Overview

Dataset statistics

Number of variables7
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 KiB
Average record size in memory61.3 B

Variable types

Categorical4
Numeric3

Alerts

cl_nm is highly overall correlated with tot_entrn_nmpr_co and 4 other fieldsHigh correlation
trrsrt_nm is highly overall correlated with tot_entrn_nmpr_co and 4 other fieldsHigh correlation
tel_no is highly overall correlated with tot_entrn_nmpr_co and 4 other fieldsHigh correlation
addr is highly overall correlated with tot_entrn_nmpr_co and 4 other fieldsHigh correlation
tot_entrn_nmpr_co is highly overall correlated with cl_nm and 3 other fieldsHigh correlation
setle_price is highly overall correlated with cl_nm and 3 other fieldsHigh correlation
cl_nm is highly imbalanced (80.6%)Imbalance
setle_price has 36 (36.0%) zerosZeros

Reproduction

Analysis started2023-12-10 10:18:03.918829
Analysis finished2023-12-10 10:18:05.938639
Duration2.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

cl_nm
Categorical

HIGH CORRELATION  IMBALANCE 

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

Length

Max length4
Median length4
Mean length3.94
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공연전시 97
97.0%
자연 3
 
3.0%

Length

2023-12-10T19:18:06.063830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:18:06.227164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공연전시 97
97.0%
자연 3
 
3.0%

trrsrt_nm
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
감귤박물관
29 
서귀포천문과학문화관
26 
기당미술관
25 
서복전시관
17 
천지연폭포
3 

Length

Max length10
Median length5
Mean length6.3
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row감귤박물관
2nd row천지연폭포
3rd row감귤박물관
4th row감귤박물관
5th row감귤박물관

Common Values

ValueCountFrequency (%)
감귤박물관 29
29.0%
서귀포천문과학문화관 26
26.0%
기당미술관 25
25.0%
서복전시관 17
17.0%
천지연폭포 3
 
3.0%

Length

2023-12-10T19:18:06.408206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:18:06.569155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
감귤박물관 29
29.0%
서귀포천문과학문화관 26
26.0%
기당미술관 25
25.0%
서복전시관 17
17.0%
천지연폭포 3
 
3.0%

addr
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
제주 서귀포시 효돈순환로 441
29 
제주 서귀포시 1100로 506-1 천문과학문화관
26 
제주 서귀포시 남성중로153번길 15
25 
제주 서귀포시 칠십리로 156-8 서복전시관
17 
제주 서귀포시 천지동 667-7
3 

Length

Max length27
Median length24
Mean length21.54
Min length17

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제주 서귀포시 효돈순환로 441
2nd row제주 서귀포시 천지동 667-7
3rd row제주 서귀포시 효돈순환로 441
4th row제주 서귀포시 효돈순환로 441
5th row제주 서귀포시 효돈순환로 441

Common Values

ValueCountFrequency (%)
제주 서귀포시 효돈순환로 441 29
29.0%
제주 서귀포시 1100로 506-1 천문과학문화관 26
26.0%
제주 서귀포시 남성중로153번길 15 25
25.0%
제주 서귀포시 칠십리로 156-8 서복전시관 17
17.0%
제주 서귀포시 천지동 667-7 3
 
3.0%

Length

2023-12-10T19:18:06.760267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:18:06.944186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주 100
22.6%
서귀포시 100
22.6%
효돈순환로 29
 
6.5%
441 29
 
6.5%
1100로 26
 
5.9%
506-1 26
 
5.9%
천문과학문화관 26
 
5.9%
남성중로153번길 25
 
5.6%
15 25
 
5.6%
칠십리로 17
 
3.8%
Other values (4) 40
 
9.0%

tel_no
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
647673010
29 
647399701
26 
647331586
25 
647606361
17 
647331528
3 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row647673010
2nd row647331528
3rd row647673010
4th row647673010
5th row647673010

Common Values

ValueCountFrequency (%)
647673010 29
29.0%
647399701 26
26.0%
647331586 25
25.0%
647606361 17
17.0%
647331528 3
 
3.0%

Length

2023-12-10T19:18:07.134741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:18:07.300498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
647673010 29
29.0%
647399701 26
26.0%
647331586 25
25.0%
647606361 17
17.0%
647331528 3
 
3.0%

tot_entrn_nmpr_co
Real number (ℝ)

HIGH CORRELATION 

Distinct76
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean204.4
Minimum6
Maximum3856
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:18:07.565137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile21
Q148.75
median73
Q3155.5
95-th percentile304.35
Maximum3856
Range3850
Interquartile range (IQR)106.75

Descriptive statistics

Standard deviation567.20052
Coefficient of variation (CV)2.7749536
Kurtosis31.655253
Mean204.4
Median Absolute Deviation (MAD)35
Skewness5.5499292
Sum20440
Variance321716.42
MonotonicityNot monotonic
2023-12-10T19:18:07.917985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51 3
 
3.0%
97 3
 
3.0%
62 3
 
3.0%
30 3
 
3.0%
73 3
 
3.0%
219 2
 
2.0%
195 2
 
2.0%
21 2
 
2.0%
66 2
 
2.0%
88 2
 
2.0%
Other values (66) 75
75.0%
ValueCountFrequency (%)
6 1
 
1.0%
7 1
 
1.0%
15 1
 
1.0%
20 1
 
1.0%
21 2
2.0%
24 1
 
1.0%
25 1
 
1.0%
26 1
 
1.0%
28 1
 
1.0%
30 3
3.0%
ValueCountFrequency (%)
3856 1
1.0%
3648 1
1.0%
2185 1
1.0%
1265 1
1.0%
368 1
1.0%
301 1
1.0%
261 1
1.0%
259 1
1.0%
255 1
1.0%
242 1
1.0%

setle_price
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct63
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean164560
Minimum0
Maximum5504600
Zeros36
Zeros (%)36.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:18:08.197490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median23225
Q344450
95-th percentile119575
Maximum5504600
Range5504600
Interquartile range (IQR)44450

Descriptive statistics

Standard deviation785119.74
Coefficient of variation (CV)4.7710242
Kurtosis35.866539
Mean164560
Median Absolute Deviation (MAD)23225
Skewness5.99194
Sum16456000
Variance6.16413 × 1011
MonotonicityNot monotonic
2023-12-10T19:18:08.440918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36
36.0%
97500 2
 
2.0%
17500 2
 
2.0%
21100 1
 
1.0%
113000 1
 
1.0%
110000 1
 
1.0%
39000 1
 
1.0%
88500 1
 
1.0%
88000 1
 
1.0%
83500 1
 
1.0%
Other values (53) 53
53.0%
ValueCountFrequency (%)
0 36
36.0%
8000 1
 
1.0%
10000 1
 
1.0%
12750 1
 
1.0%
13500 1
 
1.0%
16750 1
 
1.0%
17500 2
 
2.0%
19300 1
 
1.0%
19750 1
 
1.0%
20250 1
 
1.0%
ValueCountFrequency (%)
5504600 1
1.0%
4883600 1
1.0%
3059200 1
1.0%
132500 1
1.0%
121000 1
1.0%
119500 1
1.0%
119000 1
1.0%
113000 1
1.0%
111500 1
1.0%
110500 1
1.0%

entrn_de
Real number (ℝ)

Distinct31
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20220516
Minimum20220501
Maximum20220531
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:18:08.671688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20220501
5-th percentile20220503
Q120220508
median20220515
Q320220523
95-th percentile20220530
Maximum20220531
Range30
Interquartile range (IQR)15.25

Descriptive statistics

Standard deviation8.8705619
Coefficient of variation (CV)4.3869118 × 10-7
Kurtosis-1.1556668
Mean20220516
Median Absolute Deviation (MAD)7.5
Skewness0.1462264
Sum2.0220516 × 109
Variance78.686869
MonotonicityNot monotonic
2023-12-10T19:18:08.902317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20220517 4
 
4.0%
20220531 4
 
4.0%
20220529 4
 
4.0%
20220515 4
 
4.0%
20220514 4
 
4.0%
20220513 4
 
4.0%
20220512 4
 
4.0%
20220510 4
 
4.0%
20220511 4
 
4.0%
20220507 4
 
4.0%
Other values (21) 60
60.0%
ValueCountFrequency (%)
20220501 3
3.0%
20220502 1
 
1.0%
20220503 4
4.0%
20220504 4
4.0%
20220505 4
4.0%
20220506 4
4.0%
20220507 4
4.0%
20220508 3
3.0%
20220509 2
2.0%
20220510 4
4.0%
ValueCountFrequency (%)
20220531 4
4.0%
20220530 2
2.0%
20220529 4
4.0%
20220528 3
3.0%
20220527 3
3.0%
20220526 3
3.0%
20220525 3
3.0%
20220524 3
3.0%
20220523 1
 
1.0%
20220522 3
3.0%

Interactions

2023-12-10T19:18:05.241550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:18:04.400222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:18:04.841124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:18:05.378187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:18:04.543716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:18:04.975716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:18:05.532914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:18:04.681511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:18:05.105082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:18:09.042177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
cl_nmtrrsrt_nmaddrtel_notot_entrn_nmpr_cosetle_priceentrn_de
cl_nm1.0001.0001.0001.0001.0001.0000.584
trrsrt_nm1.0001.0001.0001.0000.6310.6240.253
addr1.0001.0001.0001.0000.6310.6240.253
tel_no1.0001.0001.0001.0000.6310.6240.253
tot_entrn_nmpr_co1.0000.6310.6310.6311.0000.9810.268
setle_price1.0000.6240.6240.6240.9811.0000.000
entrn_de0.5840.2530.2530.2530.2680.0001.000
2023-12-10T19:18:09.552037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
cl_nmtrrsrt_nmtel_noaddr
cl_nm1.0000.9850.9850.985
trrsrt_nm0.9851.0001.0001.000
tel_no0.9851.0001.0001.000
addr0.9851.0001.0001.000
2023-12-10T19:18:09.708151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
tot_entrn_nmpr_cosetle_priceentrn_decl_nmtrrsrt_nmaddrtel_no
tot_entrn_nmpr_co1.000-0.2430.1040.9900.5570.5570.557
setle_price-0.2431.0000.1250.9900.5500.5500.550
entrn_de0.1040.1251.0000.4350.1140.1140.114
cl_nm0.9900.9900.4351.0000.9850.9850.985
trrsrt_nm0.5570.5500.1140.9851.0001.0001.000
addr0.5570.5500.1140.9851.0001.0001.000
tel_no0.5570.5500.1140.9851.0001.0001.000

Missing values

2023-12-10T19:18:05.696800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:18:05.864808image/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_notot_entrn_nmpr_cosetle_priceentrn_de
0공연전시감귤박물관제주 서귀포시 효돈순환로 441647673010147020220501
1자연천지연폭포제주 서귀포시 천지동 667-76473315282185305920020220529
2공연전시감귤박물관제주 서귀포시 효돈순환로 44164767301097020220503
3공연전시감귤박물관제주 서귀포시 효돈순환로 441647673010117020220504
4공연전시감귤박물관제주 서귀포시 효돈순환로 4416476730101265020220505
5공연전시감귤박물관제주 서귀포시 효돈순환로 441647673010216020220506
6공연전시감귤박물관제주 서귀포시 효돈순환로 441647673010239020220507
7자연천지연폭포제주 서귀포시 천지동 667-76473315283856550460020220530
8공연전시감귤박물관제주 서귀포시 효돈순환로 441647673010154020220509
9공연전시감귤박물관제주 서귀포시 효돈순환로 441647673010213020220510
cl_nmtrrsrt_nmaddrtel_notot_entrn_nmpr_cosetle_priceentrn_de
90공연전시서복전시관제주 서귀포시 칠십리로 156-8 서복전시관647606361692070020220508
91공연전시서복전시관제주 서귀포시 칠십리로 156-8 서복전시관647606361652450020220509
92공연전시서복전시관제주 서귀포시 칠십리로 156-8 서복전시관647606361993315020220510
93공연전시서복전시관제주 서귀포시 칠십리로 156-8 서복전시관647606361823005020220511
94공연전시서복전시관제주 서귀포시 칠십리로 156-8 서복전시관647606361923260020220512
95공연전시서복전시관제주 서귀포시 칠십리로 156-8 서복전시관647606361732655020220513
96공연전시서복전시관제주 서귀포시 칠십리로 156-8 서복전시관647606361882835020220514
97공연전시서복전시관제주 서귀포시 칠십리로 156-8 서복전시관647606361892870020220515
98공연전시서복전시관제주 서귀포시 칠십리로 156-8 서복전시관647606361672280020220516
99공연전시서복전시관제주 서귀포시 칠십리로 156-8 서복전시관647606361973590020220517