Overview

Dataset statistics

Number of variables4
Number of observations56
Missing cells53
Missing cells (%)23.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory35.4 B

Variable types

Text2
Categorical1
Numeric1

Dataset

Description경기도 양평군 남한강 자전거길 이용객수 데이터로 기준년월 계측지점 이용객수로 구분하여 데이터를 제공합니다. 남한강자전거길 이용객수
Author경기도 양평군
URLhttps://www.data.go.kr/data/15106640/fileData.do

Alerts

계측지점 has constant value ""Constant
비고 has 53 (94.6%) missing valuesMissing
기준년월 has unique valuesUnique
이용객수 has 3 (5.4%) zerosZeros

Reproduction

Analysis started2023-12-12 13:49:30.408753
Analysis finished2023-12-12 13:49:30.818589
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Text

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size580.0 B
2023-12-12T22:49:30.980011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length8
Min length7

Characters and Unicode

Total characters448
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)100.0%

Sample

1st row2019년 1월
2nd row2019년 2월
3rd row2019년 3월
4th row2019년 4월
5th row2019년 5월
ValueCountFrequency (%)
2019년 12
 
12.0%
2020년 12
 
12.0%
2021년 12
 
12.0%
2023년 8
 
8.0%
7월 4
 
4.0%
3월 4
 
4.0%
1월 4
 
4.0%
8월 4
 
4.0%
2월 4
 
4.0%
6월 4
 
4.0%
Other values (18) 32
32.0%
2023-12-12T22:49:31.403369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 121
27.0%
0 72
16.1%
년 56
12.5%
월 56
12.5%
1 45
 
10.0%
44
 
9.8%
9 16
 
3.6%
3 13
 
2.9%
4 5
 
1.1%
5 5
 
1.1%
Other values (3) 15
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 292
65.2%
Other Letter 112
 
25.0%
Space Separator 44
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 121
41.4%
0 72
24.7%
1 45
 
15.4%
9 16
 
5.5%
3 13
 
4.5%
4 5
 
1.7%
5 5
 
1.7%
6 5
 
1.7%
7 5
 
1.7%
8 5
 
1.7%
Other Letter
ValueCountFrequency (%)
년 56
50.0%
월 56
50.0%
Space Separator
ValueCountFrequency (%)
44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 336
75.0%
Hangul 112
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 121
36.0%
0 72
21.4%
1 45
 
13.4%
44
 
13.1%
9 16
 
4.8%
3 13
 
3.9%
4 5
 
1.5%
5 5
 
1.5%
6 5
 
1.5%
7 5
 
1.5%
Hangul
ValueCountFrequency (%)
년 56
50.0%
월 56
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 336
75.0%
Hangul 112
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 121
36.0%
0 72
21.4%
1 45
 
13.4%
44
 
13.1%
9 16
 
4.8%
3 13
 
3.9%
4 5
 
1.5%
5 5
 
1.5%
6 5
 
1.5%
7 5
 
1.5%
Hangul
ValueCountFrequency (%)
년 56
50.0%
월 56
50.0%

계측지점
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
북한강철교 초소쉼터
56 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row북한강철교 초소쉼터
2nd row북한강철교 초소쉼터
3rd row북한강철교 초소쉼터
4th row북한강철교 초소쉼터
5th row북한강철교 초소쉼터

Common Values

ValueCountFrequency (%)
북한강철교 초소쉼터 56
100.0%

Length

2023-12-12T22:49:31.576133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:49:31.678146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
북한강철교 56
50.0%
초소쉼터 56
50.0%

이용객수
Real number (ℝ)

ZEROS 

Distinct54
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51129.768
Minimum0
Maximum161826
Zeros3
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size636.0 B
2023-12-12T22:49:31.819452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2825.25
Q127551.5
median49585.5
Q364961.25
95-th percentile132509.75
Maximum161826
Range161826
Interquartile range (IQR)37409.75

Descriptive statistics

Standard deviation36669.98
Coefficient of variation (CV)0.71719435
Kurtosis1.3990524
Mean51129.768
Median Absolute Deviation (MAD)19404.5
Skewness1.0468213
Sum2863267
Variance1.3446875 × 109
MonotonicityNot monotonic
2023-12-12T22:49:31.980266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3
 
5.4%
17158 1
 
1.8%
41029 1
 
1.8%
76726 1
 
1.8%
60340 1
 
1.8%
27772 1
 
1.8%
8972 1
 
1.8%
7853 1
 
1.8%
11520 1
 
1.8%
26111 1
 
1.8%
Other values (44) 44
78.6%
ValueCountFrequency (%)
0 3
5.4%
3767 1
 
1.8%
4284 1
 
1.8%
7718 1
 
1.8%
7853 1
 
1.8%
8972 1
 
1.8%
11520 1
 
1.8%
13064 1
 
1.8%
16150 1
 
1.8%
17158 1
 
1.8%
ValueCountFrequency (%)
161826 1
1.8%
148988 1
1.8%
134600 1
1.8%
131813 1
1.8%
117792 1
1.8%
86038 1
1.8%
85881 1
1.8%
83483 1
1.8%
76726 1
1.8%
72146 1
1.8%

비고
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing53
Missing (%)94.6%
Memory size580.0 B
2023-12-12T22:49:32.182550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length16.666667
Min length14

Characters and Unicode

Total characters50
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st row무인계측기 고장으로 미측정
2nd row무인계측기 교체수리 중으로 미측정
3rd row무인계측기 교체수리 중으로 미측정
ValueCountFrequency (%)
무인계측기 3
27.3%
미측정 3
27.3%
교체수리 2
18.2%
중으로 2
18.2%
고장으로 1
 
9.1%
2023-12-12T22:49:32.529062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8
16.0%
측 6
12.0%
무 3
 
6.0%
으 3
 
6.0%
계 3
 
6.0%
기 3
 
6.0%
정 3
 
6.0%
미 3
 
6.0%
인 3
 
6.0%
로 3
 
6.0%
Other values (7) 12
24.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42
84.0%
Space Separator 8
 
16.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
측 6
14.3%
무 3
 
7.1%
으 3
 
7.1%
계 3
 
7.1%
기 3
 
7.1%
정 3
 
7.1%
미 3
 
7.1%
인 3
 
7.1%
로 3
 
7.1%
수 2
 
4.8%
Other values (6) 10
23.8%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42
84.0%
Common 8
 
16.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
측 6
14.3%
무 3
 
7.1%
으 3
 
7.1%
계 3
 
7.1%
기 3
 
7.1%
정 3
 
7.1%
미 3
 
7.1%
인 3
 
7.1%
로 3
 
7.1%
수 2
 
4.8%
Other values (6) 10
23.8%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42
84.0%
ASCII 8
 
16.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8
100.0%
Hangul
ValueCountFrequency (%)
측 6
14.3%
무 3
 
7.1%
으 3
 
7.1%
계 3
 
7.1%
기 3
 
7.1%
정 3
 
7.1%
미 3
 
7.1%
인 3
 
7.1%
로 3
 
7.1%
수 2
 
4.8%
Other values (6) 10
23.8%

Interactions

2023-12-12T22:49:30.510395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:49:32.627931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년월이용객수비고
기준년월1.0001.0001.000
이용객수1.0001.000NaN
비고1.000NaN1.000

Missing values

2023-12-12T22:49:30.664477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:49:30.773081image/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

기준년월계측지점이용객수비고
02019년 1월북한강철교 초소쉼터17158<NA>
12019년 2월북한강철교 초소쉼터134600<NA>
22019년 3월북한강철교 초소쉼터161826<NA>
32019년 4월북한강철교 초소쉼터85881<NA>
42019년 5월북한강철교 초소쉼터131813<NA>
52019년 6월북한강철교 초소쉼터148988<NA>
62019년 7월북한강철교 초소쉼터53924<NA>
72019년 8월북한강철교 초소쉼터117792<NA>
82019년 9월북한강철교 초소쉼터70378<NA>
92019년 10월북한강철교 초소쉼터46980<NA>
기준년월계측지점이용객수비고
462022년11월북한강철교 초소쉼터27665<NA>
472022년12월북한강철교 초소쉼터4284<NA>
482023년 1월북한강철교 초소쉼터3767<NA>
492023년 2월북한강철교 초소쉼터16150<NA>
502023년 3월북한강철교 초소쉼터42785<NA>
512023년 4월북한강철교 초소쉼터51661<NA>
522023년 5월북한강철교 초소쉼터49751<NA>
532023년 6월북한강철교 초소쉼터49420<NA>
542023년 7월북한강철교 초소쉼터33726<NA>
552023년 8월북한강철교 초소쉼터40406<NA>