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

Categorical5
Text1
Numeric2

Alerts

dmn_nm has constant value ""Constant
chatbot_ctgry_nm has constant value ""Constant
convrs_partn_cl_nm has constant value ""Constant
area_nm is highly overall correlated with hotel_grad_noHigh correlation
hotel_grad_no is highly overall correlated with area_nmHigh correlation

Reproduction

Analysis started2023-12-10 10:15:44.143453
Analysis finished2023-12-10 10:15:45.686140
Duration1.54 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

2023-12-10T19:15:45.787662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:45.964105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박 100
100.0%

chatbot_ctgry_nm
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
호텔 100
100.0%

Length

2023-12-10T19:15:46.121261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:46.271372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
호텔 100
100.0%

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

2023-12-10T19:15:46.452756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:46.646171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고객 100
100.0%

convrs_ctgry_nm
Text

Distinct67
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:15:46.970019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length5.29
Min length2

Characters and Unicode

Total characters529
Distinct characters140
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)48.0%

Sample

1st row레스토랑석식
2nd row셔틀버스
3rd row교통안내
4th row선톡
5th row지도
ValueCountFrequency (%)
객실예약 7
 
7.0%
기본정보 5
 
5.0%
선톡 4
 
4.0%
교통안내 3
 
3.0%
디럭스더블 3
 
3.0%
운항정보 3
 
3.0%
객실타입 3
 
3.0%
호텔주소 2
 
2.0%
이원메뉴 2
 
2.0%
욕조 2
 
2.0%
Other values (57) 66
66.0%
2023-12-10T19:15:47.580523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 30
 
5.7%
실 17
 
3.2%
객 16
 
3.0%
정 16
 
3.0%
트 15
 
2.8%
룸 13
 
2.5%
타 13
 
2.5%
원 11
 
2.1%
기 11
 
2.1%
메 10
 
1.9%
Other values (130) 377
71.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 515
97.4%
Decimal Number 6
 
1.1%
Lowercase Letter 6
 
1.1%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 30
 
5.8%
실 17
 
3.3%
객 16
 
3.1%
정 16
 
3.1%
트 15
 
2.9%
룸 13
 
2.5%
타 13
 
2.5%
원 11
 
2.1%
기 11
 
2.1%
메 10
 
1.9%
Other values (118) 363
70.5%
Lowercase Letter
ValueCountFrequency (%)
a 1
16.7%
i 1
16.7%
r 1
16.7%
e 1
16.7%
s 1
16.7%
t 1
16.7%
Decimal Number
ValueCountFrequency (%)
1 3
50.0%
9 1
 
16.7%
2 1
 
16.7%
5 1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 515
97.4%
Common 8
 
1.5%
Latin 6
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 30
 
5.8%
실 17
 
3.3%
객 16
 
3.1%
정 16
 
3.1%
트 15
 
2.9%
룸 13
 
2.5%
타 13
 
2.5%
원 11
 
2.1%
기 11
 
2.1%
메 10
 
1.9%
Other values (118) 363
70.5%
Common
ValueCountFrequency (%)
1 3
37.5%
9 1
 
12.5%
2 1
 
12.5%
5 1
 
12.5%
( 1
 
12.5%
) 1
 
12.5%
Latin
ValueCountFrequency (%)
a 1
16.7%
i 1
16.7%
r 1
16.7%
e 1
16.7%
s 1
16.7%
t 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 515
97.4%
ASCII 14
 
2.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 30
 
5.8%
실 17
 
3.3%
객 16
 
3.1%
정 16
 
3.1%
트 15
 
2.9%
룸 13
 
2.5%
타 13
 
2.5%
원 11
 
2.1%
기 11
 
2.1%
메 10
 
1.9%
Other values (118) 363
70.5%
ASCII
ValueCountFrequency (%)
1 3
21.4%
9 1
 
7.1%
a 1
 
7.1%
i 1
 
7.1%
r 1
 
7.1%
e 1
 
7.1%
s 1
 
7.1%
t 1
 
7.1%
2 1
 
7.1%
5 1
 
7.1%
Other values (2) 2
14.3%

text_fq_rt
Real number (ℝ)

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.7055
Minimum0.5
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:15:47.829269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile2.44
Q15.41
median9.09
Q320
95-th percentile50
Maximum100
Range99.5
Interquartile range (IQR)14.59

Descriptive statistics

Standard deviation20.372779
Coefficient of variation (CV)1.1506469
Kurtosis6.2586445
Mean17.7055
Median Absolute Deviation (MAD)5.09
Skewness2.3590165
Sum1770.55
Variance415.05014
MonotonicityNot monotonic
2023-12-10T19:15:48.046613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
9.09 13
 
13.0%
4.0 10
 
10.0%
50.0 9
 
9.0%
14.29 7
 
7.0%
2.44 6
 
6.0%
20.0 5
 
5.0%
8.0 5
 
5.0%
5.41 4
 
4.0%
10.0 4
 
4.0%
6.1 4
 
4.0%
Other values (15) 33
33.0%
ValueCountFrequency (%)
0.5 2
 
2.0%
2.44 6
6.0%
3.66 1
 
1.0%
4.0 10
10.0%
4.88 4
 
4.0%
5.41 4
 
4.0%
6.1 4
 
4.0%
7.32 1
 
1.0%
8.0 5
5.0%
8.11 3
 
3.0%
ValueCountFrequency (%)
100.0 3
 
3.0%
50.0 9
9.0%
45.45 1
 
1.0%
40.0 2
 
2.0%
33.33 4
4.0%
32.43 1
 
1.0%
25.0 2
 
2.0%
22.22 1
 
1.0%
20.0 5
5.0%
18.18 2
 
2.0%

hotel_grad_no
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
4
48 
5
45 
3
7 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
4 48
48.0%
5 45
45.0%
3 7
 
7.0%

Length

2023-12-10T19:15:48.253832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:48.416285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 48
48.0%
5 45
45.0%
3 7
 
7.0%

area_nm
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울
42 
서울 강남구
25 
서울 중구
20 
인천
7 
제주
 
3

Length

Max length6
Median length2
Mean length3.6
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울 42
42.0%
서울 강남구 25
25.0%
서울 중구 20
20.0%
인천 7
 
7.0%
제주 3
 
3.0%
부산 3
 
3.0%

Length

2023-12-10T19:15:48.603502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:15:48.767423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울 87
60.0%
강남구 25
 
17.2%
중구 20
 
13.8%
인천 7
 
4.8%
제주 3
 
2.1%
부산 3
 
2.1%

base_de
Real number (ℝ)

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210881
Minimum20210430
Maximum20211231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:15:48.932405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210430
5-th percentile20210430
Q120210430
median20211031
Q320211130
95-th percentile20211231
Maximum20211231
Range801
Interquartile range (IQR)700

Descriptive statistics

Standard deviation318.46146
Coefficient of variation (CV)1.5756931 × 10-5
Kurtosis-1.4791617
Mean20210881
Median Absolute Deviation (MAD)200
Skewness-0.44602783
Sum2.0210881 × 109
Variance101417.7
MonotonicityNot monotonic
2023-12-10T19:15:49.099325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20211130 28
28.0%
20210430 28
28.0%
20211231 18
18.0%
20210731 12
12.0%
20210930 9
 
9.0%
20211031 5
 
5.0%
ValueCountFrequency (%)
20210430 28
28.0%
20210731 12
12.0%
20210930 9
 
9.0%
20211031 5
 
5.0%
20211130 28
28.0%
20211231 18
18.0%
ValueCountFrequency (%)
20211231 18
18.0%
20211130 28
28.0%
20211031 5
 
5.0%
20210930 9
 
9.0%
20210731 12
12.0%
20210430 28
28.0%

Interactions

2023-12-10T19:15:44.863467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:44.594606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:45.018879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:15:44.700194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:15:49.243843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
convrs_ctgry_nmtext_fq_rthotel_grad_noarea_nmbase_de
convrs_ctgry_nm1.0000.0000.0000.0000.657
text_fq_rt0.0001.0000.0000.7480.535
hotel_grad_no0.0000.0001.0001.0000.405
area_nm0.0000.7481.0001.0000.640
base_de0.6570.5350.4050.6401.000
2023-12-10T19:15:49.395861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
area_nmhotel_grad_no
area_nm1.0000.984
hotel_grad_no0.9841.000
2023-12-10T19:15:49.510862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
text_fq_rtbase_dehotel_grad_noarea_nm
text_fq_rt1.0000.2540.0000.357
base_de0.2541.0000.3010.428
hotel_grad_no0.0000.3011.0000.984
area_nm0.3570.4280.9841.000

Missing values

2023-12-10T19:15:45.308024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:15:45.597992image/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
0숙박호텔고객레스토랑석식9.095서울20211031
1숙박호텔고객셔틀버스9.095서울20211031
2숙박호텔고객교통안내18.185서울20211031
3숙박호텔고객선톡45.455서울20211031
4숙박호텔고객지도18.185서울20211031
5숙박호텔고객의료시설100.05제주20210731
6숙박호텔고객투베드룸듀플렉스스위트11.115서울20210731
7숙박호텔고객투베드룸듀플렉스스위트객실크기33.335서울20210731
8숙박호텔고객투베드룸듀플렉스스위트객실전망22.225서울20210731
9숙박호텔고객투베드룸듀플렉스스위트침대타입및정원11.115서울20210731
dmn_nmchatbot_ctgry_nmconvrs_partn_cl_nmconvrs_ctgry_nmtext_fq_rthotel_grad_noarea_nmbase_de
90숙박호텔고객객실수4.884서울 강남구20210430
91숙박호텔고객프리미어펫룸4.884서울 강남구20210430
92숙박호텔고객프리미어펫룸침대타입및정원4.884서울 강남구20210430
93숙박호텔고객다른객실보기3.664서울 강남구20210430
94숙박호텔고객기본정보2.444서울 강남구20210430
95숙박호텔고객디럭스트윈2.444서울 강남구20210430
96숙박호텔고객디럭스트윈객실전망2.444서울 강남구20210430
97숙박호텔고객디럭스트윈침대타입및정원2.444서울 강남구20210430
98숙박호텔고객디럭스패밀리트윈2.444서울 강남구20210430
99숙박호텔고객디럭스패밀리트윈침대타입및정원2.444서울 강남구20210430