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
Categorical1
DateTime1
Text1

Dataset

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

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 06:16:16.403603
Analysis finished2023-12-10 06:16:18.537404
Duration2.13 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%
Mean14707.5
Minimum14508
Maximum14907
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-10T15:16:18.658040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14508
5-th percentile14527.95
Q114607.75
median14707.5
Q314807.25
95-th percentile14887.05
Maximum14907
Range399
Interquartile range (IQR)199.5

Descriptive statistics

Standard deviation115.6143
Coefficient of variation (CV)0.0078609078
Kurtosis-1.2
Mean14707.5
Median Absolute Deviation (MAD)100
Skewness0
Sum5883000
Variance13366.667
MonotonicityStrictly increasing
2023-12-10T15:16:18.859170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14508 1
 
0.2%
14772 1
 
0.2%
14782 1
 
0.2%
14781 1
 
0.2%
14780 1
 
0.2%
14779 1
 
0.2%
14778 1
 
0.2%
14777 1
 
0.2%
14776 1
 
0.2%
14775 1
 
0.2%
Other values (390) 390
97.5%
ValueCountFrequency (%)
14508 1
0.2%
14509 1
0.2%
14510 1
0.2%
14511 1
0.2%
14512 1
0.2%
14513 1
0.2%
14514 1
0.2%
14515 1
0.2%
14516 1
0.2%
14517 1
0.2%
ValueCountFrequency (%)
14907 1
0.2%
14906 1
0.2%
14905 1
0.2%
14904 1
0.2%
14903 1
0.2%
14902 1
0.2%
14901 1
0.2%
14900 1
0.2%
14899 1
0.2%
14898 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

2023-12-10T15:16:19.094170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:16:19.248694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
블로그 400
100.0%

"해당일자"
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
Minimum2020-05-01 00:00:00
Maximum2020-05-01 00:00:00
2023-12-10T15:16:19.372413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:19.516630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

"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
2023-12-10T15:16:19.698267image/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
2023-12-10T15:16:19.934760image/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
2023-12-10T15:16:20.451666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length5.6375
Min length4

Characters and Unicode

Total characters2255
Distinct characters397
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
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"쿠팡"
2nd row"지방시"
3rd row"카카오"
4th row"푸마"
5th row"퓨마"
ValueCountFrequency (%)
쿠팡 1
 
0.2%
다시다 1
 
0.2%
뉴코아 1
 
0.2%
커피빈 1
 
0.2%
넥서스 1
 
0.2%
롯데호텔 1
 
0.2%
로젠택배 1
 
0.2%
불스원 1
 
0.2%
바디프랜드 1
 
0.2%
녹십자 1
 
0.2%
Other values (390) 390
97.5%
2023-12-10T15:16:21.143542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 800
35.5%
스 85
 
3.8%
이 48
 
2.1%
리 38
 
1.7%
아 26
 
1.2%
라 23
 
1.0%
로 22
 
1.0%
레 20
 
0.9%
트 18
 
0.8%
카 18
 
0.8%
Other values (387) 1157
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1359
60.3%
Other Punctuation 801
35.5%
Lowercase Letter 86
 
3.8%
Decimal Number 9
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 85
 
6.3%
이 48
 
3.5%
리 38
 
2.8%
아 26
 
1.9%
라 23
 
1.7%
로 22
 
1.6%
레 20
 
1.5%
트 18
 
1.3%
카 18
 
1.3%
오 17
 
1.3%
Other values (359) 1044
76.8%
Lowercase Letter
ValueCountFrequency (%)
k 10
11.6%
g 9
10.5%
b 8
 
9.3%
c 7
 
8.1%
e 7
 
8.1%
l 6
 
7.0%
s 6
 
7.0%
m 5
 
5.8%
h 4
 
4.7%
t 4
 
4.7%
Other values (12) 20
23.3%
Decimal Number
ValueCountFrequency (%)
2 4
44.4%
1 2
22.2%
4 2
22.2%
5 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
" 800
99.9%
& 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1359
60.3%
Common 810
35.9%
Latin 86
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 85
 
6.3%
이 48
 
3.5%
리 38
 
2.8%
아 26
 
1.9%
라 23
 
1.7%
로 22
 
1.6%
레 20
 
1.5%
트 18
 
1.3%
카 18
 
1.3%
오 17
 
1.3%
Other values (359) 1044
76.8%
Latin
ValueCountFrequency (%)
k 10
11.6%
g 9
10.5%
b 8
 
9.3%
c 7
 
8.1%
e 7
 
8.1%
l 6
 
7.0%
s 6
 
7.0%
m 5
 
5.8%
h 4
 
4.7%
t 4
 
4.7%
Other values (12) 20
23.3%
Common
ValueCountFrequency (%)
" 800
98.8%
2 4
 
0.5%
1 2
 
0.2%
4 2
 
0.2%
& 1
 
0.1%
5 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1359
60.3%
ASCII 896
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 800
89.3%
k 10
 
1.1%
g 9
 
1.0%
b 8
 
0.9%
c 7
 
0.8%
e 7
 
0.8%
l 6
 
0.7%
s 6
 
0.7%
m 5
 
0.6%
h 4
 
0.4%
Other values (18) 34
 
3.8%
Hangul
ValueCountFrequency (%)
스 85
 
6.3%
이 48
 
3.5%
리 38
 
2.8%
아 26
 
1.9%
라 23
 
1.7%
로 22
 
1.6%
레 20
 
1.5%
트 18
 
1.3%
카 18
 
1.3%
오 17
 
1.3%
Other values (359) 1044
76.8%

"건수값"
Real number (ℝ)

HIGH CORRELATION 

Distinct258
Distinct (%)64.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean666.5975
Minimum49
Maximum51100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-10T15:16:21.664222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum49
5-th percentile53
Q179
median149.5
Q3364.5
95-th percentile2188
Maximum51100
Range51051
Interquartile range (IQR)285.5

Descriptive statistics

Standard deviation2941.1778
Coefficient of variation (CV)4.4122245
Kurtosis221.69218
Mean666.5975
Median Absolute Deviation (MAD)86.5
Skewness13.684745
Sum266639
Variance8650526.8
MonotonicityDecreasing
2023-12-10T15:16:21.871959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49 8
 
2.0%
94 7
 
1.8%
78 6
 
1.5%
66 6
 
1.5%
71 5
 
1.2%
70 5
 
1.2%
133 5
 
1.2%
89 4
 
1.0%
62 4
 
1.0%
77 4
 
1.0%
Other values (248) 346
86.5%
ValueCountFrequency (%)
49 8
2.0%
50 2
 
0.5%
51 4
1.0%
52 4
1.0%
53 4
1.0%
54 4
1.0%
55 3
 
0.8%
56 4
1.0%
57 2
 
0.5%
58 4
1.0%
ValueCountFrequency (%)
51100 1
0.2%
16559 1
0.2%
15636 1
0.2%
12546 1
0.2%
8008 1
0.2%
7739 1
0.2%
3647 1
0.2%
3394 1
0.2%
3381 1
0.2%
3350 1
0.2%

Interactions

2023-12-10T15:16:17.825693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:16.798995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:17.344334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:17.975605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:16.965335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:17.516864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:18.121686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:17.174549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:17.679029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:16:21.993696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
"기본키값""차례값""건수값"
"기본키값"1.0001.0000.215
"차례값"1.0001.0000.257
"건수값"0.2150.2571.000
2023-12-10T15:16:22.125039image/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

2023-12-10T15:16:18.299878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:16:18.478163image/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"
014508"블로그"2020-05-011"쿠팡"51100
114509"블로그"2020-05-012"지방시"16559
214510"블로그"2020-05-013"카카오"15636
314511"블로그"2020-05-014"푸마"12546
414512"블로그"2020-05-015"퓨마"8008
514513"블로그"2020-05-016"엘르"7739
614514"블로그"2020-05-017"아이폰"3647
714515"블로그"2020-05-018"까르띠에"3394
814516"블로그"2020-05-019"펩시콜라"3381
914517"블로그"2020-05-0110"애플"3350
"기본키값""채널값""해당일자""차례값""이슈어값""건수값"
39014898"블로그"2020-05-01391"일룸"50
39114899"블로그"2020-05-01392"레모나"50
39214900"블로그"2020-05-01393"일동후디스"49
39314901"블로그"2020-05-01394"tg삼보"49
39414902"블로그"2020-05-01395"에스티로더"49
39514903"블로그"2020-05-01396"sk와이번스"49
39614904"블로그"2020-05-01397"성심당"49
39714905"블로그"2020-05-01398"persil"49
39814906"블로그"2020-05-01399"모닝글로리"49
39914907"블로그"2020-05-01400"롯데자이언츠"49