Overview

Dataset statistics

Number of variables47
Number of observations50
Missing cells83
Missing cells (%)3.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.6 KiB
Average record size in memory380.6 B

Variable types

Text3
Numeric2
Categorical1
Boolean41

Alerts

SHOPNG_KND_INCLN_OTDR_AT has constant value ""Constant
SHOPNG_KND_INCLN_SKINCARE_SUPLI_AT has constant value ""Constant
SHOPNG_KND_INCLN_WTC_ACSRY_AT has constant value ""Constant
SHOPNG_KND_INCLN_BAG_AT has constant value ""Constant
SHOPNG_KND_INCLN_HEALTH_AT has constant value ""Constant
SHOPNG_KND_INCLN_BOOK_SOND_AT has constant value ""Constant
SHOPNG_KND_INCLN_ELPRD_AT has constant value ""Constant
SHOPNG_KND_INCLN_CHLDCR_AT has constant value ""Constant
SHOPNG_KND_INCLN_CNML_AT has constant value ""Constant
SHOPNG_KND_INCLN_ELCTY_UTNSIL_AT has constant value ""Constant
SHOPNG_KND_INCLN_CAR_SUPLI_AT has constant value ""Constant
SHOPNG_KND_INCLN_SPORTS_AT has constant value ""Constant
SHOPNG_KND_INCLN_ACSRY_AT has constant value ""Constant
SHOPNG_KND_INCLN_MOBLPHON_AT has constant value ""Constant
SHOPNG_KND_INCLN_CAR_AT has constant value ""Constant
DTFD_PIZZAHUT_AT has constant value ""Constant
DTFD_SICHUAN_CUSNE_AT has constant value ""Constant
DTFD_MCDONALD_AT has constant value ""Constant
DTFD_MCCAIN_AT has constant value ""Constant
DTFD_BKNG_AT has constant value ""Constant
DTFD_PORIG_AT has constant value ""Constant
DTFD_CUSNE_AT has constant value ""Constant
DTFD_PUDDING_AT has constant value ""Constant
DTFD_FRUIT_AT has constant value ""Constant
DTFD_HOPT_AT has constant value ""Constant
DTFD_DESSERT_AT has constant value ""Constant
SHOPNG_KND_INCLN_3C_AT is highly imbalanced (85.9%)Imbalance
SHOPNG_KND_INCLN_UNIFRM_AT is highly imbalanced (85.9%)Imbalance
SHOPNG_KND_INCLN_HMFUNSIN_AT is highly imbalanced (85.9%)Imbalance
SHOPNG_KND_INCLN_MKUP_AT is highly imbalanced (85.9%)Imbalance
SHOPNG_KND_INCLN_CHLDCR_SUPLI_AT is highly imbalanced (85.9%)Imbalance
SHOPNG_KND_INCLN_UNDE_AT is highly imbalanced (85.9%)Imbalance
SHOPNG_KND_INCLN_FOOD_AT is highly imbalanced (75.8%)Imbalance
SHOPNG_KND_INCLN_FTWR_AT is highly imbalanced (85.9%)Imbalance
SHOPNG_KND_INCLN_FEMALE_SUPLI_AT is highly imbalanced (85.9%)Imbalance
SHOPNG_KND_INCLN_FSH_FDSTFFS_AT is highly imbalanced (85.9%)Imbalance
SHOPNG_KND_INCLN_MALE_SUPLI_AT is highly imbalanced (85.9%)Imbalance
SHOPNG_KND_INCLN_DRTS_AT is highly imbalanced (85.9%)Imbalance
SHOPNG_KND_INCLN_BTY_AT is highly imbalanced (85.9%)Imbalance
DTFD_KFC_AT is highly imbalanced (85.9%)Imbalance
DTFD_STARBUCKS_AT is highly imbalanced (53.1%)Imbalance
JSSFC_NM has 35 (70.0%) missing valuesMissing
SHOPNG_BRAND_INCLN_CN has 48 (96.0%) missing valuesMissing
USID has unique valuesUnique
OCCP_CL has 17 (34.0%) zerosZeros
JSSFC_CL has 2 (4.0%) zerosZeros

Reproduction

Analysis started2023-12-10 09:45:54.416886
Analysis finished2023-12-10 09:45:55.188556
Duration0.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

USID
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-10T18:45:55.525908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters1800
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)100.0%

Sample

1st row1a2e9c75-8b40-475b-9b0d-a1be1dea229d
2nd rowcd936fff-8929-4b0c-9555-42243da445dc
3rd rowbde85489-c2d1-44e6-b74e-7cff7bc5c5ea
4th rowc84c780a-eb99-4775-b74f-348aafaf0d21
5th rowed13a1b2-79fb-4d68-8a4e-26b4f1376840
ValueCountFrequency (%)
1a2e9c75-8b40-475b-9b0d-a1be1dea229d 1
 
2.0%
a90b1cfe-0f23-4578-acde-b0a53f262759 1
 
2.0%
e6b50442-6242-4f51-89ed-802ae2a23c79 1
 
2.0%
9f25dfd1-af3f-417c-9f23-55cb2b6afbf2 1
 
2.0%
134d9b75-b40f-4b27-875e-ef7caa8820b0 1
 
2.0%
ee019d91-a2a1-49d9-9e60-b00ad7091d00 1
 
2.0%
f5bfe2fd-a44e-497c-88e3-bdaf3be7143f 1
 
2.0%
761fee12-6297-478c-8a69-8aa499a706f1 1
 
2.0%
da29e9ca-5485-4859-8747-38ec8a03a650 1
 
2.0%
7b5ecda0-f911-4109-b9e8-4d3b0b881b30 1
 
2.0%
Other values (40) 40
80.0%
2023-12-10T18:45:56.498179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 200
 
11.1%
4 148
 
8.2%
b 120
 
6.7%
8 111
 
6.2%
a 110
 
6.1%
f 101
 
5.6%
2 100
 
5.6%
1 99
 
5.5%
3 96
 
5.3%
0 95
 
5.3%
Other values (7) 620
34.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1002
55.7%
Lowercase Letter 598
33.2%
Dash Punctuation 200
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 148
14.8%
8 111
11.1%
2 100
10.0%
1 99
9.9%
3 96
9.6%
0 95
9.5%
5 94
9.4%
7 93
9.3%
9 87
8.7%
6 79
7.9%
Lowercase Letter
ValueCountFrequency (%)
b 120
20.1%
a 110
18.4%
f 101
16.9%
d 92
15.4%
e 89
14.9%
c 86
14.4%
Dash Punctuation
ValueCountFrequency (%)
- 200
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1202
66.8%
Latin 598
33.2%

Most frequent character per script

Common
ValueCountFrequency (%)
- 200
16.6%
4 148
12.3%
8 111
9.2%
2 100
8.3%
1 99
8.2%
3 96
8.0%
0 95
7.9%
5 94
7.8%
7 93
7.7%
9 87
7.2%
Latin
ValueCountFrequency (%)
b 120
20.1%
a 110
18.4%
f 101
16.9%
d 92
15.4%
e 89
14.9%
c 86
14.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1800
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 200
 
11.1%
4 148
 
8.2%
b 120
 
6.7%
8 111
 
6.2%
a 110
 
6.1%
f 101
 
5.6%
2 100
 
5.6%
1 99
 
5.5%
3 96
 
5.3%
0 95
 
5.3%
Other values (7) 620
34.4%

OCCP_CL
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.92
Minimum0
Maximum99
Zeros17
Zeros (%)34.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T18:45:56.799723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8.5
Q399
95-th percentile99
Maximum99
Range99
Interquartile range (IQR)99

Descriptive statistics

Standard deviation48.491464
Coefficient of variation (CV)1.0795072
Kurtosis-2.0130816
Mean44.92
Median Absolute Deviation (MAD)8.5
Skewness0.24077383
Sum2246
Variance2351.422
MonotonicityNot monotonic
2023-12-10T18:45:57.004715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
99 22
44.0%
0 17
34.0%
4 3
 
6.0%
9 2
 
4.0%
6 1
 
2.0%
2 1
 
2.0%
7 1
 
2.0%
5 1
 
2.0%
8 1
 
2.0%
10 1
 
2.0%
ValueCountFrequency (%)
0 17
34.0%
2 1
 
2.0%
4 3
 
6.0%
5 1
 
2.0%
6 1
 
2.0%
7 1
 
2.0%
8 1
 
2.0%
9 2
 
4.0%
10 1
 
2.0%
99 22
44.0%
ValueCountFrequency (%)
99 22
44.0%
10 1
 
2.0%
9 2
 
4.0%
8 1
 
2.0%
7 1
 
2.0%
6 1
 
2.0%
5 1
 
2.0%
4 3
 
6.0%
2 1
 
2.0%
0 17
34.0%

OCCP_NM
Categorical

Distinct10
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
<NA>
22 
직장인
17 
기업사업체
3 
재택인사
 
2
공무원
 
1
Other values (5)
5 

Length

Max length5
Median length4
Mean length3.64
Min length2

Unique

Unique6 ?
Unique (%)12.0%

Sample

1st row공무원
2nd row직장인
3rd row직장인
4th row<NA>
5th row직장인

Common Values

ValueCountFrequency (%)
<NA> 22
44.0%
직장인 17
34.0%
기업사업체 3
 
6.0%
재택인사 2
 
4.0%
공무원 1
 
2.0%
학생 1
 
2.0%
사무직 1
 
2.0%
전통노동직 1
 
2.0%
농민 1
 
2.0%
새 노동직 1
 
2.0%

Length

2023-12-10T18:45:57.300370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:45:57.636811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 22
43.1%
직장인 17
33.3%
기업사업체 3
 
5.9%
재택인사 2
 
3.9%
공무원 1
 
2.0%
학생 1
 
2.0%
사무직 1
 
2.0%
전통노동직 1
 
2.0%
농민 1
 
2.0%
새 1
 
2.0%

JSSFC_CL
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.96
Minimum0
Maximum99
Zeros2
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-10T18:45:57.932263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14.6
Q138.25
median99
Q399
95-th percentile99
Maximum99
Range99
Interquartile range (IQR)60.75

Descriptive statistics

Standard deviation34.71632
Coefficient of variation (CV)0.45109563
Kurtosis-0.69135455
Mean76.96
Median Absolute Deviation (MAD)0
Skewness-1.0465763
Sum3848
Variance1205.2229
MonotonicityNot monotonic
2023-12-10T18:45:58.228490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
99 35
70.0%
36 2
 
4.0%
0 2
 
4.0%
27 2
 
4.0%
30 1
 
2.0%
39 1
 
2.0%
38 1
 
2.0%
11 1
 
2.0%
31 1
 
2.0%
23 1
 
2.0%
Other values (3) 3
 
6.0%
ValueCountFrequency (%)
0 2
4.0%
11 1
2.0%
19 1
2.0%
23 1
2.0%
26 1
2.0%
27 2
4.0%
30 1
2.0%
31 1
2.0%
36 2
4.0%
38 1
2.0%
ValueCountFrequency (%)
99 35
70.0%
40 1
 
2.0%
39 1
 
2.0%
38 1
 
2.0%
36 2
 
4.0%
31 1
 
2.0%
30 1
 
2.0%
27 2
 
4.0%
26 1
 
2.0%
23 1
 
2.0%

JSSFC_NM
Text

MISSING 

Distinct12
Distinct (%)80.0%
Missing35
Missing (%)70.0%
Memory size532.0 B
2023-12-10T18:45:58.645419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.8666667
Min length2

Characters and Unicode

Total characters73
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)60.0%

Sample

1st row정부기구인원
2nd row소매종사자
3rd row생활서비스종사자
4th row호텔종사자
5th row텔레콤대리점
ValueCountFrequency (%)
생활서비스종사자 2
13.3%
교사 2
13.3%
재택인사 2
13.3%
정부기구인원 1
6.7%
소매종사자 1
6.7%
호텔종사자 1
6.7%
텔레콤대리점 1
6.7%
교육종사자 1
6.7%
회사사무직 1
6.7%
공장인부 1
6.7%
Other values (2) 2
13.3%
2023-12-10T18:45:59.324131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 12
 
16.4%
종 6
 
8.2%
자 6
 
8.2%
인 4
 
5.5%
교 3
 
4.1%
생 2
 
2.7%
택 2
 
2.7%
텔 2
 
2.7%
부 2
 
2.7%
재 2
 
2.7%
Other values (28) 32
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 12
 
16.4%
종 6
 
8.2%
자 6
 
8.2%
인 4
 
5.5%
교 3
 
4.1%
생 2
 
2.7%
택 2
 
2.7%
텔 2
 
2.7%
부 2
 
2.7%
재 2
 
2.7%
Other values (28) 32
43.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 12
 
16.4%
종 6
 
8.2%
자 6
 
8.2%
인 4
 
5.5%
교 3
 
4.1%
생 2
 
2.7%
택 2
 
2.7%
텔 2
 
2.7%
부 2
 
2.7%
재 2
 
2.7%
Other values (28) 32
43.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 12
 
16.4%
종 6
 
8.2%
자 6
 
8.2%
인 4
 
5.5%
교 3
 
4.1%
생 2
 
2.7%
택 2
 
2.7%
텔 2
 
2.7%
부 2
 
2.7%
재 2
 
2.7%
Other values (28) 32
43.8%

SHOPNG_KND_INCLN_3C_AT
Boolean

IMBALANCE 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
49 
True
 
1
ValueCountFrequency (%)
False 49
98.0%
True 1
 
2.0%
2023-12-10T18:45:59.527305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_UNIFRM_AT
Boolean

IMBALANCE 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
49 
True
 
1
ValueCountFrequency (%)
False 49
98.0%
True 1
 
2.0%
2023-12-10T18:45:59.701795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_OTDR_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:45:59.865683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_SKINCARE_SUPLI_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:45:59.990843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_HMFUNSIN_AT
Boolean

IMBALANCE 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
49 
True
 
1
ValueCountFrequency (%)
False 49
98.0%
True 1
 
2.0%
2023-12-10T18:46:00.173330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_MKUP_AT
Boolean

IMBALANCE 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
49 
True
 
1
ValueCountFrequency (%)
False 49
98.0%
True 1
 
2.0%
2023-12-10T18:46:00.349830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_CHLDCR_SUPLI_AT
Boolean

IMBALANCE 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
49 
True
 
1
ValueCountFrequency (%)
False 49
98.0%
True 1
 
2.0%
2023-12-10T18:46:00.579856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_UNDE_AT
Boolean

IMBALANCE 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
49 
True
 
1
ValueCountFrequency (%)
False 49
98.0%
True 1
 
2.0%
2023-12-10T18:46:00.765172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_FOOD_AT
Boolean

IMBALANCE 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
48 
True
 
2
ValueCountFrequency (%)
False 48
96.0%
True 2
 
4.0%
2023-12-10T18:46:00.930719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_WTC_ACSRY_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:01.067672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_BAG_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:01.198295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_FTWR_AT
Boolean

IMBALANCE 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
49 
True
 
1
ValueCountFrequency (%)
False 49
98.0%
True 1
 
2.0%
2023-12-10T18:46:01.334329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_HEALTH_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:01.473153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_BOOK_SOND_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:01.604394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_FEMALE_SUPLI_AT
Boolean

IMBALANCE 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
49 
True
 
1
ValueCountFrequency (%)
False 49
98.0%
True 1
 
2.0%
2023-12-10T18:46:01.754570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_ELPRD_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:01.910575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_CHLDCR_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:02.162935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_CNML_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:02.345308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_FSH_FDSTFFS_AT
Boolean

IMBALANCE 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
49 
True
 
1
ValueCountFrequency (%)
False 49
98.0%
True 1
 
2.0%
2023-12-10T18:46:02.578580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_ELCTY_UTNSIL_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:02.749570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_MALE_SUPLI_AT
Boolean

IMBALANCE 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
49 
True
 
1
ValueCountFrequency (%)
False 49
98.0%
True 1
 
2.0%
2023-12-10T18:46:02.899763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_DRTS_AT
Boolean

IMBALANCE 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
49 
True
 
1
ValueCountFrequency (%)
False 49
98.0%
True 1
 
2.0%
2023-12-10T18:46:03.115988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_BTY_AT
Boolean

IMBALANCE 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
49 
True
 
1
ValueCountFrequency (%)
False 49
98.0%
True 1
 
2.0%
2023-12-10T18:46:03.268970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_CAR_SUPLI_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:03.427438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_SPORTS_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:03.599727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_ACSRY_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:03.851439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_MOBLPHON_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:04.110781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_KND_INCLN_CAR_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:04.307346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

DTFD_PIZZAHUT_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:04.551751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

DTFD_SICHUAN_CUSNE_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:04.733335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

DTFD_KFC_AT
Boolean

IMBALANCE 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
49 
True
 
1
ValueCountFrequency (%)
False 49
98.0%
True 1
 
2.0%
2023-12-10T18:46:04.868219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

DTFD_MCDONALD_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:05.007411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

DTFD_MCCAIN_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:05.143953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

DTFD_STARBUCKS_AT
Boolean

IMBALANCE 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
45 
True
5 
ValueCountFrequency (%)
False 45
90.0%
True 5
 
10.0%
2023-12-10T18:46:05.310236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

DTFD_BKNG_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:05.468653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

DTFD_PORIG_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:05.602521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

DTFD_CUSNE_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:05.830580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

DTFD_PUDDING_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:06.085833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

DTFD_FRUIT_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:06.264948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

DTFD_HOPT_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:06.402712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

DTFD_DESSERT_AT
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
False
50 
ValueCountFrequency (%)
False 50
100.0%
2023-12-10T18:46:06.609177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

SHOPNG_BRAND_INCLN_CN
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing48
Missing (%)96.0%
Memory size532.0 B
2023-12-10T18:46:06.840453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5.5
Mean length5.5
Min length2

Characters and Unicode

Total characters11
Distinct characters11
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowMUJI|无印良品
2nd row小米
ValueCountFrequency (%)
muji|无印良品 1
50.0%
小米 1
50.0%
2023-12-10T18:46:07.408720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 1
9.1%
U 1
9.1%
J 1
9.1%
I 1
9.1%
| 1
9.1%
无 1
9.1%
印 1
9.1%
良 1
9.1%
品 1
9.1%
小 1
9.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
54.5%
Uppercase Letter 4
36.4%
Math Symbol 1
 
9.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
无 1
16.7%
印 1
16.7%
良 1
16.7%
品 1
16.7%
小 1
16.7%
米 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
M 1
25.0%
U 1
25.0%
J 1
25.0%
I 1
25.0%
Math Symbol
ValueCountFrequency (%)
| 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 6
54.5%
Latin 4
36.4%
Common 1
 
9.1%

Most frequent character per script

Han
ValueCountFrequency (%)
无 1
16.7%
印 1
16.7%
良 1
16.7%
品 1
16.7%
小 1
16.7%
米 1
16.7%
Latin
ValueCountFrequency (%)
M 1
25.0%
U 1
25.0%
J 1
25.0%
I 1
25.0%
Common
ValueCountFrequency (%)
| 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 6
54.5%
ASCII 5
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 1
20.0%
U 1
20.0%
J 1
20.0%
I 1
20.0%
| 1
20.0%
CJK
ValueCountFrequency (%)
无 1
16.7%
印 1
16.7%
良 1
16.7%
品 1
16.7%
小 1
16.7%
米 1
16.7%

Sample

USIDOCCP_CLOCCP_NMJSSFC_CLJSSFC_NMSHOPNG_KND_INCLN_3C_ATSHOPNG_KND_INCLN_UNIFRM_ATSHOPNG_KND_INCLN_OTDR_ATSHOPNG_KND_INCLN_SKINCARE_SUPLI_ATSHOPNG_KND_INCLN_HMFUNSIN_ATSHOPNG_KND_INCLN_MKUP_ATSHOPNG_KND_INCLN_CHLDCR_SUPLI_ATSHOPNG_KND_INCLN_UNDE_ATSHOPNG_KND_INCLN_FOOD_ATSHOPNG_KND_INCLN_WTC_ACSRY_ATSHOPNG_KND_INCLN_BAG_ATSHOPNG_KND_INCLN_FTWR_ATSHOPNG_KND_INCLN_HEALTH_ATSHOPNG_KND_INCLN_BOOK_SOND_ATSHOPNG_KND_INCLN_FEMALE_SUPLI_ATSHOPNG_KND_INCLN_ELPRD_ATSHOPNG_KND_INCLN_CHLDCR_ATSHOPNG_KND_INCLN_CNML_ATSHOPNG_KND_INCLN_FSH_FDSTFFS_ATSHOPNG_KND_INCLN_ELCTY_UTNSIL_ATSHOPNG_KND_INCLN_MALE_SUPLI_ATSHOPNG_KND_INCLN_DRTS_ATSHOPNG_KND_INCLN_BTY_ATSHOPNG_KND_INCLN_CAR_SUPLI_ATSHOPNG_KND_INCLN_SPORTS_ATSHOPNG_KND_INCLN_ACSRY_ATSHOPNG_KND_INCLN_MOBLPHON_ATSHOPNG_KND_INCLN_CAR_ATDTFD_PIZZAHUT_ATDTFD_SICHUAN_CUSNE_ATDTFD_KFC_ATDTFD_MCDONALD_ATDTFD_MCCAIN_ATDTFD_STARBUCKS_ATDTFD_BKNG_ATDTFD_PORIG_ATDTFD_CUSNE_ATDTFD_PUDDING_ATDTFD_FRUIT_ATDTFD_HOPT_ATDTFD_DESSERT_ATSHOPNG_BRAND_INCLN_CN
01a2e9c75-8b40-475b-9b0d-a1be1dea229d6공무원30정부기구인원NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN<NA>
1cd936fff-8929-4b0c-9555-42243da445dc0직장인39소매종사자NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN<NA>
2bde85489-c2d1-44e6-b74e-7cff7bc5c5ea0직장인36생활서비스종사자NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN<NA>
3c84c780a-eb99-4775-b74f-348aafaf0d2199<NA>99<NA>NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN<NA>
4ed13a1b2-79fb-4d68-8a4e-26b4f13768400직장인38호텔종사자NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN<NA>
5473ff65c-bd00-4868-b2d4-daa32c8fb97a0직장인11텔레콤대리점NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN<NA>
6a28120dc-97cd-4dd7-b2b6-64ecaeaaeee799<NA>99<NA>NYNNYNNNNNNNNNNNNNNNNNNNNNNNNNNNNYNNNNNNNMUJI|无印良品
745102bb7-4cdd-49a4-80f5-f3370547474599<NA>99<NA>NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN<NA>
84f1719c2-1a6d-477c-8958-707bf80ca0550직장인99<NA>NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN<NA>
9f4fb33ab-3e1f-41c7-b827-c5295a93c95b99<NA>99<NA>NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN<NA>
USIDOCCP_CLOCCP_NMJSSFC_CLJSSFC_NMSHOPNG_KND_INCLN_3C_ATSHOPNG_KND_INCLN_UNIFRM_ATSHOPNG_KND_INCLN_OTDR_ATSHOPNG_KND_INCLN_SKINCARE_SUPLI_ATSHOPNG_KND_INCLN_HMFUNSIN_ATSHOPNG_KND_INCLN_MKUP_ATSHOPNG_KND_INCLN_CHLDCR_SUPLI_ATSHOPNG_KND_INCLN_UNDE_ATSHOPNG_KND_INCLN_FOOD_ATSHOPNG_KND_INCLN_WTC_ACSRY_ATSHOPNG_KND_INCLN_BAG_ATSHOPNG_KND_INCLN_FTWR_ATSHOPNG_KND_INCLN_HEALTH_ATSHOPNG_KND_INCLN_BOOK_SOND_ATSHOPNG_KND_INCLN_FEMALE_SUPLI_ATSHOPNG_KND_INCLN_ELPRD_ATSHOPNG_KND_INCLN_CHLDCR_ATSHOPNG_KND_INCLN_CNML_ATSHOPNG_KND_INCLN_FSH_FDSTFFS_ATSHOPNG_KND_INCLN_ELCTY_UTNSIL_ATSHOPNG_KND_INCLN_MALE_SUPLI_ATSHOPNG_KND_INCLN_DRTS_ATSHOPNG_KND_INCLN_BTY_ATSHOPNG_KND_INCLN_CAR_SUPLI_ATSHOPNG_KND_INCLN_SPORTS_ATSHOPNG_KND_INCLN_ACSRY_ATSHOPNG_KND_INCLN_MOBLPHON_ATSHOPNG_KND_INCLN_CAR_ATDTFD_PIZZAHUT_ATDTFD_SICHUAN_CUSNE_ATDTFD_KFC_ATDTFD_MCDONALD_ATDTFD_MCCAIN_ATDTFD_STARBUCKS_ATDTFD_BKNG_ATDTFD_PORIG_ATDTFD_CUSNE_ATDTFD_PUDDING_ATDTFD_FRUIT_ATDTFD_HOPT_ATDTFD_DESSERT_ATSHOPNG_BRAND_INCLN_CN
40056b6413-a3a4-4a0e-acad-5f1cc58270bf8농민19농촌주민NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNYNNNNNNN<NA>
41d20e1c1d-4e74-4115-8b87-7f76df0647e40직장인99<NA>NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN<NA>
42b17127e2-5e46-4876-a6ad-bc51b18326a50직장인99<NA>NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN<NA>
43d698457e-48f0-4603-861c-59ba7b220aa610새 노동직40요식종사자NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN<NA>
441184a8d7-a4e1-4a50-8033-ef41709c11f599<NA>99<NA>NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN<NA>
45f7ae199e-8b40-440f-bdb3-8a397927be4899<NA>99<NA>NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN<NA>
46d3fc3856-4b94-4eef-bf58-a7a15ca63f0a99<NA>99<NA>NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN<NA>
47ba84d679-c4c3-466e-a55b-2477d2b73ea999<NA>99<NA>NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN<NA>
48e6b50442-6242-4f51-89ed-802ae2a23c799재택인사27재택인사NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN<NA>
494921fca4-ebe9-4fcf-be0c-24bcc589c3d50직장인99<NA>NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN<NA>