Overview

Dataset statistics

Number of variables4
Number of observations98
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory35.3 B

Variable types

Categorical2
Text2

Dataset

DescriptionSample
Author한국인터넷진흥원
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=KIS0000038

Alerts

2021 has constant value ""Constant
1 has constant value ""Constant
00064968D14D3556AF90E3257D8F3D5C7EE5FBFFE6B1326C916A42B13D9ECD25 has unique valuesUnique
00064968D14D3556AF90E3257D8F3D5C7EE5FBFFE6B1326C916A42B13D9ECD25.vir has unique valuesUnique

Reproduction

Analysis started2023-12-10 06:41:30.716866
Analysis finished2023-12-10 06:41:31.226400
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

2021
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
2021
98 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 98
100.0%

Length

2023-12-10T15:41:31.352491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:41:31.497836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 98
100.0%

00064968D14D3556AF90E3257D8F3D5C7EE5FBFFE6B1326C916A42B13D9ECD25
Text

UNIQUE 

Distinct98
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
2023-12-10T15:41:31.877354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length64
Mean length64
Min length64

Characters and Unicode

Total characters6272
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)100.0%

Sample

1st row0009C2CD7B3E5FA9C55404B6629AC348E13F2AFBA54199EF2B59758EFC6E12A9
2nd row00174F7CB12FDEE2077B41D17823B6204AB0216B588358083415D977EE02D1D9
3rd row001B9442703F9B213F3CE22300C342C7AC06F890249DD7AEEFF150FF40674BCB
4th row001FA5FAD8A848482123E89A527CD672FFCBACD4CF558A65CCEF2AB496F6BC36
5th row001FE676C3C2B637D2356E96BBECA39551449299C92B0472BF5C9B5C5C9EF0CD
ValueCountFrequency (%)
0009c2cd7b3e5fa9c55404b6629ac348e13f2afba54199ef2b59758efc6e12a9 1
 
1.0%
0152e8bcc49c28fe53da9d0b2ab3793e6eb7d98d4737ae3d9671a27627249ab4 1
 
1.0%
0145f338536bb0cb4229033d7ad46cb4772e1faf85fb76c8114234711dae5343 1
 
1.0%
013b7bb59c93735300311e964c95bd56327d0e545dccba3b8772f3c55464b68e 1
 
1.0%
013b0d2ff425f94e346d0b7546d279d4c284deee6be608ada2263d3043b7f788 1
 
1.0%
01375d6c540112768cb5ca3099ffd9a6b0c7336e3eca632c42525a24cfbb22d0 1
 
1.0%
0131589b948ef7455184731d5440d8abdf19e56369c4959ce660749cddc01222 1
 
1.0%
013074667f4ccbec99a4063dc11a0d88a4874dce5cec78ddca98d77fe7e98e39 1
 
1.0%
012dc979bc15fc7ba5196af769e18e8b1cb9d0bc8d7ecae85e40b181022f6884 1
 
1.0%
012cbe99ef0244e81e9926bb0fa5bbffdceab816043472fc2df99bf97657b771 1
 
1.0%
Other values (88) 88
89.8%
2023-12-10T15:41:32.499937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 504
 
8.0%
1 443
 
7.1%
4 413
 
6.6%
9 410
 
6.5%
7 408
 
6.5%
C 398
 
6.3%
D 395
 
6.3%
6 388
 
6.2%
5 377
 
6.0%
A 376
 
6.0%
Other values (6) 2160
34.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4035
64.3%
Uppercase Letter 2237
35.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 504
12.5%
1 443
11.0%
4 413
10.2%
9 410
10.2%
7 408
10.1%
6 388
9.6%
5 377
9.3%
2 373
9.2%
8 368
9.1%
3 351
8.7%
Uppercase Letter
ValueCountFrequency (%)
C 398
17.8%
D 395
17.7%
A 376
16.8%
B 374
16.7%
F 351
15.7%
E 343
15.3%

Most occurring scripts

ValueCountFrequency (%)
Common 4035
64.3%
Latin 2237
35.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 504
12.5%
1 443
11.0%
4 413
10.2%
9 410
10.2%
7 408
10.1%
6 388
9.6%
5 377
9.3%
2 373
9.2%
8 368
9.1%
3 351
8.7%
Latin
ValueCountFrequency (%)
C 398
17.8%
D 395
17.7%
A 376
16.8%
B 374
16.7%
F 351
15.7%
E 343
15.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6272
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 504
 
8.0%
1 443
 
7.1%
4 413
 
6.6%
9 410
 
6.5%
7 408
 
6.5%
C 398
 
6.3%
D 395
 
6.3%
6 388
 
6.2%
5 377
 
6.0%
A 376
 
6.0%
Other values (6) 2160
34.4%

00064968D14D3556AF90E3257D8F3D5C7EE5FBFFE6B1326C916A42B13D9ECD25.vir
Text

UNIQUE 

Distinct98
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
2023-12-10T15:41:32.908812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length68
Mean length68
Min length68

Characters and Unicode

Total characters6664
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)100.0%

Sample

1st row0009C2CD7B3E5FA9C55404B6629AC348E13F2AFBA54199EF2B59758EFC6E12A9.vir
2nd row00174F7CB12FDEE2077B41D17823B6204AB0216B588358083415D977EE02D1D9.vir
3rd row001B9442703F9B213F3CE22300C342C7AC06F890249DD7AEEFF150FF40674BCB.vir
4th row001FA5FAD8A848482123E89A527CD672FFCBACD4CF558A65CCEF2AB496F6BC36.vir
5th row001FE676C3C2B637D2356E96BBECA39551449299C92B0472BF5C9B5C5C9EF0CD.vir
ValueCountFrequency (%)
0009c2cd7b3e5fa9c55404b6629ac348e13f2afba54199ef2b59758efc6e12a9.vir 1
 
1.0%
0152e8bcc49c28fe53da9d0b2ab3793e6eb7d98d4737ae3d9671a27627249ab4.vir 1
 
1.0%
0145f338536bb0cb4229033d7ad46cb4772e1faf85fb76c8114234711dae5343.vir 1
 
1.0%
013b7bb59c93735300311e964c95bd56327d0e545dccba3b8772f3c55464b68e.vir 1
 
1.0%
013b0d2ff425f94e346d0b7546d279d4c284deee6be608ada2263d3043b7f788.vir 1
 
1.0%
01375d6c540112768cb5ca3099ffd9a6b0c7336e3eca632c42525a24cfbb22d0.vir 1
 
1.0%
0131589b948ef7455184731d5440d8abdf19e56369c4959ce660749cddc01222.vir 1
 
1.0%
013074667f4ccbec99a4063dc11a0d88a4874dce5cec78ddca98d77fe7e98e39.vir 1
 
1.0%
012dc979bc15fc7ba5196af769e18e8b1cb9d0bc8d7ecae85e40b181022f6884.vir 1
 
1.0%
012cbe99ef0244e81e9926bb0fa5bbffdceab816043472fc2df99bf97657b771.vir 1
 
1.0%
Other values (88) 88
89.8%
2023-12-10T15:41:33.515723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 504
 
7.6%
1 443
 
6.6%
4 413
 
6.2%
9 410
 
6.2%
7 408
 
6.1%
C 398
 
6.0%
D 395
 
5.9%
6 388
 
5.8%
5 377
 
5.7%
A 376
 
5.6%
Other values (10) 2552
38.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4035
60.5%
Uppercase Letter 2237
33.6%
Lowercase Letter 294
 
4.4%
Other Punctuation 98
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 504
12.5%
1 443
11.0%
4 413
10.2%
9 410
10.2%
7 408
10.1%
6 388
9.6%
5 377
9.3%
2 373
9.2%
8 368
9.1%
3 351
8.7%
Uppercase Letter
ValueCountFrequency (%)
C 398
17.8%
D 395
17.7%
A 376
16.8%
B 374
16.7%
F 351
15.7%
E 343
15.3%
Lowercase Letter
ValueCountFrequency (%)
v 98
33.3%
i 98
33.3%
r 98
33.3%
Other Punctuation
ValueCountFrequency (%)
. 98
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4133
62.0%
Latin 2531
38.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 504
12.2%
1 443
10.7%
4 413
10.0%
9 410
9.9%
7 408
9.9%
6 388
9.4%
5 377
9.1%
2 373
9.0%
8 368
8.9%
3 351
8.5%
Latin
ValueCountFrequency (%)
C 398
15.7%
D 395
15.6%
A 376
14.9%
B 374
14.8%
F 351
13.9%
E 343
13.6%
v 98
 
3.9%
i 98
 
3.9%
r 98
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6664
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 504
 
7.6%
1 443
 
6.6%
4 413
 
6.2%
9 410
 
6.2%
7 408
 
6.1%
C 398
 
6.0%
D 395
 
5.9%
6 388
 
5.8%
5 377
 
5.7%
A 376
 
5.6%
Other values (10) 2552
38.3%

1
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
1
98 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 98
100.0%

Length

2023-12-10T15:41:33.731143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:41:33.868003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 98
100.0%

Correlations

2023-12-10T15:41:33.923838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
00064968D14D3556AF90E3257D8F3D5C7EE5FBFFE6B1326C916A42B13D9ECD2500064968D14D3556AF90E3257D8F3D5C7EE5FBFFE6B1326C916A42B13D9ECD25.vir
00064968D14D3556AF90E3257D8F3D5C7EE5FBFFE6B1326C916A42B13D9ECD251.0001.000
00064968D14D3556AF90E3257D8F3D5C7EE5FBFFE6B1326C916A42B13D9ECD25.vir1.0001.000

Missing values

2023-12-10T15:41:30.997941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:41:31.161119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

202100064968D14D3556AF90E3257D8F3D5C7EE5FBFFE6B1326C916A42B13D9ECD2500064968D14D3556AF90E3257D8F3D5C7EE5FBFFE6B1326C916A42B13D9ECD25.vir1
020210009C2CD7B3E5FA9C55404B6629AC348E13F2AFBA54199EF2B59758EFC6E12A90009C2CD7B3E5FA9C55404B6629AC348E13F2AFBA54199EF2B59758EFC6E12A9.vir1
1202100174F7CB12FDEE2077B41D17823B6204AB0216B588358083415D977EE02D1D900174F7CB12FDEE2077B41D17823B6204AB0216B588358083415D977EE02D1D9.vir1
22021001B9442703F9B213F3CE22300C342C7AC06F890249DD7AEEFF150FF40674BCB001B9442703F9B213F3CE22300C342C7AC06F890249DD7AEEFF150FF40674BCB.vir1
32021001FA5FAD8A848482123E89A527CD672FFCBACD4CF558A65CCEF2AB496F6BC36001FA5FAD8A848482123E89A527CD672FFCBACD4CF558A65CCEF2AB496F6BC36.vir1
42021001FE676C3C2B637D2356E96BBECA39551449299C92B0472BF5C9B5C5C9EF0CD001FE676C3C2B637D2356E96BBECA39551449299C92B0472BF5C9B5C5C9EF0CD.vir1
52021002021BEB887648455BC17E08DBC9769C23B479D1E00582296963C14E6AD66CC002021BEB887648455BC17E08DBC9769C23B479D1E00582296963C14E6AD66CC.vir1
62021002A8130DCC31A2C5211D5793705A5BEB01DAC4F469C3E775158C319B804AB4A002A8130DCC31A2C5211D5793705A5BEB01DAC4F469C3E775158C319B804AB4A.vir1
72021002DA5B2F60088C49DAC1263C40E1D991E17FE1407360D7E32B3F6C7E61C072D002DA5B2F60088C49DAC1263C40E1D991E17FE1407360D7E32B3F6C7E61C072D.vir1
82021002EC5B4C801DA52442D50E6E602A2640971FEE1F7E3F2CF66FEF7CFAE6CC24A002EC5B4C801DA52442D50E6E602A2640971FEE1F7E3F2CF66FEF7CFAE6CC24A.vir1
9202100310856002D11F7C19EFD921019C8312DB24E4A6203AA4106EFBCB4C501809500310856002D11F7C19EFD921019C8312DB24E4A6203AA4106EFBCB4C5018095.vir1
202100064968D14D3556AF90E3257D8F3D5C7EE5FBFFE6B1326C916A42B13D9ECD2500064968D14D3556AF90E3257D8F3D5C7EE5FBFFE6B1326C916A42B13D9ECD25.vir1
88202101955D7AEAA49C9923CAA4B4549D10A7029A8F9B3FDC2FD3E3E5FB0253CAFF6A01955D7AEAA49C9923CAA4B4549D10A7029A8F9B3FDC2FD3E3E5FB0253CAFF6A.vir1
892021019A37887CCAC36ABEA0819926A3CD0C17131749AA5AD501305BBFD2567EBC24019A37887CCAC36ABEA0819926A3CD0C17131749AA5AD501305BBFD2567EBC24.vir1
902021019BCD17D82FEFD3BD369C50213F9C3B2AA9671F8D8868D0A1820E67D117D883019BCD17D82FEFD3BD369C50213F9C3B2AA9671F8D8868D0A1820E67D117D883.vir1
912021019DE89BC968E3C4FEC15147BC975CC57AECD71A7DBCE75AD039F161259425B8019DE89BC968E3C4FEC15147BC975CC57AECD71A7DBCE75AD039F161259425B8.vir1
92202101ADC9B1894093E4E1C56A5FBCBDA298F32A01547D042F957CCE5E69C7B139EE01ADC9B1894093E4E1C56A5FBCBDA298F32A01547D042F957CCE5E69C7B139EE.vir1
93202101AE00C7D63158021088E70F1CD02D6CD654E5461365662A5CBB48E35936025A01AE00C7D63158021088E70F1CD02D6CD654E5461365662A5CBB48E35936025A.vir1
94202101AE27CBA813C9C01B349AC474070FF3CB69D23117A964B950B7056F68A7A1CA01AE27CBA813C9C01B349AC474070FF3CB69D23117A964B950B7056F68A7A1CA.vir1
95202101B09506F865E53300CEE297DB9D1424A94247CE6ACF9E065FE402C4516C1DD601B09506F865E53300CEE297DB9D1424A94247CE6ACF9E065FE402C4516C1DD6.vir1
96202101B1B42AC4C26A941F22B5A580D8172AED37650812071F29943F1A52E3CB225C01B1B42AC4C26A941F22B5A580D8172AED37650812071F29943F1A52E3CB225C.vir1
97202101B2CFF4A3B853028736FE464DBD5C491B7C2046D167F0EBDFA7F816E90642CB01B2CFF4A3B853028736FE464DBD5C491B7C2046D167F0EBDFA7F816E90642CB.vir1