Overview

Dataset statistics

Number of variables5
Number of observations79
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory44.7 B

Variable types

Numeric3
Categorical1
Text1

Dataset

Description순번,명칭,SHAPE,X좌표,Y좌표
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-11985/S/1/datasetView.do

Alerts

X좌표 is highly overall correlated with Y좌표 and 1 other fieldsHigh correlation
Y좌표 is highly overall correlated with X좌표 and 1 other fieldsHigh correlation
명칭 is highly overall correlated with X좌표 and 1 other fieldsHigh correlation
명칭 is highly imbalanced (66.9%)Imbalance
순번 has unique valuesUnique
SHAPE has unique valuesUnique
X좌표 has unique valuesUnique
Y좌표 has unique valuesUnique

Reproduction

Analysis started2023-12-11 09:12:25.530503
Analysis finished2023-12-11 09:12:26.754866
Duration1.22 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40
Minimum1
Maximum79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2023-12-11T18:12:26.840121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.9
Q120.5
median40
Q359.5
95-th percentile75.1
Maximum79
Range78
Interquartile range (IQR)39

Descriptive statistics

Standard deviation22.949219
Coefficient of variation (CV)0.57373048
Kurtosis-1.2
Mean40
Median Absolute Deviation (MAD)20
Skewness0
Sum3160
Variance526.66667
MonotonicityNot monotonic
2023-12-11T18:12:26.985769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 1
 
1.3%
31 1
 
1.3%
42 1
 
1.3%
75 1
 
1.3%
73 1
 
1.3%
72 1
 
1.3%
69 1
 
1.3%
68 1
 
1.3%
66 1
 
1.3%
65 1
 
1.3%
Other values (69) 69
87.3%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
79 1
1.3%
78 1
1.3%
77 1
1.3%
76 1
1.3%
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%

명칭
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size764.0 B
탐방가능구간
67 
제목 없는 경로
8 
광나루~올림픽공원역
 
1
Placemark
 
1
올림픽공원역~수서역
 
1

Length

Max length10
Median length6
Mean length6.3164557
Min length4

Unique

Unique4 ?
Unique (%)5.1%

Sample

1st row탐방가능구간
2nd row탐방가능구간
3rd row탐방가능구간
4th row탐방가능구간
5th row제목 없는 경로

Common Values

ValueCountFrequency (%)
탐방가능구간 67
84.8%
제목 없는 경로 8
 
10.1%
광나루~올림픽공원역 1
 
1.3%
Placemark 1
 
1.3%
올림픽공원역~수서역 1
 
1.3%
보조구간 1
 
1.3%

Length

2023-12-11T18:12:27.153681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:12:27.300515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
탐방가능구간 67
70.5%
제목 8
 
8.4%
없는 8
 
8.4%
경로 8
 
8.4%
광나루~올림픽공원역 1
 
1.1%
placemark 1
 
1.1%
올림픽공원역~수서역 1
 
1.1%
보조구간 1
 
1.1%

SHAPE
Text

UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size764.0 B
2023-12-11T18:12:27.604177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.860759
Min length10

Characters and Unicode

Total characters858
Distinct characters19
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)100.0%

Sample

1st row[B@17af119b
2nd row[B@66ace342
3rd row[B@607c36b7
4th row[B@7aec59dd
5th row[B@32fffb37
ValueCountFrequency (%)
b@17af119b 1
 
1.3%
b@5229b004 1
 
1.3%
b@35186545 1
 
1.3%
b@2f060881 1
 
1.3%
b@7b5c6ab 1
 
1.3%
b@57f2d5d9 1
 
1.3%
b@6afc4476 1
 
1.3%
b@3c0ad45d 1
 
1.3%
b@23e3bb03 1
 
1.3%
b@4a1d6bc9 1
 
1.3%
Other values (69) 69
87.3%
2023-12-11T18:12:28.046556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
[ 79
 
9.2%
B 79
 
9.2%
@ 79
 
9.2%
0 49
 
5.7%
1 44
 
5.1%
7 42
 
4.9%
9 41
 
4.8%
2 40
 
4.7%
3 40
 
4.7%
6 40
 
4.7%
Other values (9) 325
37.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 408
47.6%
Lowercase Letter 213
24.8%
Open Punctuation 79
 
9.2%
Uppercase Letter 79
 
9.2%
Other Punctuation 79
 
9.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 49
12.0%
1 44
10.8%
7 42
10.3%
9 41
10.0%
2 40
9.8%
3 40
9.8%
6 40
9.8%
5 38
9.3%
4 38
9.3%
8 36
8.8%
Lowercase Letter
ValueCountFrequency (%)
f 40
18.8%
a 39
18.3%
d 36
16.9%
c 33
15.5%
e 33
15.5%
b 32
15.0%
Open Punctuation
ValueCountFrequency (%)
[ 79
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 79
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 79
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 566
66.0%
Latin 292
34.0%

Most frequent character per script

Common
ValueCountFrequency (%)
[ 79
14.0%
@ 79
14.0%
0 49
8.7%
1 44
7.8%
7 42
7.4%
9 41
7.2%
2 40
7.1%
3 40
7.1%
6 40
7.1%
5 38
6.7%
Other values (2) 74
13.1%
Latin
ValueCountFrequency (%)
B 79
27.1%
f 40
13.7%
a 39
13.4%
d 36
12.3%
c 33
11.3%
e 33
11.3%
b 32
11.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 858
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
[ 79
 
9.2%
B 79
 
9.2%
@ 79
 
9.2%
0 49
 
5.7%
1 44
 
5.1%
7 42
 
4.9%
9 41
 
4.8%
2 40
 
4.7%
3 40
 
4.7%
6 40
 
4.7%
Other values (9) 325
37.9%

X좌표
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean200142.46
Minimum189291.15
Maximum212019.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2023-12-11T18:12:28.230346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189291.15
5-th percentile194347.7
Q1198764.88
median200542.73
Q3201078.36
95-th percentile206253.02
Maximum212019.28
Range22728.134
Interquartile range (IQR)2313.4815

Descriptive statistics

Standard deviation3660.9046
Coefficient of variation (CV)0.018291494
Kurtosis2.442062
Mean200142.46
Median Absolute Deviation (MAD)1592.084
Skewness0.22682767
Sum15811255
Variance13402222
MonotonicityNot monotonic
2023-12-11T18:12:28.418480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200715.339 1
 
1.3%
199231.614 1
 
1.3%
200854.874 1
 
1.3%
195759.661 1
 
1.3%
200756.847 1
 
1.3%
200152.911 1
 
1.3%
198968.971 1
 
1.3%
198957.632 1
 
1.3%
206126.134 1
 
1.3%
203817.406 1
 
1.3%
Other values (69) 69
87.3%
ValueCountFrequency (%)
189291.146 1
1.3%
190908.404 1
1.3%
194303.314 1
1.3%
194329.026 1
1.3%
194349.778 1
1.3%
194649.175 1
1.3%
194807.316 1
1.3%
194892.372 1
1.3%
195531.682 1
1.3%
195706.776 1
1.3%
ValueCountFrequency (%)
212019.28 1
1.3%
210779.142 1
1.3%
208812.83 1
1.3%
207395.023 1
1.3%
206126.134 1
1.3%
203817.406 1
1.3%
203724.923 1
1.3%
203373.637 1
1.3%
202901.442 1
1.3%
202856.807 1
1.3%

Y좌표
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean458802.26
Minimum439522.66
Maximum465384.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2023-12-11T18:12:28.602274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439522.66
5-th percentile448320.74
Q1457201.7
median459223.88
Q3461702.84
95-th percentile464769.03
Maximum465384.75
Range25862.09
Interquartile range (IQR)4501.139

Descriptive statistics

Standard deviation4863.8344
Coefficient of variation (CV)0.010601156
Kurtosis5.3859021
Mean458802.26
Median Absolute Deviation (MAD)2060.273
Skewness-1.9534157
Sum36245378
Variance23656885
MonotonicityNot monotonic
2023-12-11T18:12:29.062766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
459320.935 1
 
1.3%
457308.657 1
 
1.3%
458231.826 1
 
1.3%
456602.531 1
 
1.3%
459179.559 1
 
1.3%
460386.862 1
 
1.3%
457181.854 1
 
1.3%
457142.066 1
 
1.3%
461735.442 1
 
1.3%
465384.748 1
 
1.3%
Other values (69) 69
87.3%
ValueCountFrequency (%)
439522.658 1
1.3%
441604.847 1
1.3%
443901.934 1
1.3%
444427.619 1
1.3%
448753.313 1
1.3%
453714.731 1
1.3%
455508.971 1
1.3%
456491.069 1
1.3%
456554.326 1
1.3%
456602.531 1
1.3%
ValueCountFrequency (%)
465384.748 1
1.3%
465220.039 1
1.3%
465102.88 1
1.3%
464967.918 1
1.3%
464746.932 1
1.3%
464546.247 1
1.3%
464460.938 1
1.3%
464247.785 1
1.3%
463945.696 1
1.3%
463873.89 1
1.3%

Interactions

2023-12-11T18:12:26.310765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:12:25.708381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:12:26.013617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:12:26.425787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:12:25.828000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:12:26.108765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:12:26.507472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:12:25.921299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:12:26.195224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T18:12:29.192583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번명칭SHAPEX좌표Y좌표
순번1.0000.0671.0000.2730.309
명칭0.0671.0001.0000.8300.773
SHAPE1.0001.0001.0001.0001.000
X좌표0.2730.8301.0001.0000.833
Y좌표0.3090.7731.0000.8331.000
2023-12-11T18:12:29.322908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번X좌표Y좌표명칭
순번1.0000.2400.2270.000
X좌표0.2401.0000.5890.590
Y좌표0.2270.5891.0000.579
명칭0.0000.5900.5791.000

Missing values

2023-12-11T18:12:26.612002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T18:12:26.720126image/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

순번명칭SHAPEX좌표Y좌표
028탐방가능구간[B@17af119b200715.339459320.935
131탐방가능구간[B@66ace342199231.614457308.657
232탐방가능구간[B@607c36b7202651.647464967.918
34탐방가능구간[B@7aec59dd199534.923457335.856
410제목 없는 경로[B@32fffb37190908.404455508.971
511탐방가능구간[B@43c5f209198024.286457498.197
612탐방가능구간[B@78954fa1198318.428457221.545
713탐방가능구간[B@129f10e0200739.216461335.983
814탐방가능구간[B@90cebad202901.442465102.88
915탐방가능구간[B@2f44af7f198705.984457170.071
순번명칭SHAPEX좌표Y좌표
6967탐방가능구간[B@4bd5e8c9200823.182459015.37
7070보조구간[B@48a60b04207395.023463873.89
7171탐방가능구간[B@d1d58df200247.693460665.444
7274탐방가능구간[B@1b59f33198823.776457144.329
7377탐방가능구간[B@3ae6ce25202627.914464460.938
7433탐방가능구간[B@6e7fd59200272.559460610.825
7534탐방가능구간[B@68a9e199200146.691460315.417
7636탐방가능구간[B@691a397d198494.695457000.37
7737탐방가능구간[B@38b47373200751.032458723.801
7879탐방가능구간[B@4f07a01a200561.431459520.409