Overview

Dataset statistics

Number of variables4
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.2 KiB
Average record size in memory33.3 B

Variable types

Text1
Numeric1
Categorical2

Alerts

GAP_RISK_CN is highly overall correlated with GAP_XTN and 1 other fieldsHigh correlation
GAP_RISK_GRD_CD is highly overall correlated with GAP_XTN and 1 other fieldsHigh correlation
GAP_XTN is highly overall correlated with GAP_RISK_GRD_CD and 1 other fieldsHigh correlation
GEOM has unique valuesUnique

Reproduction

Analysis started2024-03-13 12:46:52.120081
Analysis finished2024-03-13 12:46:52.682743
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

GEOM
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-03-13T21:46:52.986192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length256
Median length255
Mean length188.994
Min length180

Characters and Unicode

Total characters94497
Distinct characters25
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique500 ?
Unique (%)100.0%

Sample

1st rowMULTIPOLYGON (((126.771284694686 34.3177177302285,126.771284057228 34.3177264505777,126.771293826504 34.3177264688197,126.771293850955 34.3177174540465,126.771285130226 34.3177174377624,126.771284694686 34.3177177302285)))
2nd rowMULTIPOLYGON (((126.771283398334 34.3177354641662,126.771293802053 34.3177354835929,126.771293826504 34.3177264688197,126.771284057228 34.3177264505777,126.771283398334 34.3177354641662)))
3rd rowMULTIPOLYGON (((126.771282919456 34.3177420151583,126.771282912775 34.3177444780784,126.771293777603 34.3177444983661,126.771293802053 34.3177354835929,126.771283398334 34.3177354641662,126.771282919456 34.3177420151583)))
4th rowMULTIPOLYGON (((126.771282912775 34.3177444780784,126.771282888323 34.3177534928516,126.771293753152 34.3177535131393,126.771293777603 34.3177444983661,126.771282912775 34.3177444780784)))
5th rowMULTIPOLYGON (((126.771282888323 34.3177534928516,126.771282863871 34.3177625076248,126.771293728701 34.3177625279125,126.771293753152 34.3177535131393,126.771282888323 34.3177534928516)))
ValueCountFrequency (%)
multipolygon 500
 
14.1%
34.3177629619102,126.771532754959 1
 
< 0.1%
34.3177359296795,126.771521963408 1
 
< 0.1%
34.3177359094129 1
 
< 0.1%
126.771521938981 1
 
< 0.1%
34.3177449241863,126.771521914555 1
 
< 0.1%
34.3177539389596,126.771532779384 1
 
< 0.1%
34.3177539592262,126.771532803809 1
 
< 0.1%
34.3177449444528,126.771521938981 1
 
< 0.1%
34.3177449241863 1
 
< 0.1%
Other values (3025) 3025
85.6%
2024-03-13T21:46:53.540786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 13461
14.2%
1 11661
12.3%
3 9801
10.4%
6 8226
8.7%
4 7411
7.8%
2 6568
 
7.0%
5 5662
 
6.0%
. 5068
 
5.4%
8 4620
 
4.9%
9 4419
 
4.7%
Other values (15) 17600
18.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75361
79.7%
Other Punctuation 7102
 
7.5%
Uppercase Letter 6000
 
6.3%
Space Separator 3034
 
3.2%
Close Punctuation 1500
 
1.6%
Open Punctuation 1500
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 13461
17.9%
1 11661
15.5%
3 9801
13.0%
6 8226
10.9%
4 7411
9.8%
2 6568
8.7%
5 5662
7.5%
8 4620
 
6.1%
9 4419
 
5.9%
0 3532
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
O 1000
16.7%
L 1000
16.7%
U 500
8.3%
N 500
8.3%
G 500
8.3%
Y 500
8.3%
P 500
8.3%
I 500
8.3%
T 500
8.3%
M 500
8.3%
Other Punctuation
ValueCountFrequency (%)
. 5068
71.4%
, 2034
28.6%
Space Separator
ValueCountFrequency (%)
3034
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1500
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1500
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 88497
93.7%
Latin 6000
 
6.3%

Most frequent character per script

Common
ValueCountFrequency (%)
7 13461
15.2%
1 11661
13.2%
3 9801
11.1%
6 8226
9.3%
4 7411
8.4%
2 6568
7.4%
5 5662
6.4%
. 5068
 
5.7%
8 4620
 
5.2%
9 4419
 
5.0%
Other values (5) 11600
13.1%
Latin
ValueCountFrequency (%)
O 1000
16.7%
L 1000
16.7%
U 500
8.3%
N 500
8.3%
G 500
8.3%
Y 500
8.3%
P 500
8.3%
I 500
8.3%
T 500
8.3%
M 500
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 94497
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 13461
14.2%
1 11661
12.3%
3 9801
10.4%
6 8226
8.7%
4 7411
7.8%
2 6568
 
7.0%
5 5662
 
6.0%
. 5068
 
5.4%
8 4620
 
4.9%
9 4419
 
4.7%
Other values (15) 17600
18.6%

GAP_XTN
Real number (ℝ)

HIGH CORRELATION 

Distinct296
Distinct (%)59.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.20033
Minimum0
Maximum0.829
Zeros5
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-03-13T21:46:53.758489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.02
Q10.10075
median0.1735
Q30.27225
95-th percentile0.47715
Maximum0.829
Range0.829
Interquartile range (IQR)0.1715

Descriptive statistics

Standard deviation0.13858118
Coefficient of variation (CV)0.69176447
Kurtosis1.1725109
Mean0.20033
Median Absolute Deviation (MAD)0.0825
Skewness1.0446231
Sum100.165
Variance0.019204743
MonotonicityNot monotonic
2024-03-13T21:46:54.001288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.167 7
 
1.4%
0.02 5
 
1.0%
0.147 5
 
1.0%
0.1 5
 
1.0%
0.119 5
 
1.0%
0.183 5
 
1.0%
0.009 5
 
1.0%
0.0 5
 
1.0%
0.237 5
 
1.0%
0.12 4
 
0.8%
Other values (286) 449
89.8%
ValueCountFrequency (%)
0.0 5
1.0%
0.002 1
 
0.2%
0.004 1
 
0.2%
0.005 3
0.6%
0.006 1
 
0.2%
0.007 3
0.6%
0.008 1
 
0.2%
0.009 5
1.0%
0.011 1
 
0.2%
0.015 1
 
0.2%
ValueCountFrequency (%)
0.829 1
0.2%
0.716 1
0.2%
0.637 1
0.2%
0.611 1
0.2%
0.602 1
0.2%
0.6 1
0.2%
0.594 1
0.2%
0.578 1
0.2%
0.569 1
0.2%
0.56 1
0.2%

GAP_RISK_GRD_CD
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
C
275 
B
120 
D
81 
E
 
19
A
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowB
2nd rowB
3rd rowD
4th rowC
5th rowB

Common Values

ValueCountFrequency (%)
C 275
55.0%
B 120
24.0%
D 81
 
16.2%
E 19
 
3.8%
A 5
 
1.0%

Length

2024-03-13T21:46:54.249913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:46:54.413647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
c 275
55.0%
b 120
24.0%
d 81
 
16.2%
e 19
 
3.8%
a 5
 
1.0%

GAP_RISK_CN
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
주의
275 
보통
120 
위험
81 
매우위험
 
19
안전
 
5

Length

Max length4
Median length2
Mean length2.076
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row보통
2nd row보통
3rd row위험
4th row주의
5th row보통

Common Values

ValueCountFrequency (%)
주의 275
55.0%
보통 120
24.0%
위험 81
 
16.2%
매우위험 19
 
3.8%
안전 5
 
1.0%

Length

2024-03-13T21:46:54.619014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:46:54.830355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주의 275
55.0%
보통 120
24.0%
위험 81
 
16.2%
매우위험 19
 
3.8%
안전 5
 
1.0%

Interactions

2024-03-13T21:46:52.312911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:46:54.968322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
GAP_XTNGAP_RISK_GRD_CDGAP_RISK_CN
GAP_XTN1.0000.9760.976
GAP_RISK_GRD_CD0.9761.0001.000
GAP_RISK_CN0.9761.0001.000
2024-03-13T21:46:55.152356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
GAP_RISK_CNGAP_RISK_GRD_CD
GAP_RISK_CN1.0001.000
GAP_RISK_GRD_CD1.0001.000
2024-03-13T21:46:55.285253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
GAP_XTNGAP_RISK_GRD_CDGAP_RISK_CN
GAP_XTN1.0000.7790.779
GAP_RISK_GRD_CD0.7791.0001.000
GAP_RISK_CN0.7791.0001.000

Missing values

2024-03-13T21:46:52.477606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:46:52.627941image/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

GEOMGAP_XTNGAP_RISK_GRD_CDGAP_RISK_CN
0MULTIPOLYGON (((126.771284694686 34.3177177302285,126.771284057228 34.3177264505777,126.771293826504 34.3177264688197,126.771293850955 34.3177174540465,126.771285130226 34.3177174377624,126.771284694686 34.3177177302285)))0.02B보통
1MULTIPOLYGON (((126.771283398334 34.3177354641662,126.771293802053 34.3177354835929,126.771293826504 34.3177264688197,126.771284057228 34.3177264505777,126.771283398334 34.3177354641662)))0.031B보통
2MULTIPOLYGON (((126.771282919456 34.3177420151583,126.771282912775 34.3177444780784,126.771293777603 34.3177444983661,126.771293802053 34.3177354835929,126.771283398334 34.3177354641662,126.771282919456 34.3177420151583)))0.308D위험
3MULTIPOLYGON (((126.771282912775 34.3177444780784,126.771282888323 34.3177534928516,126.771293753152 34.3177535131393,126.771293777603 34.3177444983661,126.771282912775 34.3177444780784)))0.222C주의
4MULTIPOLYGON (((126.771282888323 34.3177534928516,126.771282863871 34.3177625076248,126.771293728701 34.3177625279125,126.771293753152 34.3177535131393,126.771282888323 34.3177534928516)))0.083B보통
5MULTIPOLYGON (((126.771282863871 34.3177625076248,126.771282839419 34.3177715223979,126.77129370425 34.3177715426857,126.771293728701 34.3177625279125,126.771282863871 34.3177625076248)))0.215C주의
6MULTIPOLYGON (((126.771293683983 34.3177790150018,126.77129370425 34.3177715426857,126.771282839419 34.3177715223979,126.771282823736 34.317777304444,126.771293683983 34.3177790150018)))0.237C주의
7MULTIPOLYGON (((126.771293866911 34.3177115710487,126.771293850955 34.3177174540465,126.771304715779 34.3177174743332,126.771304740228 34.3177084595599,126.771298517828 34.3177084479416,126.771293866911 34.3177115710487)))0.21C주의
8MULTIPOLYGON (((126.771293850955 34.3177174540465,126.771293826504 34.3177264688197,126.771304691329 34.3177264891065,126.771304715779 34.3177174743332,126.771293850955 34.3177174540465)))0.071B보통
9MULTIPOLYGON (((126.771293826504 34.3177264688197,126.771293802053 34.3177354835929,126.77130466688 34.3177355038797,126.771304691329 34.3177264891065,126.771293826504 34.3177264688197)))0.065B보통
GEOMGAP_XTNGAP_RISK_GRD_CDGAP_RISK_CN
490MULTIPOLYGON (((126.771597724175 34.3178442285385,126.771597699756 34.3178532433117,126.771608564598 34.3178532635716,126.771608589015 34.3178442487984,126.771597724175 34.3178442285385)))0.569E매우위험
491MULTIPOLYGON (((126.771597699756 34.3178532433117,126.771597675338 34.317862258085,126.771608540181 34.3178622783448,126.771608564598 34.3178532635716,126.771597699756 34.3178532433117)))0.169C주의
492MULTIPOLYGON (((126.771597675338 34.317862258085,126.77159765092 34.3178712728582,126.771608515764 34.3178712931181,126.771608540181 34.3178622783448,126.771597675338 34.317862258085)))0.107C주의
493MULTIPOLYGON (((126.77159765092 34.3178712728582,126.771597626501 34.3178802876314,126.771608491346 34.3178803078913,126.771608515764 34.3178712931181,126.77159765092 34.3178712728582)))0.129C주의
494MULTIPOLYGON (((126.771597626501 34.3178802876314,126.771597602083 34.3178893024046,126.771608466929 34.3178893226645,126.771608491346 34.3178803078913,126.771597626501 34.3178802876314)))0.168C주의
495MULTIPOLYGON (((126.771602039269 34.3178983254975,126.771608442512 34.3178983374377,126.771608466929 34.3178893226645,126.771597602083 34.3178893024046,126.77159759913 34.3178903926921,126.771602039269 34.3178983254975)))0.096B보통
496MULTIPOLYGON (((126.771619141043 34.3176459424573,126.77160912619 34.3176459237834,126.771609101773 34.3176549385569,126.771619966589 34.3176549588157,126.771619985623 34.3176479310464,126.771619141043 34.3176459424573)))0.361D위험
497MULTIPOLYGON (((126.771609101773 34.3176549385569,126.771609077356 34.3176639533305,126.771619942173 34.3176639735893,126.771619966589 34.3176549588157,126.771609101773 34.3176549385569)))0.484D위험
498MULTIPOLYGON (((126.771609077356 34.3176639533305,126.771609052939 34.317672968104,126.771619917758 34.3176729883628,126.771619942173 34.3176639735893,126.771609077356 34.3176639533305)))0.829E매우위험
499MULTIPOLYGON (((126.771609052939 34.317672968104,126.771609028522 34.3176819828775,126.771619893342 34.3176820031363,126.771619917758 34.3176729883628,126.771609052939 34.317672968104)))0.216C주의