Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells15
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_대기질 진단평가시스템의 이온물질 데이터로 대기질지점코드, 측정날짜, 나트륨이온, 암모니아이온, 칼륨이온, 마그네슘이온, 칼슘이온, 염소이온, 질산이온, 황산이온, 원소탄소, 유기탄소, 총탄소 등의 정보를 제공합니다.
Author부산광역시
URLhttps://www.data.go.kr/data/15120955/fileData.do

Reproduction

Analysis started2024-03-23 05:41:26.265572
Analysis finished2024-03-23 05:41:30.662794
Duration4.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
221121
3337 
221105
3336 
221102
3327 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
221121 3337
33.4%
221105 3336
33.4%
221102 3327
33.3%

Length

2024-03-23T05:41:31.172522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:41:31.645224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
221121 3337
33.4%
221105 3336
33.4%
221102 3327
33.3%
Distinct6634
Distinct (%)66.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-01-01 03:00:00
Maximum2024-01-01 00:00:00
2024-03-23T05:41:32.239653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:41:32.842665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct1797
Distinct (%)18.0%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-23T05:41:33.911336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.6247625
Min length2

Characters and Unicode

Total characters46243
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

Unique892 ?
Unique (%)8.9%

Sample

1st row교정
2nd row0.09
3rd row0.124
4th row0.133
5th row0.086
ValueCountFrequency (%)
보수 872
 
8.7%
교정 611
 
6.1%
동불 310
 
3.1%
0.052 62
 
0.6%
0.047 57
 
0.6%
0.031 55
 
0.6%
0.043 53
 
0.5%
0.055 53
 
0.5%
0.038 51
 
0.5%
0.049 50
 
0.5%
Other values (1787) 7825
78.3%
2024-03-23T05:41:35.557678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13931
30.1%
. 8165
17.7%
1 3867
 
8.4%
2 2849
 
6.2%
3 2478
 
5.4%
4 2240
 
4.8%
5 2093
 
4.5%
6 1877
 
4.1%
7 1775
 
3.8%
8 1657
 
3.6%
Other values (9) 5311
 
11.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34410
74.4%
Other Punctuation 8165
 
17.7%
Other Letter 3668
 
7.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13931
40.5%
1 3867
 
11.2%
2 2849
 
8.3%
3 2478
 
7.2%
4 2240
 
6.5%
5 2093
 
6.1%
6 1877
 
5.5%
7 1775
 
5.2%
8 1657
 
4.8%
9 1643
 
4.8%
Other Letter
ValueCountFrequency (%)
872
23.8%
872
23.8%
611
16.7%
611
16.7%
310
 
8.5%
310
 
8.5%
41
 
1.1%
41
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 8165
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42575
92.1%
Hangul 3668
 
7.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13931
32.7%
. 8165
19.2%
1 3867
 
9.1%
2 2849
 
6.7%
3 2478
 
5.8%
4 2240
 
5.3%
5 2093
 
4.9%
6 1877
 
4.4%
7 1775
 
4.2%
8 1657
 
3.9%
Hangul
ValueCountFrequency (%)
872
23.8%
872
23.8%
611
16.7%
611
16.7%
310
 
8.5%
310
 
8.5%
41
 
1.1%
41
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42575
92.1%
Hangul 3668
 
7.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13931
32.7%
. 8165
19.2%
1 3867
 
9.1%
2 2849
 
6.7%
3 2478
 
5.8%
4 2240
 
5.3%
5 2093
 
4.9%
6 1877
 
4.4%
7 1775
 
4.2%
8 1657
 
3.9%
Hangul
ValueCountFrequency (%)
872
23.8%
872
23.8%
611
16.7%
611
16.7%
310
 
8.5%
310
 
8.5%
41
 
1.1%
41
 
1.1%
Distinct5057
Distinct (%)50.6%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-23T05:41:36.860097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.5646565
Min length1

Characters and Unicode

Total characters45642
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

Unique3407 ?
Unique (%)34.1%

Sample

1st row교정
2nd row0.582
3rd row10.893
4th row0.865
5th row동불
ValueCountFrequency (%)
보수 872
 
8.7%
교정 611
 
6.1%
동불 364
 
3.6%
전단 41
 
0.4%
1.608 10
 
0.1%
0.965 9
 
0.1%
0.723 9
 
0.1%
0.335 9
 
0.1%
0.753 9
 
0.1%
0.918 8
 
0.1%
Other values (5047) 8057
80.6%
2024-03-23T05:41:38.899167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 8102
17.8%
1 5243
11.5%
0 4831
10.6%
2 4026
8.8%
3 3255
7.1%
4 2950
 
6.5%
5 2751
 
6.0%
7 2716
 
6.0%
6 2698
 
5.9%
9 2678
 
5.9%
Other values (9) 6392
14.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33764
74.0%
Other Punctuation 8102
 
17.8%
Other Letter 3776
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5243
15.5%
0 4831
14.3%
2 4026
11.9%
3 3255
9.6%
4 2950
8.7%
5 2751
8.1%
7 2716
8.0%
6 2698
8.0%
9 2678
7.9%
8 2616
7.7%
Other Letter
ValueCountFrequency (%)
872
23.1%
872
23.1%
611
16.2%
611
16.2%
364
9.6%
364
9.6%
41
 
1.1%
41
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 8102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41866
91.7%
Hangul 3776
 
8.3%

Most frequent character per script

Common
ValueCountFrequency (%)
. 8102
19.4%
1 5243
12.5%
0 4831
11.5%
2 4026
9.6%
3 3255
7.8%
4 2950
 
7.0%
5 2751
 
6.6%
7 2716
 
6.5%
6 2698
 
6.4%
9 2678
 
6.4%
Hangul
ValueCountFrequency (%)
872
23.1%
872
23.1%
611
16.2%
611
16.2%
364
9.6%
364
9.6%
41
 
1.1%
41
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41866
91.7%
Hangul 3776
 
8.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 8102
19.4%
1 5243
12.5%
0 4831
11.5%
2 4026
9.6%
3 3255
7.8%
4 2950
 
7.0%
5 2751
 
6.6%
7 2716
 
6.5%
6 2698
 
6.4%
9 2678
 
6.4%
Hangul
ValueCountFrequency (%)
872
23.1%
872
23.1%
611
16.2%
611
16.2%
364
9.6%
364
9.6%
41
 
1.1%
41
 
1.1%
Distinct1463
Distinct (%)14.6%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-23T05:41:39.998907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.7158716
Min length1

Characters and Unicode

Total characters47154
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

Unique469 ?
Unique (%)4.7%

Sample

1st row교정
2nd row0.093
3rd row0.139
4th row0.082
5th row0.0492
ValueCountFrequency (%)
보수 872
 
8.7%
교정 612
 
6.1%
동불 351
 
3.5%
0.078 45
 
0.5%
0.091 44
 
0.4%
0.084 43
 
0.4%
0.077 43
 
0.4%
전단 41
 
0.4%
0.086 40
 
0.4%
0.069 39
 
0.4%
Other values (1453) 7869
78.7%
2024-03-23T05:41:41.419230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15098
32.0%
. 8085
17.1%
1 4404
 
9.3%
2 2667
 
5.7%
3 2135
 
4.5%
4 1983
 
4.2%
5 1849
 
3.9%
7 1844
 
3.9%
8 1798
 
3.8%
6 1793
 
3.8%
Other values (9) 5498
 
11.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35317
74.9%
Other Punctuation 8085
 
17.1%
Other Letter 3752
 
8.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15098
42.7%
1 4404
 
12.5%
2 2667
 
7.6%
3 2135
 
6.0%
4 1983
 
5.6%
5 1849
 
5.2%
7 1844
 
5.2%
8 1798
 
5.1%
6 1793
 
5.1%
9 1746
 
4.9%
Other Letter
ValueCountFrequency (%)
872
23.2%
872
23.2%
612
16.3%
612
16.3%
351
9.4%
351
9.4%
41
 
1.1%
41
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 8085
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 43402
92.0%
Hangul 3752
 
8.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15098
34.8%
. 8085
18.6%
1 4404
 
10.1%
2 2667
 
6.1%
3 2135
 
4.9%
4 1983
 
4.6%
5 1849
 
4.3%
7 1844
 
4.2%
8 1798
 
4.1%
6 1793
 
4.1%
Hangul
ValueCountFrequency (%)
872
23.2%
872
23.2%
612
16.3%
612
16.3%
351
9.4%
351
9.4%
41
 
1.1%
41
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43402
92.0%
Hangul 3752
 
8.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15098
34.8%
. 8085
18.6%
1 4404
 
10.1%
2 2667
 
6.1%
3 2135
 
4.9%
4 1983
 
4.6%
5 1849
 
4.3%
7 1844
 
4.2%
8 1798
 
4.1%
6 1793
 
4.1%
Hangul
ValueCountFrequency (%)
872
23.2%
872
23.2%
612
16.3%
612
16.3%
351
9.4%
351
9.4%
41
 
1.1%
41
 
1.1%
Distinct1066
Distinct (%)10.7%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-23T05:41:42.566003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.7867787
Min length2

Characters and Unicode

Total characters47863
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

Unique438 ?
Unique (%)4.4%

Sample

1st row교정
2nd row0.0261
3rd row0.022
4th row0.017
5th row0.0222
ValueCountFrequency (%)
보수 872
 
8.7%
교정 611
 
6.1%
동불 345
 
3.5%
0.02 125
 
1.3%
0.015 122
 
1.2%
0.017 121
 
1.2%
0.021 119
 
1.2%
0.016 118
 
1.2%
0.019 113
 
1.1%
0.014 104
 
1.0%
Other values (1056) 7349
73.5%
2024-03-23T05:41:44.049691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17845
37.3%
. 8130
17.0%
1 3833
 
8.0%
2 2690
 
5.6%
3 2130
 
4.5%
4 1900
 
4.0%
5 1701
 
3.6%
6 1665
 
3.5%
7 1443
 
3.0%
8 1395
 
2.9%
Other values (9) 5131
 
10.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35995
75.2%
Other Punctuation 8130
 
17.0%
Other Letter 3738
 
7.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17845
49.6%
1 3833
 
10.6%
2 2690
 
7.5%
3 2130
 
5.9%
4 1900
 
5.3%
5 1701
 
4.7%
6 1665
 
4.6%
7 1443
 
4.0%
8 1395
 
3.9%
9 1393
 
3.9%
Other Letter
ValueCountFrequency (%)
872
23.3%
872
23.3%
611
16.3%
611
16.3%
345
 
9.2%
345
 
9.2%
41
 
1.1%
41
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 8130
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44125
92.2%
Hangul 3738
 
7.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 17845
40.4%
. 8130
18.4%
1 3833
 
8.7%
2 2690
 
6.1%
3 2130
 
4.8%
4 1900
 
4.3%
5 1701
 
3.9%
6 1665
 
3.8%
7 1443
 
3.3%
8 1395
 
3.2%
Hangul
ValueCountFrequency (%)
872
23.3%
872
23.3%
611
16.3%
611
16.3%
345
 
9.2%
345
 
9.2%
41
 
1.1%
41
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44125
92.2%
Hangul 3738
 
7.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17845
40.4%
. 8130
18.4%
1 3833
 
8.7%
2 2690
 
6.1%
3 2130
 
4.8%
4 1900
 
4.3%
5 1701
 
3.9%
6 1665
 
3.8%
7 1443
 
3.3%
8 1395
 
3.2%
Hangul
ValueCountFrequency (%)
872
23.3%
872
23.3%
611
16.3%
611
16.3%
345
 
9.2%
345
 
9.2%
41
 
1.1%
41
 
1.1%
Distinct1592
Distinct (%)15.9%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-23T05:41:45.129157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.7458746
Min length2

Characters and Unicode

Total characters47454
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

Unique648 ?
Unique (%)6.5%

Sample

1st row교정
2nd row0.0345
3rd row0.129
4th row0.115
5th row0.061
ValueCountFrequency (%)
보수 872
 
8.7%
교정 611
 
6.1%
동불 315
 
3.2%
0.042 55
 
0.6%
0.054 48
 
0.5%
0.047 46
 
0.5%
0.032 45
 
0.5%
0.049 44
 
0.4%
0.04 43
 
0.4%
0.036 43
 
0.4%
Other values (1582) 7877
78.8%
2024-03-23T05:41:46.892694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14719
31.0%
. 8160
17.2%
1 3908
 
8.2%
2 3052
 
6.4%
3 2599
 
5.5%
4 2384
 
5.0%
5 2060
 
4.3%
6 1827
 
3.9%
7 1821
 
3.8%
8 1643
 
3.5%
Other values (9) 5281
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35616
75.1%
Other Punctuation 8160
 
17.2%
Other Letter 3678
 
7.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14719
41.3%
1 3908
 
11.0%
2 3052
 
8.6%
3 2599
 
7.3%
4 2384
 
6.7%
5 2060
 
5.8%
6 1827
 
5.1%
7 1821
 
5.1%
8 1643
 
4.6%
9 1603
 
4.5%
Other Letter
ValueCountFrequency (%)
872
23.7%
872
23.7%
611
16.6%
611
16.6%
315
 
8.6%
315
 
8.6%
41
 
1.1%
41
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 8160
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 43776
92.2%
Hangul 3678
 
7.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14719
33.6%
. 8160
18.6%
1 3908
 
8.9%
2 3052
 
7.0%
3 2599
 
5.9%
4 2384
 
5.4%
5 2060
 
4.7%
6 1827
 
4.2%
7 1821
 
4.2%
8 1643
 
3.8%
Hangul
ValueCountFrequency (%)
872
23.7%
872
23.7%
611
16.6%
611
16.6%
315
 
8.6%
315
 
8.6%
41
 
1.1%
41
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43776
92.2%
Hangul 3678
 
7.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14719
33.6%
. 8160
18.6%
1 3908
 
8.9%
2 3052
 
7.0%
3 2599
 
5.9%
4 2384
 
5.4%
5 2060
 
4.7%
6 1827
 
4.2%
7 1821
 
4.2%
8 1643
 
3.8%
Hangul
ValueCountFrequency (%)
872
23.7%
872
23.7%
611
16.6%
611
16.6%
315
 
8.6%
315
 
8.6%
41
 
1.1%
41
 
1.1%
Distinct2008
Distinct (%)20.1%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-23T05:41:48.165939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.4356436
Min length1

Characters and Unicode

Total characters44352
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

Unique1158 ?
Unique (%)11.6%

Sample

1st row교정
2nd row0.188
3rd row0.79
4th row0.275
5th row0.0912
ValueCountFrequency (%)
보수 872
 
8.7%
교정 611
 
6.1%
동불 346
 
3.5%
0.128 43
 
0.4%
전단 41
 
0.4%
0.13 39
 
0.4%
0.116 38
 
0.4%
0.127 38
 
0.4%
0.146 36
 
0.4%
0.15 34
 
0.3%
Other values (1998) 7901
79.0%
2024-03-23T05:41:51.111216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9047
20.4%
. 8124
18.3%
1 4767
10.7%
2 3442
 
7.8%
3 2794
 
6.3%
4 2478
 
5.6%
5 2256
 
5.1%
6 2025
 
4.6%
7 2002
 
4.5%
9 1853
 
4.2%
Other values (9) 5564
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32488
73.3%
Other Punctuation 8124
 
18.3%
Other Letter 3740
 
8.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9047
27.8%
1 4767
14.7%
2 3442
 
10.6%
3 2794
 
8.6%
4 2478
 
7.6%
5 2256
 
6.9%
6 2025
 
6.2%
7 2002
 
6.2%
9 1853
 
5.7%
8 1824
 
5.6%
Other Letter
ValueCountFrequency (%)
872
23.3%
872
23.3%
611
16.3%
611
16.3%
346
 
9.3%
346
 
9.3%
41
 
1.1%
41
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 8124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 40612
91.6%
Hangul 3740
 
8.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9047
22.3%
. 8124
20.0%
1 4767
11.7%
2 3442
 
8.5%
3 2794
 
6.9%
4 2478
 
6.1%
5 2256
 
5.6%
6 2025
 
5.0%
7 2002
 
4.9%
9 1853
 
4.6%
Hangul
ValueCountFrequency (%)
872
23.3%
872
23.3%
611
16.3%
611
16.3%
346
 
9.3%
346
 
9.3%
41
 
1.1%
41
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40612
91.6%
Hangul 3740
 
8.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9047
22.3%
. 8124
20.0%
1 4767
11.7%
2 3442
 
8.5%
3 2794
 
6.9%
4 2478
 
6.1%
5 2256
 
5.6%
6 2025
 
5.0%
7 2002
 
4.9%
9 1853
 
4.6%
Hangul
ValueCountFrequency (%)
872
23.3%
872
23.3%
611
16.3%
611
16.3%
346
 
9.3%
346
 
9.3%
41
 
1.1%
41
 
1.1%
Distinct4757
Distinct (%)47.6%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-23T05:41:52.341682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.4539454
Min length1

Characters and Unicode

Total characters44535
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

Unique3121 ?
Unique (%)31.2%

Sample

1st row교정
2nd row0.423
3rd row25.885
4th row1.151
5th row0.93
ValueCountFrequency (%)
보수 872
 
8.7%
교정 611
 
6.1%
동불 354
 
3.5%
전단 41
 
0.4%
0.666 10
 
0.1%
0.443 9
 
0.1%
0.587 9
 
0.1%
0.467 9
 
0.1%
0.472 9
 
0.1%
0.688 9
 
0.1%
Other values (4747) 8066
80.7%
2024-03-23T05:41:54.157424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 8116
18.2%
0 4645
10.4%
1 4530
10.2%
2 3580
8.0%
3 3255
7.3%
4 3170
 
7.1%
5 2959
 
6.6%
6 2804
 
6.3%
7 2677
 
6.0%
8 2577
 
5.8%
Other values (9) 6222
14.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32663
73.3%
Other Punctuation 8116
 
18.2%
Other Letter 3756
 
8.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4645
14.2%
1 4530
13.9%
2 3580
11.0%
3 3255
10.0%
4 3170
9.7%
5 2959
9.1%
6 2804
8.6%
7 2677
8.2%
8 2577
7.9%
9 2466
7.5%
Other Letter
ValueCountFrequency (%)
872
23.2%
872
23.2%
611
16.3%
611
16.3%
354
9.4%
354
9.4%
41
 
1.1%
41
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 8116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 40779
91.6%
Hangul 3756
 
8.4%

Most frequent character per script

Common
ValueCountFrequency (%)
. 8116
19.9%
0 4645
11.4%
1 4530
11.1%
2 3580
8.8%
3 3255
8.0%
4 3170
 
7.8%
5 2959
 
7.3%
6 2804
 
6.9%
7 2677
 
6.6%
8 2577
 
6.3%
Hangul
ValueCountFrequency (%)
872
23.2%
872
23.2%
611
16.3%
611
16.3%
354
9.4%
354
9.4%
41
 
1.1%
41
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40779
91.6%
Hangul 3756
 
8.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 8116
19.9%
0 4645
11.4%
1 4530
11.1%
2 3580
8.8%
3 3255
8.0%
4 3170
 
7.8%
5 2959
 
7.3%
6 2804
 
6.9%
7 2677
 
6.6%
8 2577
 
6.3%
Hangul
ValueCountFrequency (%)
872
23.2%
872
23.2%
611
16.3%
611
16.3%
354
9.4%
354
9.4%
41
 
1.1%
41
 
1.1%
Distinct4402
Distinct (%)44.0%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-23T05:41:55.219421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.3758376
Min length1

Characters and Unicode

Total characters43754
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

Unique2490 ?
Unique (%)24.9%

Sample

1st row교정
2nd row1.985
3rd row7.9
4th row1.389
5th row1.788
ValueCountFrequency (%)
보수 872
 
8.7%
교정 617
 
6.2%
동불 491
 
4.9%
전단 41
 
0.4%
1.223 9
 
0.1%
0.672 8
 
0.1%
1.886 8
 
0.1%
0.773 8
 
0.1%
0.399 8
 
0.1%
1.35 8
 
0.1%
Other values (4392) 7929
79.3%
2024-03-23T05:41:56.769540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7969
18.2%
1 5078
11.6%
2 3921
9.0%
0 3475
7.9%
3 3446
7.9%
4 2858
 
6.5%
5 2736
 
6.3%
6 2683
 
6.1%
7 2641
 
6.0%
8 2526
 
5.8%
Other values (9) 6421
14.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31743
72.5%
Other Punctuation 7969
 
18.2%
Other Letter 4042
 
9.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5078
16.0%
2 3921
12.4%
0 3475
10.9%
3 3446
10.9%
4 2858
9.0%
5 2736
8.6%
6 2683
8.5%
7 2641
8.3%
8 2526
8.0%
9 2379
7.5%
Other Letter
ValueCountFrequency (%)
872
21.6%
872
21.6%
617
15.3%
617
15.3%
491
12.1%
491
12.1%
41
 
1.0%
41
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 7969
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39712
90.8%
Hangul 4042
 
9.2%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7969
20.1%
1 5078
12.8%
2 3921
9.9%
0 3475
8.8%
3 3446
8.7%
4 2858
 
7.2%
5 2736
 
6.9%
6 2683
 
6.8%
7 2641
 
6.7%
8 2526
 
6.4%
Hangul
ValueCountFrequency (%)
872
21.6%
872
21.6%
617
15.3%
617
15.3%
491
12.1%
491
12.1%
41
 
1.0%
41
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39712
90.8%
Hangul 4042
 
9.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7969
20.1%
1 5078
12.8%
2 3921
9.9%
0 3475
8.8%
3 3446
8.7%
4 2858
 
7.2%
5 2736
 
6.9%
6 2683
 
6.8%
7 2641
 
6.7%
8 2526
 
6.4%
Hangul
ValueCountFrequency (%)
872
21.6%
872
21.6%
617
15.3%
617
15.3%
491
12.1%
491
12.1%
41
 
1.0%
41
 
1.0%
Distinct6748
Distinct (%)67.5%
Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-23T05:41:57.901482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.5023005
Min length2

Characters and Unicode

Total characters55012
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

Unique4967 ?
Unique (%)49.7%

Sample

1st row교정
2nd row0.6479
3rd row2.0268
4th row0.7617
5th row0.6228
ValueCountFrequency (%)
교정 607
 
6.1%
동불 271
 
2.7%
전단 92
 
0.9%
0.0014 8
 
0.1%
0.3701 8
 
0.1%
0.0012 7
 
0.1%
0.6938 6
 
0.1%
0.2225 6
 
0.1%
0.0015 5
 
0.1%
0.6716 5
 
0.1%
Other values (6738) 8983
89.8%
2024-03-23T05:41:59.453378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9557
17.4%
. 9028
16.4%
1 5342
9.7%
2 4164
7.6%
3 3903
7.1%
4 3859
7.0%
5 3686
 
6.7%
6 3525
 
6.4%
7 3503
 
6.4%
8 3330
 
6.1%
Other values (7) 5115
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44044
80.1%
Other Punctuation 9028
 
16.4%
Other Letter 1940
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9557
21.7%
1 5342
12.1%
2 4164
9.5%
3 3903
8.9%
4 3859
8.8%
5 3686
 
8.4%
6 3525
 
8.0%
7 3503
 
8.0%
8 3330
 
7.6%
9 3175
 
7.2%
Other Letter
ValueCountFrequency (%)
607
31.3%
607
31.3%
271
14.0%
271
14.0%
92
 
4.7%
92
 
4.7%
Other Punctuation
ValueCountFrequency (%)
. 9028
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53072
96.5%
Hangul 1940
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9557
18.0%
. 9028
17.0%
1 5342
10.1%
2 4164
7.8%
3 3903
7.4%
4 3859
7.3%
5 3686
 
6.9%
6 3525
 
6.6%
7 3503
 
6.6%
8 3330
 
6.3%
Hangul
ValueCountFrequency (%)
607
31.3%
607
31.3%
271
14.0%
271
14.0%
92
 
4.7%
92
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53072
96.5%
Hangul 1940
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9557
18.0%
. 9028
17.0%
1 5342
10.1%
2 4164
7.8%
3 3903
7.4%
4 3859
7.3%
5 3686
 
6.9%
6 3525
 
6.6%
7 3503
 
6.6%
8 3330
 
6.3%
Hangul
ValueCountFrequency (%)
607
31.3%
607
31.3%
271
14.0%
271
14.0%
92
 
4.7%
92
 
4.7%
Distinct8343
Distinct (%)83.4%
Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-23T05:42:00.600771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.5157031
Min length1

Characters and Unicode

Total characters55146
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 row교정
2nd row2.1774
3rd row5.7644
4th row1.8562
5th row2.098
ValueCountFrequency (%)
교정 607
 
6.1%
동불 269
 
2.7%
전단 92
 
0.9%
0 5
 
0.1%
2.3457 5
 
0.1%
4.3104 4
 
< 0.1%
2.5271 4
 
< 0.1%
3.4508 4
 
< 0.1%
3.7211 3
 
< 0.1%
2.8516 3
 
< 0.1%
Other values (8333) 9002
90.0%
2024-03-23T05:42:02.383907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9023
16.4%
2 6136
11.1%
3 5511
10.0%
1 5227
9.5%
4 4842
8.8%
5 4372
7.9%
6 4010
7.3%
7 3926
7.1%
8 3754
6.8%
9 3588
 
6.5%
Other values (7) 4757
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44187
80.1%
Other Punctuation 9023
 
16.4%
Other Letter 1936
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 6136
13.9%
3 5511
12.5%
1 5227
11.8%
4 4842
11.0%
5 4372
9.9%
6 4010
9.1%
7 3926
8.9%
8 3754
8.5%
9 3588
8.1%
0 2821
6.4%
Other Letter
ValueCountFrequency (%)
607
31.4%
607
31.4%
269
13.9%
269
13.9%
92
 
4.8%
92
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 9023
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53210
96.5%
Hangul 1936
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9023
17.0%
2 6136
11.5%
3 5511
10.4%
1 5227
9.8%
4 4842
9.1%
5 4372
8.2%
6 4010
7.5%
7 3926
7.4%
8 3754
7.1%
9 3588
 
6.7%
Hangul
ValueCountFrequency (%)
607
31.4%
607
31.4%
269
13.9%
269
13.9%
92
 
4.8%
92
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53210
96.5%
Hangul 1936
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9023
17.0%
2 6136
11.5%
3 5511
10.4%
1 5227
9.8%
4 4842
9.1%
5 4372
8.2%
6 4010
7.5%
7 3926
7.4%
8 3754
7.1%
9 3588
 
6.7%
Hangul
ValueCountFrequency (%)
607
31.4%
607
31.4%
269
13.9%
269
13.9%
92
 
4.8%
92
 
4.8%
Distinct8397
Distinct (%)84.0%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-23T05:42:03.542800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.5135541
Min length1

Characters and Unicode

Total characters55119
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

Unique7796 ?
Unique (%)78.0%

Sample

1st row교정
2nd row2.8254
3rd row7.7912
4th row2.618
5th row2.7208
ValueCountFrequency (%)
교정 607
 
6.1%
동불 268
 
2.7%
전단 92
 
0.9%
3.7223 4
 
< 0.1%
3.0902 4
 
< 0.1%
0 4
 
< 0.1%
2.6941 4
 
< 0.1%
3.2515 3
 
< 0.1%
4.2292 3
 
< 0.1%
1.9901 3
 
< 0.1%
Other values (8387) 9005
90.1%
2024-03-23T05:42:05.018163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9023
16.4%
2 5788
10.5%
3 5708
10.4%
4 4948
9.0%
1 4583
8.3%
5 4455
8.1%
6 4244
7.7%
7 4034
7.3%
8 3865
7.0%
9 3827
6.9%
Other values (7) 4644
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44162
80.1%
Other Punctuation 9023
 
16.4%
Other Letter 1934
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 5788
13.1%
3 5708
12.9%
4 4948
11.2%
1 4583
10.4%
5 4455
10.1%
6 4244
9.6%
7 4034
9.1%
8 3865
8.8%
9 3827
8.7%
0 2710
6.1%
Other Letter
ValueCountFrequency (%)
607
31.4%
607
31.4%
268
13.9%
268
13.9%
92
 
4.8%
92
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 9023
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53185
96.5%
Hangul 1934
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9023
17.0%
2 5788
10.9%
3 5708
10.7%
4 4948
9.3%
1 4583
8.6%
5 4455
8.4%
6 4244
8.0%
7 4034
7.6%
8 3865
7.3%
9 3827
7.2%
Hangul
ValueCountFrequency (%)
607
31.4%
607
31.4%
268
13.9%
268
13.9%
92
 
4.8%
92
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53185
96.5%
Hangul 1934
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9023
17.0%
2 5788
10.9%
3 5708
10.7%
4 4948
9.3%
1 4583
8.6%
5 4455
8.4%
6 4244
8.0%
7 4034
7.6%
8 3865
7.3%
9 3827
7.2%
Hangul
ValueCountFrequency (%)
607
31.4%
607
31.4%
268
13.9%
268
13.9%
92
 
4.8%
92
 
4.8%

Missing values

2024-03-23T05:41:28.904294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T05:41:29.556998image/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.
2024-03-23T05:41:30.189317image/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
240782211052023-12-01 11:00교정교정교정교정교정교정교정교정교정교정교정
172702211212023-08-28 21:000.090.5820.0930.02610.03450.1880.4231.9850.64792.17742.8254
49922211052023-03-11 09:000.12410.8930.1390.0220.1290.7925.8857.92.02685.76447.7912
33362211052023-02-16 09:000.1330.8650.0820.0170.1150.2751.1511.3890.76171.85622.618
125732211052023-06-24 16:000.086동불0.04920.02220.0610.09120.931.7880.62282.0982.7208
92892211022023-05-10 01:000.12372.02140.03870.03450.1060.62064.17022.43181.345111.874113.2193
223172211052023-11-07 00:000.2140.1840.00860.03970.03960.3540.5820.8220.15711.80391.961
18202211212023-01-26 07:000.0350.5270.0650.00780.0460.3821.2460.3910.53514.89135.4264
42182211052023-02-28 15:00교정교정교정교정교정교정교정교정교정교정교정
114932211052023-06-09 16:000.1162.1030.0240.01640.0690.1742.1254.3541.33244.9356.2674
대기질지점코드측정날짜나트륨이온암모니아이온칼륨이온마그네슘이온칼슘이온염소이온질산이온황산이온원소탄소유기탄소총탄소
75822211022023-04-16 08:000.2411.2320.0990.1360.330.6692.8371.4030.19253.82944.0219
188982211022023-09-20 12:000.04980.78890.00070.06970.05090.684.8222.745동불동불동불
80852211052023-04-23 08:00동불동불동불동불동불동불동불동불0.29551.99562.2911
178832211052023-09-06 10:00교정교정교정교정교정교정교정교정교정교정교정
27712211212023-02-08 12:000.23779.02160.44580.16020.13511.286920.24136.56352.32286.06258.3853
204952211212023-10-12 16:00보수보수보수보수보수보수보수보수0.57962.94283.5225
54452211052023-03-17 16:00교정교정교정교정교정교정교정교정교정교정교정
90132211022023-05-06 05:000.14841.07060.06630.02860.09620.34830.30150.81780.11872.00222.1209
202682211052023-10-09 13:000.0430.30460.01790.00750.05270.0860.2060.6530.85322.19163.0449
99012211022023-05-18 13:000.5113.78790.20640.06810.43620.72554.52865.94711.00644.95485.9611