Overview

Dataset statistics

Number of variables3
Number of observations171
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory25.8 B

Variable types

Categorical2
Numeric1

Dataset

Description무인계수기가 설치된 관광지의 무인계수기 입장객 수에 대한 데이터로관광지명, 계수일자, 입장객수 등의 항목을 제공합니다.
Author대구광역시 북구
URLhttps://www.data.go.kr/data/15095834/fileData.do

Alerts

관광객수 is highly overall correlated with 관광지명High correlation
관광지명 is highly overall correlated with 관광객수High correlation
관광객수 has unique valuesUnique

Reproduction

Analysis started2024-04-21 02:05:17.115705
Analysis finished2024-04-21 02:05:18.410734
Duration1.3 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관광지명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
운암지수변공원
48 
별별상상칠성야시장
48 
이태원길
47 
구암서원
28 

Length

Max length9
Median length7
Mean length6.245614
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운암지수변공원 48
28.1%
별별상상칠성야시장 48
28.1%
이태원길 47
27.5%
구암서원 28
16.4%

Length

2024-04-21T11:05:18.491697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:05:18.603010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운암지수변공원 48
28.1%
별별상상칠성야시장 48
28.1%
이태원길 47
27.5%
구암서원 28
16.4%

계수일자
Categorical

Distinct48
Distinct (%)28.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2022-04-01
 
4
2023-08-01
 
4
2022-03-01
 
4
2021-12-01
 
4
2022-01-01
 
4
Other values (43)
151 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-04-01
2nd row2020-05-01
3rd row2020-06-01
4th row2020-07-01
5th row2020-08-01

Common Values

ValueCountFrequency (%)
2022-04-01 4
 
2.3%
2023-08-01 4
 
2.3%
2022-03-01 4
 
2.3%
2021-12-01 4
 
2.3%
2022-01-01 4
 
2.3%
2023-04-01 4
 
2.3%
2024-03-01 4
 
2.3%
2022-06-01 4
 
2.3%
2024-02-01 4
 
2.3%
2024-01-01 4
 
2.3%
Other values (38) 131
76.6%

Length

2024-04-21T11:05:18.719347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022-04-01 4
 
2.3%
2023-07-01 4
 
2.3%
2022-05-01 4
 
2.3%
2023-05-01 4
 
2.3%
2023-03-01 4
 
2.3%
2023-08-01 4
 
2.3%
2023-01-01 4
 
2.3%
2022-08-01 4
 
2.3%
2022-11-01 4
 
2.3%
2022-10-01 4
 
2.3%
Other values (38) 131
76.6%

관광객수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct171
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47880.772
Minimum552
Maximum171576
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-21T11:05:18.844177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum552
5-th percentile1772
Q118227
median34014
Q352019.5
95-th percentile125841
Maximum171576
Range171024
Interquartile range (IQR)33792.5

Descriptive statistics

Standard deviation43063.346
Coefficient of variation (CV)0.89938704
Kurtosis-0.25404731
Mean47880.772
Median Absolute Deviation (MAD)15922
Skewness1.0155757
Sum8187612
Variance1.8544517 × 109
MonotonicityNot monotonic
2024-04-21T11:05:18.976959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16154 1
 
0.6%
29575 1
 
0.6%
30575 1
 
0.6%
30650 1
 
0.6%
35191 1
 
0.6%
35787 1
 
0.6%
33895 1
 
0.6%
27632 1
 
0.6%
26103 1
 
0.6%
21376 1
 
0.6%
Other values (161) 161
94.2%
ValueCountFrequency (%)
552 1
0.6%
847 1
0.6%
926 1
0.6%
1053 1
0.6%
1176 1
0.6%
1181 1
0.6%
1457 1
0.6%
1485 1
0.6%
1763 1
0.6%
1781 1
0.6%
ValueCountFrequency (%)
171576 1
0.6%
154280 1
0.6%
153960 1
0.6%
139415 1
0.6%
133172 1
0.6%
132118 1
0.6%
131499 1
0.6%
129492 1
0.6%
127146 1
0.6%
124536 1
0.6%

Interactions

2024-04-21T11:05:18.024595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T11:05:19.071042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관광지명계수일자관광객수
관광지명1.0000.0000.812
계수일자0.0001.0000.469
관광객수0.8120.4691.000
2024-04-21T11:05:19.154262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관광지명계수일자
관광지명1.0000.000
계수일자0.0001.000
2024-04-21T11:05:19.237446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관광객수관광지명계수일자
관광객수1.0000.6700.152
관광지명0.6701.0000.000
계수일자0.1520.0001.000

Missing values

2024-04-21T11:05:18.314522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:05:18.377848image/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

관광지명계수일자관광객수
0운암지수변공원2020-04-0116154
1운암지수변공원2020-05-0148678
2운암지수변공원2020-06-0147118
3운암지수변공원2020-07-0149890
4운암지수변공원2020-08-0139740
5운암지수변공원2020-09-0143752
6운암지수변공원2020-10-0154149
7운암지수변공원2020-11-0118362
8운암지수변공원2020-12-014451
9운암지수변공원2021-01-015340
관광지명계수일자관광객수
161구암서원2023-06-014326
162구암서원2023-07-011781
163구암서원2023-08-011763
164구암서원2023-09-015010
165구암서원2023-10-014970
166구암서원2023-11-014282
167구암서원2023-12-011181
168구암서원2024-01-01926
169구암서원2024-02-011176
170구암서원2024-03-012401