Overview

Dataset statistics

Number of variables7
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory60.3 B

Variable types

Categorical4
Numeric3

Alerts

trrsrt_nm is highly overall correlated with tel_no and 2 other fieldsHigh correlation
addr is highly overall correlated with tel_no and 2 other fieldsHigh correlation
cl_nm is highly overall correlated with trrsrt_nm and 1 other fieldsHigh correlation
tel_no is highly overall correlated with trrsrt_nm and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-10 09:55:32.624994
Analysis finished2023-12-10 09:55:35.372608
Duration2.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

cl_nm
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
자연
75 
공연전시
25 

Length

Max length4
Median length2
Mean length2.5
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공연전시
2nd row자연
3rd row공연전시
4th row공연전시
5th row공연전시

Common Values

ValueCountFrequency (%)
자연 75
75.0%
공연전시 25
 
25.0%

Length

2023-12-10T18:55:35.780221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:55:36.455182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자연 75
75.0%
공연전시 25
 
25.0%

trrsrt_nm
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
산방산 암벽식물지대
28 
서귀포 치유의 숲
28 
이중섭미술관
24 
용머리해안
11 
정방폭포
5 
Other values (2)
4 

Length

Max length10
Median length9
Mean length7.71
Min length4

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row서복전시관
2nd row천지연폭포
3rd row이중섭미술관
4th row이중섭미술관
5th row이중섭미술관

Common Values

ValueCountFrequency (%)
산방산 암벽식물지대 28
28.0%
서귀포 치유의 숲 28
28.0%
이중섭미술관 24
24.0%
용머리해안 11
 
11.0%
정방폭포 5
 
5.0%
천지연폭포 3
 
3.0%
서복전시관 1
 
1.0%

Length

2023-12-10T18:55:37.171933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:55:37.627228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
산방산 28
15.2%
암벽식물지대 28
15.2%
서귀포 28
15.2%
치유의 28
15.2%
숲 28
15.2%
이중섭미술관 24
13.0%
용머리해안 11
 
6.0%
정방폭포 5
 
2.7%
천지연폭포 3
 
1.6%
서복전시관 1
 
0.5%

addr
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
제주 서귀포시 안덕면 사계리 산16
28 
제주 서귀포시 산록남로 2271
28 
제주 서귀포시 이중섭로 27-3
24 
제주 서귀포시 안덕면 사계리 112-3
11 
제주 서귀포시 칠십리로214번길 37
5 
Other values (2)
4 

Length

Max length24
Median length17
Mean length18.22
Min length17

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row제주 서귀포시 칠십리로 156-8 서복전시관
2nd row제주 서귀포시 천지동 667-7
3rd row제주 서귀포시 이중섭로 27-3
4th row제주 서귀포시 이중섭로 27-3
5th row제주 서귀포시 이중섭로 27-3

Common Values

ValueCountFrequency (%)
제주 서귀포시 안덕면 사계리 산16 28
28.0%
제주 서귀포시 산록남로 2271 28
28.0%
제주 서귀포시 이중섭로 27-3 24
24.0%
제주 서귀포시 안덕면 사계리 112-3 11
 
11.0%
제주 서귀포시 칠십리로214번길 37 5
 
5.0%
제주 서귀포시 천지동 667-7 3
 
3.0%
제주 서귀포시 칠십리로 156-8 서복전시관 1
 
1.0%

Length

2023-12-10T18:55:37.973108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:55:38.290344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주 100
22.7%
서귀포시 100
22.7%
안덕면 39
 
8.9%
사계리 39
 
8.9%
산16 28
 
6.4%
산록남로 28
 
6.4%
2271 28
 
6.4%
27-3 24
 
5.5%
이중섭로 24
 
5.5%
112-3 11
 
2.5%
Other values (7) 19
 
4.3%

tel_no
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4767702 × 108
Minimum6.4733153 × 108
Maximum6.4794294 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:55:38.532948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.4733153 × 108
5-th percentile6.4733153 × 108
Q16.4760307 × 108
median6.4760357 × 108
Q36.4794294 × 108
95-th percentile6.4794294 × 108
Maximum6.4794294 × 108
Range611412
Interquartile range (IQR)339873

Descriptive statistics

Standard deviation181950.25
Coefficient of variation (CV)0.00028092744
Kurtosis-0.58798336
Mean6.4767702 × 108
Median Absolute Deviation (MAD)500
Skewness0.29351453
Sum6.4767702 × 1010
Variance3.3105893 × 1010
MonotonicityNot monotonic
2023-12-10T18:55:38.818289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
647942940 28
28.0%
647603067 28
28.0%
647603567 24
24.0%
647606321 11
 
11.0%
647331530 5
 
5.0%
647331528 3
 
3.0%
647606361 1
 
1.0%
ValueCountFrequency (%)
647331528 3
 
3.0%
647331530 5
 
5.0%
647603067 28
28.0%
647603567 24
24.0%
647606321 11
 
11.0%
647606361 1
 
1.0%
647942940 28
28.0%
ValueCountFrequency (%)
647942940 28
28.0%
647606361 1
 
1.0%
647606321 11
 
11.0%
647603567 24
24.0%
647603067 28
28.0%
647331530 5
 
5.0%
647331528 3
 
3.0%

entrn_flag_nm
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
무료경로
74 
무료장애인
17 
무료유아
9 

Length

Max length5
Median length4
Mean length4.17
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row무료경로
2nd row무료경로
3rd row무료경로
4th row무료경로
5th row무료장애인

Common Values

ValueCountFrequency (%)
무료경로 74
74.0%
무료장애인 17
 
17.0%
무료유아 9
 
9.0%

Length

2023-12-10T18:55:39.084664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:55:39.290562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
무료경로 74
74.0%
무료장애인 17
 
17.0%
무료유아 9
 
9.0%

entrn_nmpr_co
Real number (ℝ)

Distinct64
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.14
Minimum5
Maximum429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:55:39.579218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile9.95
Q123
median41
Q366.25
95-th percentile284.5
Maximum429
Range424
Interquartile range (IQR)43.25

Descriptive statistics

Standard deviation86.975559
Coefficient of variation (CV)1.2056496
Kurtosis4.321574
Mean72.14
Median Absolute Deviation (MAD)19
Skewness2.2092779
Sum7214
Variance7564.7479
MonotonicityNot monotonic
2023-12-10T18:55:39.937270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
43 5
 
5.0%
35 4
 
4.0%
22 4
 
4.0%
23 4
 
4.0%
10 3
 
3.0%
47 3
 
3.0%
17 3
 
3.0%
63 3
 
3.0%
41 3
 
3.0%
57 3
 
3.0%
Other values (54) 65
65.0%
ValueCountFrequency (%)
5 1
 
1.0%
6 1
 
1.0%
7 1
 
1.0%
9 2
2.0%
10 3
3.0%
11 2
2.0%
13 2
2.0%
14 2
2.0%
16 1
 
1.0%
17 3
3.0%
ValueCountFrequency (%)
429 1
1.0%
340 1
1.0%
328 1
1.0%
316 1
1.0%
294 1
1.0%
284 1
1.0%
283 1
1.0%
261 1
1.0%
257 1
1.0%
222 1
1.0%

entrn_de
Real number (ℝ)

Distinct30
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20230615
Minimum20230601
Maximum20230630
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:55:40.239266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20230601
5-th percentile20230602
Q120230607
median20230615
Q320230622
95-th percentile20230629
Maximum20230630
Range29
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.7216149
Coefficient of variation (CV)4.3110973 × 10-7
Kurtosis-1.1926578
Mean20230615
Median Absolute Deviation (MAD)7.5
Skewness0.04757527
Sum2.0230615 × 109
Variance76.066566
MonotonicityNot monotonic
2023-12-10T18:55:40.549260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
20230616 5
 
5.0%
20230603 5
 
5.0%
20230604 5
 
5.0%
20230614 4
 
4.0%
20230624 4
 
4.0%
20230623 4
 
4.0%
20230622 4
 
4.0%
20230615 4
 
4.0%
20230617 4
 
4.0%
20230602 4
 
4.0%
Other values (20) 57
57.0%
ValueCountFrequency (%)
20230601 4
4.0%
20230602 4
4.0%
20230603 5
5.0%
20230604 5
5.0%
20230605 2
 
2.0%
20230606 3
3.0%
20230607 3
3.0%
20230608 4
4.0%
20230609 3
3.0%
20230610 3
3.0%
ValueCountFrequency (%)
20230630 2
2.0%
20230629 4
4.0%
20230628 3
3.0%
20230627 3
3.0%
20230626 2
2.0%
20230625 2
2.0%
20230624 4
4.0%
20230623 4
4.0%
20230622 4
4.0%
20230621 3
3.0%

Interactions

2023-12-10T18:55:34.282055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:55:33.292323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:55:33.806952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:55:34.466589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:55:33.469693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:55:33.977371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:55:34.638824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:55:33.627696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:55:34.117795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:55:40.785189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
cl_nmtrrsrt_nmaddrtel_noentrn_flag_nmentrn_nmpr_coentrn_de
cl_nm1.0001.0001.0000.2470.0000.1730.000
trrsrt_nm1.0001.0001.0001.0000.0000.7100.240
addr1.0001.0001.0001.0000.0000.7100.240
tel_no0.2471.0001.0001.0000.0000.8220.000
entrn_flag_nm0.0000.0000.0000.0001.0000.0000.009
entrn_nmpr_co0.1730.7100.7100.8220.0001.0000.000
entrn_de0.0000.2400.2400.0000.0090.0001.000
2023-12-10T18:55:41.040161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
entrn_flag_nmtrrsrt_nmaddrcl_nm
entrn_flag_nm1.0000.0000.0000.000
trrsrt_nm0.0001.0001.0000.974
addr0.0001.0001.0000.974
cl_nm0.0000.9740.9741.000
2023-12-10T18:55:41.395345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
tel_noentrn_nmpr_coentrn_decl_nmtrrsrt_nmaddrentrn_flag_nm
tel_no1.000-0.4810.0490.4110.9790.9790.000
entrn_nmpr_co-0.4811.000-0.3080.1640.4730.4730.000
entrn_de0.049-0.3081.0000.0000.1340.1340.000
cl_nm0.4110.1640.0001.0000.9740.9740.000
trrsrt_nm0.9790.4730.1340.9741.0001.0000.000
addr0.9790.4730.1340.9741.0001.0000.000
entrn_flag_nm0.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-10T18:55:34.917964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:55:35.216670image/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

cl_nmtrrsrt_nmaddrtel_noentrn_flag_nmentrn_nmpr_coentrn_de
0공연전시서복전시관제주 서귀포시 칠십리로 156-8 서복전시관647606361무료경로920230616
1자연천지연폭포제주 서귀포시 천지동 667-7647331528무료경로32820230628
2공연전시이중섭미술관제주 서귀포시 이중섭로 27-3647603567무료경로3320230601
3공연전시이중섭미술관제주 서귀포시 이중섭로 27-3647603567무료경로4320230602
4공연전시이중섭미술관제주 서귀포시 이중섭로 27-3647603567무료장애인4320230603
5공연전시이중섭미술관제주 서귀포시 이중섭로 27-3647603567무료장애인4720230604
6공연전시이중섭미술관제주 서귀포시 이중섭로 27-3647603567무료경로6720230606
7자연천지연폭포제주 서귀포시 천지동 667-7647331528무료장애인19820230629
8공연전시이중섭미술관제주 서귀포시 이중섭로 27-3647603567무료경로4720230608
9공연전시이중섭미술관제주 서귀포시 이중섭로 27-3647603567무료유아4120230609
cl_nmtrrsrt_nmaddrtel_noentrn_flag_nmentrn_nmpr_coentrn_de
90자연용머리해안제주 서귀포시 안덕면 사계리 112-3647606321무료장애인22220230616
91자연용머리해안제주 서귀포시 안덕면 사계리 112-3647606321무료경로10620230617
92자연용머리해안제주 서귀포시 안덕면 사계리 112-3647606321무료유아14420230622
93자연용머리해안제주 서귀포시 안덕면 사계리 112-3647606321무료경로25720230623
94자연용머리해안제주 서귀포시 안덕면 사계리 112-3647606321무료경로5820230624
95자연정방폭포제주 서귀포시 칠십리로214번길 37647331530무료장애인12620230601
96자연정방폭포제주 서귀포시 칠십리로214번길 37647331530무료장애인29420230602
97자연정방폭포제주 서귀포시 칠십리로214번길 37647331530무료경로28320230603
98자연정방폭포제주 서귀포시 칠십리로214번길 37647331530무료경로42920230604
99자연정방폭포제주 서귀포시 칠십리로214번길 37647331530무료경로31620230605