Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.7 KiB
Average record size in memory68.3 B

Variable types

Categorical6
Text1
Numeric1

Alerts

dmn_nm has constant value ""Constant
convrs_partn_cl_nm has constant value ""Constant
base_de has constant value ""Constant
chatbot_ctgry_nm is highly overall correlated with hotel_grad_no and 1 other fieldsHigh correlation
hotel_grad_no is highly overall correlated with chatbot_ctgry_nm and 1 other fieldsHigh correlation
area_nm is highly overall correlated with chatbot_ctgry_nm and 1 other fieldsHigh correlation
chatbot_ctgry_nm is highly imbalanced (80.6%)Imbalance
hotel_grad_no is highly imbalanced (80.6%)Imbalance
area_nm is highly imbalanced (80.6%)Imbalance
convrs_ctgry_nm has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:14:48.531862
Analysis finished2023-12-10 10:14:49.584055
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

dmn_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
숙박
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
숙박 100
100.0%

Length

2023-12-10T19:14:49.768221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:14:49.945362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박 100
100.0%

chatbot_ctgry_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
호텔
97 
펜션
 
3

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row호텔
2nd row펜션
3rd row호텔
4th row호텔
5th row호텔

Common Values

ValueCountFrequency (%)
호텔 97
97.0%
펜션 3
 
3.0%

Length

2023-12-10T19:14:50.138555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:14:50.355902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
호텔 97
97.0%
펜션 3
 
3.0%

convrs_partn_cl_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
고객
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고객 100
100.0%

Length

2023-12-10T19:14:50.554897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:14:50.711414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고객 100
100.0%

convrs_ctgry_nm
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:14:51.180914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length4.91
Min length2

Characters and Unicode

Total characters491
Distinct characters167
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

Unique100 ?
Unique (%)100.0%

Sample

1st row선톡
2nd row청와삼대중식위치
3rd row체크인
4th row부대시설
5th row캐슬테라스요금
ValueCountFrequency (%)
선톡 1
 
1.0%
편의점 1
 
1.0%
운항정보 1
 
1.0%
캐슬테라스 1
 
1.0%
낙원 1
 
1.0%
객실타입 1
 
1.0%
액티비티 1
 
1.0%
레스토랑조식 1
 
1.0%
지도 1
 
1.0%
룸서비스 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T19:14:51.921304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 30
 
6.1%
메 12
 
2.4%
레 10
 
2.0%
랑 10
 
2.0%
토 10
 
2.0%
식 10
 
2.0%
예 10
 
2.0%
라 10
 
2.0%
약 10
 
2.0%
원 9
 
1.8%
Other values (157) 370
75.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 487
99.2%
Uppercase Letter 3
 
0.6%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 30
 
6.2%
메 12
 
2.5%
레 10
 
2.1%
랑 10
 
2.1%
토 10
 
2.1%
식 10
 
2.1%
예 10
 
2.1%
라 10
 
2.1%
약 10
 
2.1%
원 9
 
1.8%
Other values (153) 366
75.2%
Uppercase Letter
ValueCountFrequency (%)
D 1
33.3%
M 1
33.3%
Z 1
33.3%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 487
99.2%
Latin 3
 
0.6%
Common 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 30
 
6.2%
메 12
 
2.5%
레 10
 
2.1%
랑 10
 
2.1%
토 10
 
2.1%
식 10
 
2.1%
예 10
 
2.1%
라 10
 
2.1%
약 10
 
2.1%
원 9
 
1.8%
Other values (153) 366
75.2%
Latin
ValueCountFrequency (%)
D 1
33.3%
M 1
33.3%
Z 1
33.3%
Common
ValueCountFrequency (%)
3 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 487
99.2%
ASCII 4
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 30
 
6.2%
메 12
 
2.5%
레 10
 
2.1%
랑 10
 
2.1%
토 10
 
2.1%
식 10
 
2.1%
예 10
 
2.1%
라 10
 
2.1%
약 10
 
2.1%
원 9
 
1.8%
Other values (153) 366
75.2%
ASCII
ValueCountFrequency (%)
D 1
25.0%
M 1
25.0%
Z 1
25.0%
3 1
25.0%

text_fq_rt
Real number (ℝ)

Distinct38
Distinct (%)38.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9938
Minimum0.03
Maximum79.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:14:52.139318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.03
5-th percentile0.03
Q10.04
median0.085
Q30.2025
95-th percentile0.903
Maximum79.57
Range79.54
Interquartile range (IQR)0.1625

Descriptive statistics

Standard deviation7.9448966
Coefficient of variation (CV)7.9944622
Kurtosis99.590304
Mean0.9938
Median Absolute Deviation (MAD)0.045
Skewness9.9700045
Sum99.38
Variance63.121381
MonotonicityNot monotonic
2023-12-10T19:14:52.408996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0.04 28
28.0%
0.05 8
 
8.0%
0.03 6
 
6.0%
0.13 4
 
4.0%
0.12 4
 
4.0%
0.08 4
 
4.0%
0.11 3
 
3.0%
0.06 3
 
3.0%
0.1 3
 
3.0%
0.16 3
 
3.0%
Other values (28) 34
34.0%
ValueCountFrequency (%)
0.03 6
 
6.0%
0.04 28
28.0%
0.05 8
 
8.0%
0.06 3
 
3.0%
0.07 1
 
1.0%
0.08 4
 
4.0%
0.09 2
 
2.0%
0.1 3
 
3.0%
0.11 3
 
3.0%
0.12 4
 
4.0%
ValueCountFrequency (%)
79.57 1
1.0%
2.82 1
1.0%
1.29 1
1.0%
1.27 1
1.0%
0.96 1
1.0%
0.9 1
1.0%
0.69 1
1.0%
0.57 1
1.0%
0.48 1
1.0%
0.46 1
1.0%

hotel_grad_no
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
5
97 
3
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row3
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5 97
97.0%
3 3
 
3.0%

Length

2023-12-10T19:14:52.748665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:14:52.892832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 97
97.0%
3 3
 
3.0%

area_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울
97 
서울 금천구
 
3

Length

Max length6
Median length2
Mean length2.12
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울
2nd row서울 금천구
3rd row서울
4th row서울
5th row서울

Common Values

ValueCountFrequency (%)
서울 97
97.0%
서울 금천구 3
 
3.0%

Length

2023-12-10T19:14:53.072017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:14:53.247211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울 100
97.1%
금천구 3
 
2.9%

base_de
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20211031
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20211031
2nd row20211031
3rd row20211031
4th row20211031
5th row20211031

Common Values

ValueCountFrequency (%)
20211031 100
100.0%

Length

2023-12-10T19:14:53.426907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:14:53.594479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20211031 100
100.0%

Interactions

2023-12-10T19:14:48.971496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:14:53.710296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
chatbot_ctgry_nmconvrs_ctgry_nmtext_fq_rthotel_grad_noarea_nm
chatbot_ctgry_nm1.0001.0000.0000.9630.963
convrs_ctgry_nm1.0001.0001.0001.0001.000
text_fq_rt0.0001.0001.0000.0000.000
hotel_grad_no0.9631.0000.0001.0000.963
area_nm0.9631.0000.0000.9631.000
2023-12-10T19:14:53.927773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
area_nmhotel_grad_nochatbot_ctgry_nm
area_nm1.0000.8260.826
hotel_grad_no0.8261.0000.826
chatbot_ctgry_nm0.8260.8261.000
2023-12-10T19:14:54.124356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
text_fq_rtchatbot_ctgry_nmhotel_grad_noarea_nm
text_fq_rt1.0000.0000.0000.000
chatbot_ctgry_nm0.0001.0000.8260.826
hotel_grad_no0.0000.8261.0000.826
area_nm0.0000.8260.8261.000

Missing values

2023-12-10T19:14:49.237442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:14:49.486639image/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

dmn_nmchatbot_ctgry_nmconvrs_partn_cl_nmconvrs_ctgry_nmtext_fq_rthotel_grad_noarea_nmbase_de
0숙박호텔고객선톡79.575서울20211031
1숙박펜션고객청와삼대중식위치0.433서울 금천구20211031
2숙박호텔고객체크인0.045서울20211031
3숙박호텔고객부대시설1.275서울20211031
4숙박호텔고객캐슬테라스요금0.135서울20211031
5숙박호텔고객객실예약2.825서울20211031
6숙박호텔고객투베드룸듀플렉스스위트0.045서울20211031
7숙박펜션고객청와삼대조식예약0.433서울 금천구20211031
8숙박호텔고객운동시설0.215서울20211031
9숙박호텔고객레스토랑조식메뉴0.125서울20211031
dmn_nmchatbot_ctgry_nmconvrs_partn_cl_nmconvrs_ctgry_nmtext_fq_rthotel_grad_noarea_nmbase_de
90숙박호텔고객캐슬테라스시간0.065서울20211031
91숙박호텔고객로얄마일0.055서울20211031
92숙박호텔고객상품권0.055서울20211031
93숙박호텔고객봉래헌메뉴0.055서울20211031
94숙박호텔고객프로모션안내0.055서울20211031
95숙박호텔고객낙원예약0.045서울20211031
96숙박호텔고객낙원요금0.045서울20211031
97숙박호텔고객이원메뉴0.045서울20211031
98숙박호텔고객메이필드돌잔치0.045서울20211031
99숙박호텔고객모닝콜0.045서울20211031