
4 4855
10.9%
5 4274
9.6%
6 4008
9.0%
7 3962
8.9%
8 3728
8.4%
9 3612
8.1%
0 2831
6.4%
Other Letter
ValueCountFrequency (%)
614
33.2%
614
33.2%
217
 
11.7%
217
 
11.7%
95
 
5.1%
95
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 9066
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53427
96.6%
Hangul 1852
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9066
17.0%
2 6236
11.7%
3 5545
10.4%
1 5310
9.9%
4 4855
9.1%
5 4274
8.0%
6 4008
7.5%
7 3962
7.4%
8 3728
7.0%
9 3612
 
6.8%
Hangul
ValueCountFrequency (%)
614
33.2%
614
33.2%
217
 
11.7%
217
 
11.7%
95
 
5.1%
95
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53427
96.6%
Hangul 1852
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9066
17.0%
2 6236
11.7%
3 5545
10.4%
1 5310
9.9%
4 4855
9.1%
5 4274
8.0%
6 4008
7.5%
7 3962
7.4%
8 3728
7.0%
9 3612
 
6.8%
Hangul
ValueCountFrequency (%)
614
33.2%
614
33.2%
217
 
11.7%
217
 
11.7%
95
 
5.1%
95
 
5.1%
Distinct8462
Distinct (%)84.6%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-23T07:04:16.854656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.5296589
Min length1

Characters and Unicode

Total characters55280
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7883 ?
Unique (%)78.9%

Sample

1st row5.9002
2nd row9.2781
3rd row1.69
4th row2.8865
5th row3.0727
ValueCountFrequency (%)
교정 614
 
6.1%
동불 216
 
2.2%
전단 95
 
1.0%
3.4775 4
 
< 0.1%
2.3416 4
 
< 0.1%
5.5233 3
 
< 0.1%
2.3504 3
 
< 0.1%
3.3059 3
 
< 0.1%
3.0902 3
 
< 0.1%
5.0359 3
 
< 0.1%
Other values (8452) 9049
90.5%
2024-03-23T07:04:18.352572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9068
16.4%
2 5757
10.4%
3 5635
10.2%
4 5040
9.1%
1 4731
8.6%
5 4446
8.0%
6 4196
7.6%
7 4002
7.2%
8 3961
7.2%
9 3868
7.0%
Other values (7) 4576
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44362
80.2%
Other Punctuation 9068
 
16.4%
Other Letter 1850
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 5757
13.0%
3 5635
12.7%
4 5040
11.4%
1 4731
10.7%
5 4446
10.0%
6 4196
9.5%
7 4002
9.0%
8 3961
8.9%
9 3868
8.7%
0 2726
6.1%
Other Letter
ValueCountFrequency (%)
614
33.2%
614
33.2%
216
 
11.7%
216
 
11.7%
95
 
5.1%
95
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 9068
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53430
96.7%
Hangul 1850
 
3.3%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9068
17.0%
2 5757
10.8%
3 5635
10.5%
4 5040
9.4%
1 4731
8.9%
5 4446
8.3%
6 4196
7.9%
7 4002
7.5%
8 3961
7.4%
9 3868
7.2%
Hangul
ValueCountFrequency (%)
614
33.2%
614
33.2%
216
 
11.7%
216
 
11.7%
95
 
5.1%
95
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53430
96.7%
Hangul 1850
 
3.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9068
17.0%
2 5757
10.8%
3 5635
10.5%
4 5040
9.4%
1 4731
8.9%
5 4446
8.3%
6 4196
7.9%
7 4002
7.5%
8 3961
7.4%
9 3868
7.2%
Hangul
ValueCountFrequency (%)
614
33.2%
614
33.2%
216
 
11.7%
216
 
11.7%
95
 
5.1%
95
 
5.1%

Missing values

2024-03-23T07:03:42.782162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T07:03:43.626830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-03-23T07:03:44.201866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

대기질지점코드측정날짜나트륨이온암모니아이온칼륨이온마그네슘이온칼슘이온염소이온질산이온황산이온원소탄소유기탄소총탄소
34382211052023-02-17 19:000.0882.7120.0930.0210.160.3766.5051.4911.61484.28545.9002
30132211022023-02-11 21:000.0596.8330.2280.0230.0380.79112.6723.9880.92518.35299.2781
70532211052023-04-09 00:000.1331.7910.18860.0780.2450.05640.8660.910.37471.31541.69
58102211212023-03-22 17:000.1451.9260.1980.0340.0930.1511.5862.4960.50622.38032.8865
28472211052023-02-09 14:000.0712.3190.2390.0340.0770.2495.4392.90.59472.4783.0727
169972211212023-08-25 02:000.0280.210.090.0120.02140.150.130.5510.66761.93082.5984
25182211022023-02-05 00:000.0613.8130.1110.3170.0418.7162.3891.63957.96569.6052
224492211052023-11-08 20:00교정교정교정교정교정교정교정교정교정교정교정
121542211022023-06-18 20:000.0512.5610.04790.00260.03220.1282.0873.6561.01953.87254.8921
101642211052023-05-22 05:000.1181.3790.060.0280.4310.1571.2543.6381.0165.28036.2963
대기질지점코드측정날짜나트륨이온암모니아이온칼륨이온마그네슘이온칼슘이온염소이온질산이온황산이온원소탄소유기탄소총탄소
138912211022023-07-12 23:000.2420.8520.00250.020.0160.721.4751.0460.49362.85733.3509
261002211052023-12-29 13:000.01674.7170.01640.01780.03680.4089.133.2151.34274.7076.0497
252342211022023-12-17 12:000.04931.3715동불0.03120.03380.3021.3291.3130.32651.60121.9277
192742211212023-09-25 17:00동불동불동불동불동불동불동불동불1.71853.13214.8506
194932211212023-09-28 18:00보수보수보수보수보수보수보수보수0.14722.29232.4395
155202211022023-08-04 14:000.1291.280.03710.01740.02050.2260.4562.2760.67733.42434.1016
119802211022023-06-16 10:00전단전단전단전단전단전단전단전단전단전단전단
255872211052023-12-22 10:000.01130.68590.0120.00990.00670.1091.0181.060.78681.66112.4479
15252211022023-01-22 05:000.02670.6260.0290.0090.0240.4811.6150.4540.21663.01573.2322
154912211212023-08-04 04:000.1610.710.0870.1670.08280.3240.6482.2681.72423.93085.655