Overview

Dataset statistics

Number of variables6
Number of observations400
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.1 KiB
Average record size in memory51.3 B

Variable types

Numeric3
Categorical2
Text1

Dataset

DescriptionSample
Author코난테크놀로지
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=TPOLANDMARK

Alerts

"채널값" has constant value ""Constant
"해당일자" has constant value ""Constant
"기본키값" is highly overall correlated with "차례값" and 1 other fieldsHigh correlation
"차례값" is highly overall correlated with "기본키값" and 1 other fieldsHigh correlation
"건수값" is highly overall correlated with "기본키값" and 1 other fieldsHigh correlation
"기본키값" has unique valuesUnique
"차례값" has unique valuesUnique
"이슈어값" has unique valuesUnique

Reproduction

Analysis started2023-12-10 06:39:03.662038
Analysis finished2023-12-10 06:39:06.011951
Duration2.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

"기본키값"
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct400
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12674.5
Minimum12475
Maximum12874
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-10T15:39:06.127848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12475
5-th percentile12494.95
Q112574.75
median12674.5
Q312774.25
95-th percentile12854.05
Maximum12874
Range399
Interquartile range (IQR)199.5

Descriptive statistics

Standard deviation115.6143
Coefficient of variation (CV)0.0091218037
Kurtosis-1.2
Mean12674.5
Median Absolute Deviation (MAD)100
Skewness0
Sum5069800
Variance13366.667
MonotonicityStrictly increasing
2023-12-10T15:39:06.369070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12475 1
 
0.2%
12739 1
 
0.2%
12749 1
 
0.2%
12748 1
 
0.2%
12747 1
 
0.2%
12746 1
 
0.2%
12745 1
 
0.2%
12744 1
 
0.2%
12743 1
 
0.2%
12742 1
 
0.2%
Other values (390) 390
97.5%
ValueCountFrequency (%)
12475 1
0.2%
12476 1
0.2%
12477 1
0.2%
12478 1
0.2%
12479 1
0.2%
12480 1
0.2%
12481 1
0.2%
12482 1
0.2%
12483 1
0.2%
12484 1
0.2%
ValueCountFrequency (%)
12874 1
0.2%
12873 1
0.2%
12872 1
0.2%
12871 1
0.2%
12870 1
0.2%
12869 1
0.2%
12868 1
0.2%
12867 1
0.2%
12866 1
0.2%
12865 1
0.2%

"채널값"
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
"블로그"
400 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row"블로그"
2nd row"블로그"
3rd row"블로그"
4th row"블로그"
5th row"블로그"

Common Values

ValueCountFrequency (%)
"블로그" 400
100.0%

Length

2023-12-10T15:39:06.591511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:39:06.765965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
블로그 400
100.0%

"해당일자"
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2020-05-01
400 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-05-01
2nd row2020-05-01
3rd row2020-05-01
4th row2020-05-01
5th row2020-05-01

Common Values

ValueCountFrequency (%)
2020-05-01 400
100.0%

Length

2023-12-10T15:39:06.956901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:39:07.231066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-05-01 400
100.0%

"차례값"
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct400
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean200.5
Minimum1
Maximum400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-10T15:39:07.451084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile20.95
Q1100.75
median200.5
Q3300.25
95-th percentile380.05
Maximum400
Range399
Interquartile range (IQR)199.5

Descriptive statistics

Standard deviation115.6143
Coefficient of variation (CV)0.57662993
Kurtosis-1.2
Mean200.5
Median Absolute Deviation (MAD)100
Skewness0
Sum80200
Variance13366.667
MonotonicityStrictly increasing
2023-12-10T15:39:07.709189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
265 1
 
0.2%
275 1
 
0.2%
274 1
 
0.2%
273 1
 
0.2%
272 1
 
0.2%
271 1
 
0.2%
270 1
 
0.2%
269 1
 
0.2%
268 1
 
0.2%
Other values (390) 390
97.5%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
400 1
0.2%
399 1
0.2%
398 1
0.2%
397 1
0.2%
396 1
0.2%
395 1
0.2%
394 1
0.2%
393 1
0.2%
392 1
0.2%
391 1
0.2%

"이슈어값"
Text

UNIQUE 

Distinct400
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-12-10T15:39:08.212056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length6.1775
Min length4

Characters and Unicode

Total characters2471
Distinct characters272
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique400 ?
Unique (%)100.0%

Sample

1st row"홍익대학교"
2nd row"서울대학교"
3rd row"강남역"
4th row"건국대학교"
5th row"제주국제공항"
ValueCountFrequency (%)
홍익대학교 1
 
0.2%
주왕산 1
 
0.2%
상인역 1
 
0.2%
화정역 1
 
0.2%
을지대학교 1
 
0.2%
울산국내공항 1
 
0.2%
왕십리역 1
 
0.2%
영통역 1
 
0.2%
약수역 1
 
0.2%
회기역 1
 
0.2%
Other values (390) 390
97.5%
2023-12-10T15:39:08.922524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 800
32.4%
역 198
 
8.0%
대 121
 
4.9%
교 98
 
4.0%
학 91
 
3.7%
산 57
 
2.3%
수 26
 
1.1%
원 24
 
1.0%
동 22
 
0.9%
국 22
 
0.9%
Other values (262) 1012
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1665
67.4%
Other Punctuation 801
32.4%
Decimal Number 3
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 198
 
11.9%
대 121
 
7.3%
교 98
 
5.9%
학 91
 
5.5%
산 57
 
3.4%
수 26
 
1.6%
원 24
 
1.4%
동 22
 
1.3%
국 22
 
1.3%
한 21
 
1.3%
Other values (256) 985
59.2%
Other Punctuation
ValueCountFrequency (%)
" 800
99.9%
· 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
3 2
66.7%
6 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1665
67.4%
Common 806
32.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 198
 
11.9%
대 121
 
7.3%
교 98
 
5.9%
학 91
 
5.5%
산 57
 
3.4%
수 26
 
1.6%
원 24
 
1.4%
동 22
 
1.3%
국 22
 
1.3%
한 21
 
1.3%
Other values (256) 985
59.2%
Common
ValueCountFrequency (%)
" 800
99.3%
3 2
 
0.2%
· 1
 
0.1%
) 1
 
0.1%
( 1
 
0.1%
6 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1665
67.4%
ASCII 805
32.6%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 800
99.4%
3 2
 
0.2%
) 1
 
0.1%
( 1
 
0.1%
6 1
 
0.1%
Hangul
ValueCountFrequency (%)
역 198
 
11.9%
대 121
 
7.3%
교 98
 
5.9%
학 91
 
5.5%
산 57
 
3.4%
수 26
 
1.6%
원 24
 
1.4%
동 22
 
1.3%
국 22
 
1.3%
한 21
 
1.3%
Other values (256) 985
59.2%
None
ValueCountFrequency (%)
· 1
100.0%

"건수값"
Real number (ℝ)

HIGH CORRELATION 

Distinct137
Distinct (%)34.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean106.67
Minimum40
Maximum1674
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-10T15:39:09.182008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile41
Q148.75
median66
Q3108
95-th percentile266.05
Maximum1674
Range1634
Interquartile range (IQR)59.25

Descriptive statistics

Standard deviation135.45411
Coefficient of variation (CV)1.2698426
Kurtosis57.489867
Mean106.67
Median Absolute Deviation (MAD)22
Skewness6.403856
Sum42668
Variance18347.816
MonotonicityDecreasing
2023-12-10T15:39:09.416301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42 18
 
4.5%
43 13
 
3.2%
52 12
 
3.0%
41 12
 
3.0%
40 11
 
2.8%
44 10
 
2.5%
45 10
 
2.5%
47 10
 
2.5%
48 10
 
2.5%
56 9
 
2.2%
Other values (127) 285
71.2%
ValueCountFrequency (%)
40 11
2.8%
41 12
3.0%
42 18
4.5%
43 13
3.2%
44 10
2.5%
45 10
2.5%
46 6
 
1.5%
47 10
2.5%
48 10
2.5%
49 6
 
1.5%
ValueCountFrequency (%)
1674 1
0.2%
1104 1
0.2%
1015 1
0.2%
601 1
0.2%
594 1
0.2%
571 1
0.2%
517 1
0.2%
511 1
0.2%
505 1
0.2%
452 1
0.2%

Interactions

2023-12-10T15:39:05.067478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:39:04.044835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:39:04.575956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:39:05.234346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:39:04.218425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:39:04.730507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:39:05.408628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:39:04.377561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:39:04.897885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:39:09.566644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
"기본키값""차례값""건수값"
"기본키값"1.0001.0000.640
"차례값"1.0001.0000.609
"건수값"0.6400.6091.000
2023-12-10T15:39:09.733690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
"기본키값""차례값""건수값"
"기본키값"1.0001.000-1.000
"차례값"1.0001.000-1.000
"건수값"-1.000-1.0001.000

Missing values

2023-12-10T15:39:05.762493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:39:05.949862image/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

"기본키값""채널값""해당일자""차례값""이슈어값""건수값"
012475"블로그"2020-05-011"홍익대학교"1674
112476"블로그"2020-05-012"서울대학교"1104
212477"블로그"2020-05-013"강남역"1015
312478"블로그"2020-05-014"건국대학교"601
412479"블로그"2020-05-015"제주국제공항"594
512480"블로그"2020-05-016"인천국제공항"571
612481"블로그"2020-05-017"한라산"517
712482"블로그"2020-05-018"남산"511
812483"블로그"2020-05-019"지리산"505
912484"블로그"2020-05-0110"광화문"452
"기본키값""채널값""해당일자""차례값""이슈어값""건수값"
39012865"블로그"2020-05-01391"등촌역"40
39112866"블로그"2020-05-01392"대구한의대학교"40
39212867"블로그"2020-05-01393"연산역"40
39312868"블로그"2020-05-01394"백운역"40
39412869"블로그"2020-05-01395"상봉역"40
39512870"블로그"2020-05-01396"창동역"40
39612871"블로그"2020-05-01397"석계역"40
39712872"블로그"2020-05-01398"평택·당진항"40
39812873"블로그"2020-05-01399"회룡역"40
39912874"블로그"2020-05-01400"경남대학교"40