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,위도,경도
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-11986/S/1/datasetView.do

Alerts

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

Reproduction

Analysis started2023-12-11 04:39:28.689692
Analysis finished2023-12-11 04:39:30.035120
Duration1.35 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
2023-12-11T13:39:30.174100image/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
2023-12-11T13:39:30.678462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12 1
 
1.3%
13 1
 
1.3%
42 1
 
1.3%
76 1
 
1.3%
75 1
 
1.3%
74 1
 
1.3%
71 1
 
1.3%
64 1
 
1.3%
63 1
 
1.3%
61 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
보조구간
 
1

Length

Max length10
Median length6
Mean length6.3164557
Min length4

Unique

Unique4 ?
Unique (%)5.1%

Sample

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

Common Values

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

Length

2023-12-11T13:39:30.896823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:39:31.081081image/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%
보조구간 1
 
1.1%
올림픽공원역~수서역 1
 
1.1%

SHAPE
Text

UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size764.0 B
2023-12-11T13:39:31.416271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.898734
Min length10

Characters and Unicode

Total characters861
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@7f7d9193
2nd row[B@ce08b49
3rd row[B@69d86c39
4th row[B@7fa94878
5th row[B@42d4ffc2
ValueCountFrequency (%)
b@7f7d9193 1
 
1.3%
b@23841447 1
 
1.3%
b@5abdbd2a 1
 
1.3%
b@dfb03e9 1
 
1.3%
b@51bfe78d 1
 
1.3%
b@4fe72b1e 1
 
1.3%
b@40a9dcec 1
 
1.3%
b@5b7e4be9 1
 
1.3%
b@3f8b705e 1
 
1.3%
b@31484541 1
 
1.3%
Other values (69) 69
87.3%
2023-12-11T13:39:31.908181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
[ 79
 
9.2%
@ 79
 
9.2%
B 79
 
9.2%
3 49
 
5.7%
4 47
 
5.5%
2 45
 
5.2%
f 44
 
5.1%
9 43
 
5.0%
6 42
 
4.9%
7 40
 
4.6%
Other values (9) 314
36.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 406
47.2%
Lowercase Letter 218
25.3%
Open Punctuation 79
 
9.2%
Other Punctuation 79
 
9.2%
Uppercase Letter 79
 
9.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 49
12.1%
4 47
11.6%
2 45
11.1%
9 43
10.6%
6 42
10.3%
7 40
9.9%
5 40
9.9%
1 39
9.6%
0 33
8.1%
8 28
6.9%
Lowercase Letter
ValueCountFrequency (%)
f 44
20.2%
b 40
18.3%
c 39
17.9%
d 33
15.1%
e 32
14.7%
a 30
13.8%
Open Punctuation
ValueCountFrequency (%)
[ 79
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 79
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 79
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 564
65.5%
Latin 297
34.5%

Most frequent character per script

Common
ValueCountFrequency (%)
[ 79
14.0%
@ 79
14.0%
3 49
8.7%
4 47
8.3%
2 45
8.0%
9 43
7.6%
6 42
7.4%
7 40
7.1%
5 40
7.1%
1 39
6.9%
Other values (2) 61
10.8%
Latin
ValueCountFrequency (%)
B 79
26.6%
f 44
14.8%
b 40
13.5%
c 39
13.1%
d 33
11.1%
e 32
10.8%
a 30
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 861
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
[ 79
 
9.2%
@ 79
 
9.2%
B 79
 
9.2%
3 49
 
5.7%
4 47
 
5.5%
2 45
 
5.2%
f 44
 
5.1%
9 43
 
5.0%
6 42
 
4.9%
7 40
 
4.6%
Other values (9) 314
36.5%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.628818
Minimum37.455098
Maximum37.688125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2023-12-11T13:39:32.108537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.455098
5-th percentile37.534303
Q137.614404
median37.632609
Q337.654948
95-th percentile37.682581
Maximum37.688125
Range0.2330272
Interquartile range (IQR)0.04054425

Descriptive statistics

Standard deviation0.043832659
Coefficient of variation (CV)0.0011648694
Kurtosis5.3854891
Mean37.628818
Median Absolute Deviation (MAD)0.0185505
Skewness-1.9537755
Sum2972.6766
Variance0.001921302
MonotonicityNot monotonic
2023-12-11T13:39:32.274707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6145821 1
 
1.3%
37.6855885 1
 
1.3%
37.6440275 1
 
1.3%
37.6591567 1
 
1.3%
37.6428931 1
 
1.3%
37.6516539 1
 
1.3%
37.6546654 1
 
1.3%
37.6322248 1
 
1.3%
37.6676027 1
 
1.3%
37.6142255 1
 
1.3%
Other values (69) 69
87.3%
ValueCountFrequency (%)
37.4550975 1
1.3%
37.4738506 1
1.3%
37.4945012 1
1.3%
37.4992481 1
1.3%
37.5381981 1
1.3%
37.5829493 1
1.3%
37.5990934 1
1.3%
37.6079913 1
1.3%
37.6085621 1
1.3%
37.6089966 1
1.3%
ValueCountFrequency (%)
37.6881247 1
1.3%
37.6866424 1
1.3%
37.6855885 1
1.3%
37.6843733 1
1.3%
37.6823823 1
1.3%
37.6805743 1
1.3%
37.6798056 1
1.3%
37.6778848 1
1.3%
37.6751627 1
1.3%
37.6744913 1
1.3%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.00162
Minimum126.87888
Maximum127.136
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2023-12-11T13:39:32.424742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.87888
5-th percentile126.93598
Q1126.98601
median127.00615
Q3127.01222
95-th percentile127.07087
Maximum127.136
Range0.2571269
Interquartile range (IQR)0.02620825

Descriptive statistics

Standard deviation0.041446722
Coefficient of variation (CV)0.00032634798
Kurtosis2.432814
Mean127.00162
Median Absolute Deviation (MAD)0.018033
Skewness0.22614868
Sum10033.128
Variance0.0017178308
MonotonicityNot monotonic
2023-12-11T13:39:32.585939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.980954 1
 
1.3%
127.0328939 1
 
1.3%
127.0028646 1
 
1.3%
127.0079445 1
 
1.3%
127.0013072 1
 
1.3%
127.0083767 1
 
1.3%
127.0084132 1
 
1.3%
127.0085743 1
 
1.3%
127.0270891 1
 
1.3%
126.9883224 1
 
1.3%
Other values (69) 69
87.3%
ValueCountFrequency (%)
126.8788777 1
1.3%
126.8970699 1
1.3%
126.9354667 1
1.3%
126.9357633 1
1.3%
126.9360017 1
1.3%
126.9393804 1
1.3%
126.9411885 1
1.3%
126.9422836 1
1.3%
126.949395 1
1.3%
126.9513776 1
1.3%
ValueCountFrequency (%)
127.1360046 1
1.3%
127.1218916 1
1.3%
127.0998072 1
1.3%
127.0838273 1
1.3%
127.0694274 1
1.3%
127.0432797 1
1.3%
127.0421189 1
1.3%
127.0382478 1
1.3%
127.0328939 1
1.3%
127.0323835 1
1.3%

Interactions

2023-12-11T13:39:29.560976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:39:28.899202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:39:29.235727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:39:29.671654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:39:29.026241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:39:29.362761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:39:29.749125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:39:29.131009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:39:29.456250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T13:39:32.689482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번명칭SHAPE위도경도
순번1.0000.0001.0000.3810.278
명칭0.0001.0001.0000.7840.837
SHAPE1.0001.0001.0001.0001.000
위도0.3810.7841.0001.0000.821
경도0.2780.8371.0000.8211.000
2023-12-11T13:39:32.817410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번위도경도명칭
순번1.0000.2780.2730.000
위도0.2781.0000.5890.579
경도0.2730.5891.0000.590
명칭0.0000.5790.5901.000

Missing values

2023-12-11T13:39:29.863953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T13:39:29.989986image/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

순번명칭SHAPE위도경도
012탐방가능구간[B@7f7d919337.614582126.980954
113탐방가능구간[B@ce08b4937.685589127.032894
214탐방가능구간[B@69d86c3937.614984126.988115
315제목 없는 경로[B@7fa9487837.499248126.878878
420탐방가능구간[B@42d4ffc237.614119126.985344
529탐방가능구간[B@2de33bd537.680574127.029453
630탐방가능구간[B@216d347c37.61259126.982951
732탐방가능구간[B@890ca0937.629245127.008926
833탐방가능구간[B@59c0194337.662438127.009296
91탐방가능구간[B@52baabbd37.632821127.008809
순번명칭SHAPE위도경도
6960탐방가능구간[B@3ccf8f1037.635296127.006361
7062탐방가능구간[B@5eb982a037.645613127.002807
7165탐방가능구간[B@652f06f537.670917127.026451
7278탐방가능구간[B@7271f2b837.647551127.003949
7379올림픽공원역~수서역[B@16f648bb37.494501127.121892
7469탐방가능구간[B@320f8c437.656211127.00743
7570탐방가능구간[B@69ac0d7637.677885127.03109
7672탐방가능구간[B@1ea7f42d37.61694126.975317
7773탐방가능구간[B@248fc61437.649375127.003981
7877탐방가능구간[B@5b155dcc37.679806127.029791