Overview

Dataset statistics

Number of variables3
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows44
Duplicate rows (%)0.4%
Total size in memory332.0 KiB
Average record size in memory34.0 B

Variable types

DateTime1
Categorical1
Numeric1

Dataset

Description충청북도 행정간행물홈페이지내의 도서인덱스 메뉴분석 테이블 정보를 날짜, 뎁스 등의 항목등을 공개하는 csv 파일입니다
Author충청북도
URLhttps://www.data.go.kr/data/15039146/fileData.do

Alerts

접근일 has constant value ""Constant
메뉴_그룹_키 has constant value ""Constant
Dataset has 44 (0.4%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 16:49:39.634114
Analysis finished2023-12-12 16:49:39.987978
Duration0.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

접근일
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2019-09-17 00:00:00
Maximum2019-09-17 00:00:00
2023-12-13T01:49:40.040796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:49:40.161817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

메뉴_그룹_키
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
10000 

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 10000
100.0%

Length

2023-12-13T01:49:40.284662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:49:40.385320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 10000
100.0%

메뉴_키
Real number (ℝ)

Distinct44
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56073.736
Minimum1
Maximum91670
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:49:40.829946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q112
median89265
Q389272
95-th percentile89281
Maximum91670
Range91669
Interquartile range (IQR)89260

Descriptive statistics

Standard deviation43150.667
Coefficient of variation (CV)0.76953437
Kurtosis-1.7197199
Mean56073.736
Median Absolute Deviation (MAD)12
Skewness-0.5296989
Sum5.6073736 × 108
Variance1.86198 × 109
MonotonicityNot monotonic
2023-12-13T01:49:41.013870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
89272 1985
19.9%
12 1608
16.1%
1 471
 
4.7%
89278 369
 
3.7%
89253 333
 
3.3%
89290 323
 
3.2%
89276 301
 
3.0%
89271 274
 
2.7%
21 261
 
2.6%
9 240
 
2.4%
Other values (34) 3835
38.4%
ValueCountFrequency (%)
1 471
 
4.7%
3 12
 
0.1%
5 75
 
0.8%
8 31
 
0.3%
9 240
 
2.4%
10 234
 
2.3%
11 211
 
2.1%
12 1608
16.1%
13 73
 
0.7%
14 68
 
0.7%
ValueCountFrequency (%)
91670 31
 
0.3%
89311 24
 
0.2%
89291 8
 
0.1%
89290 323
3.2%
89281 121
 
1.2%
89280 141
 
1.4%
89279 111
 
1.1%
89278 369
3.7%
89276 301
3.0%
89275 234
2.3%

Interactions

2023-12-13T01:49:39.727093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-13T01:49:39.861207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:49:39.945937image/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

접근일메뉴_그룹_키메뉴_키
442762019-09-17189273
13902019-09-17189274
420952019-09-17189253
526372019-09-1711
534672019-09-17118
255142019-09-17189272
193342019-09-17189272
781612019-09-17113
603682019-09-17111
449812019-09-17189281
접근일메뉴_그룹_키메뉴_키
15562019-09-17189271
314682019-09-17189253
237542019-09-17189270
224722019-09-17189272
524942019-09-17113
43082019-09-17189274
43972019-09-17189269
441462019-09-17189261
524452019-09-17112
406512019-09-17189266

Duplicate rows

Most frequently occurring

접근일메뉴_그룹_키메뉴_키# duplicates
312019-09-171892721985
72019-09-171121608
02019-09-1711471
362019-09-17189278369
172019-09-17189253333
402019-09-17189290323
352019-09-17189276301
302019-09-17189271274
152019-09-17121261
42019-09-1719240