Overview

Dataset statistics

Number of variables8
Number of observations684
Missing cells63
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory44.2 KiB
Average record size in memory66.2 B

Variable types

Text1
Categorical6
Numeric1

Alerts

STEEP_CLLN_ID has constant value ""Constant
SE_NM has constant value ""Constant
SGG_NM has constant value ""Constant
SPOT_NM has constant value ""Constant
STA_NM has constant value ""Constant
GRDNT_VAL is highly overall correlated with SLANT_GRD_CDHigh correlation
SLANT_GRD_CD is highly overall correlated with GRDNT_VALHigh correlation
GRDNT_VAL has 63 (9.2%) missing valuesMissing
GEOM has unique valuesUnique

Reproduction

Analysis started2024-03-13 12:49:31.122809
Analysis finished2024-03-13 12:49:31.940792
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

GEOM
Text

UNIQUE 

Distinct684
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
2024-03-13T21:49:32.129412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1024
Median length930
Mean length388.22222
Min length151

Characters and Unicode

Total characters265544
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

Unique684 ?
Unique (%)100.0%

Sample

1st rowMULTIPOLYGON (((129.324849410675 37.2810798983142,129.324851085854 37.2810831120484,129.324852875104 37.2810869909657,129.324852114342 37.2810622712174,129.324796366087 37.2810633666838,129.324849410675 37.2810798983142)))
2nd rowMULTIPOLYGON (((129.324882748421 37.2811517532753,129.324967553332 37.2811500867649,129.324966020397 37.2811002790735,129.324936033708 37.2810735762185,129.324888000114 37.2810814787168,129.324886597951 37.2810803825194,129.324861052027 37.2810620955873,129.324852114342 37.2810622712174,129.324852875104 37.2810869909657,129.324882748421 37.2811517532753)))
3rd rowMULTIPOLYGON (((129.324891951032 37.2811717035739,129.324970093918 37.2812326345124,129.324967553332 37.2811500867649,129.324882748421 37.2811517532753,129.324891951032 37.2811717035739)))
4th rowMULTIPOLYGON (((129.324923240163 37.2813311256425,129.324973095056 37.2813301459272,129.324971531795 37.2812793533187,129.324923240163 37.2813311256425)))
5th rowMULTIPOLYGON (((129.324897700128 37.2813585064777,129.324931671163 37.2813883143253,129.324974362041 37.2813713119736,129.324973095056 37.2813301459272,129.324923240163 37.2813311256425,129.324897700128 37.2813585064777)))
ValueCountFrequency (%)
multipolygon 684
 
7.7%
37.276 2
 
< 0.1%
37.28 2
 
< 0.1%
37.2841814099601,129.326238682183 1
 
< 0.1%
37.2841824189811,129.326197915872 1
 
< 0.1%
37.2841838319321,129.32620442979 1
 
< 0.1%
37.2841843362419,129.326207644975 1
 
< 0.1%
37.2841840739377,129.326210825083 1
 
< 0.1%
37.2841833682091,129.326215809931 1
 
< 0.1%
37.2841678449043,129.326243000148 1
 
< 0.1%
Other values (8177) 8177
92.2%
2024-03-13T21:49:32.688058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 37199
14.0%
3 30226
11.4%
7 25329
9.5%
9 24369
9.2%
1 23826
9.0%
8 20686
7.8%
6 16851
6.3%
4 16175
6.1%
5 15602
 
5.9%
. 15008
 
5.7%
Other values (15) 40273
15.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 223249
84.1%
Other Punctuation 21832
 
8.2%
Uppercase Letter 8208
 
3.1%
Space Separator 8188
 
3.1%
Open Punctuation 2122
 
0.8%
Close Punctuation 1945
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 37199
16.7%
3 30226
13.5%
7 25329
11.3%
9 24369
10.9%
1 23826
10.7%
8 20686
9.3%
6 16851
7.5%
4 16175
7.2%
5 15602
7.0%
0 12986
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
O 1368
16.7%
L 1368
16.7%
U 684
8.3%
N 684
8.3%
G 684
8.3%
Y 684
8.3%
P 684
8.3%
I 684
8.3%
T 684
8.3%
M 684
8.3%
Other Punctuation
ValueCountFrequency (%)
. 15008
68.7%
, 6824
31.3%
Space Separator
ValueCountFrequency (%)
8188
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2122
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1945
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 257336
96.9%
Latin 8208
 
3.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 37199
14.5%
3 30226
11.7%
7 25329
9.8%
9 24369
9.5%
1 23826
9.3%
8 20686
8.0%
6 16851
6.5%
4 16175
6.3%
5 15602
6.1%
. 15008
5.8%
Other values (5) 32065
12.5%
Latin
ValueCountFrequency (%)
O 1368
16.7%
L 1368
16.7%
U 684
8.3%
N 684
8.3%
G 684
8.3%
Y 684
8.3%
P 684
8.3%
I 684
8.3%
T 684
8.3%
M 684
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 265544
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 37199
14.0%
3 30226
11.4%
7 25329
9.5%
9 24369
9.2%
1 23826
9.0%
8 20686
7.8%
6 16851
6.3%
4 16175
6.1%
5 15602
 
5.9%
. 15008
 
5.7%
Other values (15) 40273
15.2%

STEEP_CLLN_ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
1
684 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 684
100.0%

Length

2024-03-13T21:49:32.908946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:49:33.061980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 684
100.0%

SE_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
갯바위
684 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
갯바위 684
100.0%

Length

2024-03-13T21:49:33.248714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:49:33.417324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
갯바위 684
100.0%

SGG_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
삼척시
684 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
삼척시 684
100.0%

Length

2024-03-13T21:49:33.683614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:49:33.872497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
삼척시 684
100.0%

SPOT_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
갈남리
684 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
갈남리 684
100.0%

Length

2024-03-13T21:49:34.051719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:49:34.213334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
갈남리 684
100.0%

STA_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
갈남해수욕장
684 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
갈남해수욕장 684
100.0%

Length

2024-03-13T21:49:34.383408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:49:34.531785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
갈남해수욕장 684
100.0%

GRDNT_VAL
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct596
Distinct (%)96.0%
Missing63
Missing (%)9.2%
Infinite0
Infinite (%)0.0%
Mean33.096167
Minimum3.14
Maximum77.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2024-03-13T21:49:34.712487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.14
5-th percentile8.89
Q119.63
median33.04
Q344.64
95-th percentile60.41
Maximum77.23
Range74.09
Interquartile range (IQR)25.01

Descriptive statistics

Standard deviation16.213249
Coefficient of variation (CV)0.48988296
Kurtosis-0.64378873
Mean33.096167
Median Absolute Deviation (MAD)12.61
Skewness0.24517553
Sum20552.72
Variance262.86943
MonotonicityNot monotonic
2024-03-13T21:49:34.991135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41.2 2
 
0.3%
38.11 2
 
0.3%
19.69 2
 
0.3%
69.71 2
 
0.3%
40.42 2
 
0.3%
41.83 2
 
0.3%
16.94 2
 
0.3%
36.82 2
 
0.3%
52.07 2
 
0.3%
36.62 2
 
0.3%
Other values (586) 601
87.9%
(Missing) 63
 
9.2%
ValueCountFrequency (%)
3.14 1
0.1%
4.4 1
0.1%
4.55 1
0.1%
4.66 1
0.1%
4.84 1
0.1%
4.94 1
0.1%
5.1 1
0.1%
5.42 1
0.1%
5.45 1
0.1%
5.57 1
0.1%
ValueCountFrequency (%)
77.23 1
0.1%
76.61 1
0.1%
76.21 1
0.1%
74.18 1
0.1%
74.13 1
0.1%
72.74 1
0.1%
71.21 1
0.1%
70.46 1
0.1%
69.71 2
0.3%
69.33 1
0.1%

SLANT_GRD_CD
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
B
241 
C
187 
A
159 
<NA>
63 
D
34 

Length

Max length4
Median length1
Mean length1.2763158
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowB
2nd rowB
3rd rowB
4th rowA
5th rowB

Common Values

ValueCountFrequency (%)
B 241
35.2%
C 187
27.3%
A 159
23.2%
<NA> 63
 
9.2%
D 34
 
5.0%

Length

2024-03-13T21:49:35.222625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:49:35.407891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
b 241
35.2%
c 187
27.3%
a 159
23.2%
na 63
 
9.2%
d 34
 
5.0%

Interactions

2024-03-13T21:49:31.516859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:49:35.543604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
GRDNT_VALSLANT_GRD_CD
GRDNT_VAL1.0000.981
SLANT_GRD_CD0.9811.000
2024-03-13T21:49:35.715413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
GRDNT_VALSLANT_GRD_CD
GRDNT_VAL1.0000.928
SLANT_GRD_CD0.9281.000

Missing values

2024-03-13T21:49:31.717231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:49:31.869858image/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

GEOMSTEEP_CLLN_IDSE_NMSGG_NMSPOT_NMSTA_NMGRDNT_VALSLANT_GRD_CD
0MULTIPOLYGON (((129.324849410675 37.2810798983142,129.324851085854 37.2810831120484,129.324852875104 37.2810869909657,129.324852114342 37.2810622712174,129.324796366087 37.2810633666838,129.324849410675 37.2810798983142)))1갯바위삼척시갈남리갈남해수욕장35.58B
1MULTIPOLYGON (((129.324882748421 37.2811517532753,129.324967553332 37.2811500867649,129.324966020397 37.2811002790735,129.324936033708 37.2810735762185,129.324888000114 37.2810814787168,129.324886597951 37.2810803825194,129.324861052027 37.2810620955873,129.324852114342 37.2810622712174,129.324852875104 37.2810869909657,129.324882748421 37.2811517532753)))1갯바위삼척시갈남리갈남해수욕장26.57B
2MULTIPOLYGON (((129.324891951032 37.2811717035739,129.324970093918 37.2812326345124,129.324967553332 37.2811500867649,129.324882748421 37.2811517532753,129.324891951032 37.2811717035739)))1갯바위삼척시갈남리갈남해수욕장36.28B
3MULTIPOLYGON (((129.324923240163 37.2813311256425,129.324973095056 37.2813301459272,129.324971531795 37.2812793533187,129.324923240163 37.2813311256425)))1갯바위삼척시갈남리갈남해수욕장14.6A
4MULTIPOLYGON (((129.324897700128 37.2813585064777,129.324931671163 37.2813883143253,129.324974362041 37.2813713119736,129.324973095056 37.2813301459272,129.324923240163 37.2813311256425,129.324897700128 37.2813585064777)))1갯바위삼척시갈남리갈남해수욕장22.05B
5MULTIPOLYGON (((129.325008386696 37.2811380058032,129.324966020397 37.2811002790735,129.324967553332 37.2811500867649,129.325020483952 37.2811490465887,129.325008386696 37.2811380058032)))1갯바위삼척시갈남리갈남해수욕장17.21A
6MULTIPOLYGON (((129.324979459032 37.281239936833,129.32508299259 37.2812379021894,129.325081985348 37.2812051769076,129.325020483952 37.2811490465887,129.324967553332 37.2811500867649,129.324970093918 37.2812326345124,129.324979459032 37.281239936833)))1갯바위삼척시갈남리갈남해수욕장24.2B
7MULTIPOLYGON (((129.324996155024 37.2812529552997,129.324971531795 37.2812793533187,129.324973095056 37.2813301459272,129.325085763593 37.2813279317626,129.32508299259 37.2812379021894,129.324979459032 37.281239936833,129.324996155024 37.2812529552997)))1갯바위삼척시갈남리갈남해수욕장20.56B
8MULTIPOLYGON (((129.325049725724 37.2813412970784,129.325087283331 37.2813773077285,129.325085763593 37.2813279317626,129.324973095056 37.2813301459272,129.324974362041 37.2813713119736,129.325049725724 37.2813412970784)))1갯바위삼척시갈남리갈남해수욕장25.03B
9MULTIPOLYGON (((129.325085301634 37.2812082035698,129.325081985348 37.2812051769076,129.32508299259 37.2812379021894,129.325117107549 37.2812372317416,129.325085301634 37.2812082035698)))1갯바위삼척시갈남리갈남해수욕장26.08B
GEOMSTEEP_CLLN_IDSE_NMSGG_NMSPOT_NMSTA_NMGRDNT_VALSLANT_GRD_CD
674MULTIPOLYGON (((129.321251644498 37.286068322895,129.32117847055 37.2860816461035,129.321173367737 37.2860832969916,129.321173546793 37.2860891232924,129.321286222728 37.2860869125048,129.321285658118 37.2860685415479,129.321251644498 37.286068322895)))1갯바위삼척시갈남리갈남해수욕장40.4C
675MULTIPOLYGON (((129.321173546793 37.2860891232924,129.321176313624 37.2861791530416,129.321288989693 37.2861769422468,129.321286222728 37.2860869125048,129.321173546793 37.2860891232924)))1갯바위삼척시갈남리갈남해수욕장35.32B
676MULTIPOLYGON (((129.321176313624 37.2861791530416,129.321179080467 37.2862691827893,129.32129175667 37.2862669719873,129.321288989693 37.2861769422468,129.321176313624 37.2861791530416)))1갯바위삼척시갈남리갈남해수욕장40.59C
677MULTIPOLYGON (((129.32118304187 37.2862818979004,129.321253741211 37.2863007814387,129.321279329093 37.2863128695202,129.321293445002 37.2863219054252,129.32129175667 37.2862669719873,129.321179080467 37.2862691827893,129.32117941078 37.2862799307418,129.32118304187 37.2862818979004)))1갯바위삼척시갈남리갈남해수욕장51.18C
678MULTIPOLYGON (((129.321336660369 37.2860814267528,129.321332686867 37.2860782220573,129.321327826569 37.2860755104056,129.321319035356 37.2860723002474,129.321297119694 37.2860686152252,129.321285658118 37.2860685415479,129.321286222728 37.2860869125048,129.32134029912 37.2860858514467,129.321336660369 37.2860814267528)))1갯바위삼척시갈남리갈남해수욕장31.55B
679MULTIPOLYGON (((129.321395356337 37.2861515756359,129.321351468117 37.2860992169654,129.321348481395 37.2860958010291,129.32134029912 37.2860858514467,129.321286222728 37.2860869125048,129.321288989693 37.2861769422468,129.321401665749 37.2861747313449,129.321401334384 37.2861639501501,129.321395356337 37.2861515756359)))1갯바위삼척시갈남리갈남해수욕장35.26B
680MULTIPOLYGON (((129.321403468535 37.2862333861727,129.321401665749 37.2861747313449,129.321288989693 37.2861769422468,129.32129175667 37.2862669719873,129.321389942915 37.286265045403,129.321403468535 37.2862333861727)))1갯바위삼척시갈남리갈남해수욕장39.8B
681MULTIPOLYGON (((129.321300780165 37.2863266008233,129.321302565067 37.2863274864598,129.321304086756 37.2863280250323,129.321305462864 37.2863282655807,129.321306813279 37.2863282571004,129.321322362797 37.2863239964054,129.321366016483 37.2862990603815,129.321372249487 37.286293831214,129.321384389371 37.286278044501,129.321389942915 37.286265045403,129.32129175667 37.2862669719873,129.321293445002 37.2863219054252,129.321300780165 37.2863266008233)))1갯바위삼척시갈남리갈남해수욕장43.11C
682MULTIPOLYGON (((129.321401334384 37.2861639501501,129.321401665749 37.2861747313449,129.321406496915 37.2861746365466,129.321401334384 37.2861639501501)))1갯바위삼척시갈남리갈남해수욕장<NA><NA>
683MULTIPOLYGON (((129.321416818721 37.2862021375525,129.32141726681 37.2862005396776,129.321417449549 37.2861988920583,129.321417336161 37.286197073685,129.321406496915 37.2861746365466,129.321401665749 37.2861747313449,129.321403468535 37.2862333861727,129.321416818721 37.2862021375525)))1갯바위삼척시갈남리갈남해수욕장27.34B