Overview

Dataset statistics

Number of variables5
Number of observations400
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.9 KiB
Average record size in memory43.3 B

Variable types

Numeric3
DateTime1
Text1

Dataset

DescriptionSample
Author코난테크놀로지
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=TOPICINSTT

Alerts

"차례값" is highly overall correlated with "건수값"High correlation
"건수값" is highly overall correlated with "차례값"High correlation
"기본키값" has unique valuesUnique

Reproduction

Analysis started2023-12-10 06:35:39.382445
Analysis finished2023-12-10 06:35:41.651034
Duration2.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

"기본키값"
Real number (ℝ)

UNIQUE 

Distinct400
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65020.5
Minimum64821
Maximum65220
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-10T15:35:41.770015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum64821
5-th percentile64840.95
Q164920.75
median65020.5
Q365120.25
95-th percentile65200.05
Maximum65220
Range399
Interquartile range (IQR)199.5

Descriptive statistics

Standard deviation115.6143
Coefficient of variation (CV)0.0017781208
Kurtosis-1.2
Mean65020.5
Median Absolute Deviation (MAD)100
Skewness0
Sum26008200
Variance13366.667
MonotonicityStrictly increasing
2023-12-10T15:35:41.993144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
64821 1
 
0.2%
65085 1
 
0.2%
65095 1
 
0.2%
65094 1
 
0.2%
65093 1
 
0.2%
65092 1
 
0.2%
65091 1
 
0.2%
65090 1
 
0.2%
65089 1
 
0.2%
65088 1
 
0.2%
Other values (390) 390
97.5%
ValueCountFrequency (%)
64821 1
0.2%
64822 1
0.2%
64823 1
0.2%
64824 1
0.2%
64825 1
0.2%
64826 1
0.2%
64827 1
0.2%
64828 1
0.2%
64829 1
0.2%
64830 1
0.2%
ValueCountFrequency (%)
65220 1
0.2%
65219 1
0.2%
65218 1
0.2%
65217 1
0.2%
65216 1
0.2%
65215 1
0.2%
65214 1
0.2%
65213 1
0.2%
65212 1
0.2%
65211 1
0.2%

"해당일시"
Date

Distinct40
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
Minimum2020-10-01 00:00:00
Maximum2020-10-02 15:00:00
2023-12-10T15:35:42.203169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:35:42.411292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

"차례값"
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-10T15:35:42.675885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5.5
Q38
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.8758784
Coefficient of variation (CV)0.52288699
Kurtosis-1.224533
Mean5.5
Median Absolute Deviation (MAD)2.5
Skewness0
Sum2200
Variance8.2706767
MonotonicityNot monotonic
2023-12-10T15:35:42.871031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 40
10.0%
2 40
10.0%
3 40
10.0%
4 40
10.0%
5 40
10.0%
6 40
10.0%
7 40
10.0%
8 40
10.0%
9 40
10.0%
10 40
10.0%
ValueCountFrequency (%)
1 40
10.0%
2 40
10.0%
3 40
10.0%
4 40
10.0%
5 40
10.0%
6 40
10.0%
7 40
10.0%
8 40
10.0%
9 40
10.0%
10 40
10.0%
ValueCountFrequency (%)
10 40
10.0%
9 40
10.0%
8 40
10.0%
7 40
10.0%
6 40
10.0%
5 40
10.0%
4 40
10.0%
3 40
10.0%
2 40
10.0%
1 40
10.0%

"이슈어값"
Text

Distinct165
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-12-10T15:35:43.306035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.77
Min length2

Characters and Unicode

Total characters1508
Distinct characters236
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)24.2%

Sample

1st row기호일보
2nd row청와대
3rd row기초과학연구원
4th row디즈니
5th rowytn
ValueCountFrequency (%)
네이버 13
 
3.2%
ytn 12
 
3.0%
청와대 12
 
3.0%
국회 11
 
2.8%
애플 10
 
2.5%
sbs 9
 
2.2%
kbs 9
 
2.2%
롯데 8
 
2.0%
중앙일보 8
 
2.0%
더불어민주당 7
 
1.8%
Other values (155) 301
75.2%
2023-12-10T15:35:43.991216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 47
 
3.1%
일 45
 
3.0%
스 43
 
2.9%
국 37
 
2.5%
보 37
 
2.5%
s 33
 
2.2%
부 29
 
1.9%
b 29
 
1.9%
원 25
 
1.7%
뉴 24
 
1.6%
Other values (226) 1159
76.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1341
88.9%
Lowercase Letter 157
 
10.4%
Decimal Number 10
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 47
 
3.5%
일 45
 
3.4%
스 43
 
3.2%
국 37
 
2.8%
보 37
 
2.8%
부 29
 
2.2%
원 25
 
1.9%
뉴 24
 
1.8%
청 24
 
1.8%
데 24
 
1.8%
Other values (210) 1006
75.0%
Lowercase Letter
ValueCountFrequency (%)
s 33
21.0%
b 29
18.5%
t 23
14.6%
k 17
10.8%
n 13
 
8.3%
y 12
 
7.6%
c 9
 
5.7%
g 5
 
3.2%
m 5
 
3.2%
v 5
 
3.2%
Other values (3) 6
 
3.8%
Decimal Number
ValueCountFrequency (%)
1 8
80.0%
2 1
 
10.0%
4 1
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1341
88.9%
Latin 157
 
10.4%
Common 10
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 47
 
3.5%
일 45
 
3.4%
스 43
 
3.2%
국 37
 
2.8%
보 37
 
2.8%
부 29
 
2.2%
원 25
 
1.9%
뉴 24
 
1.8%
청 24
 
1.8%
데 24
 
1.8%
Other values (210) 1006
75.0%
Latin
ValueCountFrequency (%)
s 33
21.0%
b 29
18.5%
t 23
14.6%
k 17
10.8%
n 13
 
8.3%
y 12
 
7.6%
c 9
 
5.7%
g 5
 
3.2%
m 5
 
3.2%
v 5
 
3.2%
Other values (3) 6
 
3.8%
Common
ValueCountFrequency (%)
1 8
80.0%
2 1
 
10.0%
4 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1341
88.9%
ASCII 167
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 47
 
3.5%
일 45
 
3.4%
스 43
 
3.2%
국 37
 
2.8%
보 37
 
2.8%
부 29
 
2.2%
원 25
 
1.9%
뉴 24
 
1.8%
청 24
 
1.8%
데 24
 
1.8%
Other values (210) 1006
75.0%
ASCII
ValueCountFrequency (%)
s 33
19.8%
b 29
17.4%
t 23
13.8%
k 17
10.2%
n 13
 
7.8%
y 12
 
7.2%
c 9
 
5.4%
1 8
 
4.8%
g 5
 
3.0%
m 5
 
3.0%
Other values (6) 13
 
7.8%

"건수값"
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.905
Minimum2
Maximum85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-10T15:35:44.218149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q13
median5
Q38
95-th percentile17.05
Maximum85
Range83
Interquartile range (IQR)5

Descriptive statistics

Standard deviation7.6335872
Coefficient of variation (CV)1.1055159
Kurtosis41.152899
Mean6.905
Median Absolute Deviation (MAD)2
Skewness5.3769407
Sum2762
Variance58.271654
MonotonicityNot monotonic
2023-12-10T15:35:44.440226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
3 69
17.2%
4 63
15.8%
5 51
12.8%
2 47
11.8%
6 38
9.5%
7 30
7.5%
8 20
 
5.0%
9 20
 
5.0%
10 9
 
2.2%
11 8
 
2.0%
Other values (22) 45
11.2%
ValueCountFrequency (%)
2 47
11.8%
3 69
17.2%
4 63
15.8%
5 51
12.8%
6 38
9.5%
7 30
7.5%
8 20
 
5.0%
9 20
 
5.0%
10 9
 
2.2%
11 8
 
2.0%
ValueCountFrequency (%)
85 1
0.2%
68 1
0.2%
49 1
0.2%
42 1
0.2%
36 1
0.2%
35 1
0.2%
34 1
0.2%
33 1
0.2%
28 1
0.2%
25 1
0.2%

Interactions

2023-12-10T15:35:40.872256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:35:39.787386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:35:40.425458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:35:41.030308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:35:40.026700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:35:40.602764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:35:41.176677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:35:40.281111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:35:40.738274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:35:44.624979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
"기본키값""해당일시""차례값""건수값"
"기본키값"1.0001.0000.0000.124
"해당일시"1.0001.0000.0000.252
"차례값"0.0000.0001.0000.448
"건수값"0.1240.2520.4481.000
2023-12-10T15:35:44.900848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
"기본키값""차례값""건수값"
"기본키값"1.0000.0250.141
"차례값"0.0251.000-0.674
"건수값"0.141-0.6741.000

Missing values

2023-12-10T15:35:41.437911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:35:41.591193image/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

"기본키값""해당일시""차례값""이슈어값""건수값"
0648212020-10-01 00:00:001기호일보16
1648222020-10-01 00:00:002청와대7
2648232020-10-01 00:00:003기초과학연구원7
3648242020-10-01 00:00:004디즈니6
4648252020-10-01 00:00:005ytn6
5648262020-10-01 00:00:006울산과학기술원5
6648272020-10-01 00:00:007국방부4
7648282020-10-01 00:00:008lg전자4
8648292020-10-01 00:00:009롯데제과4
9648302020-10-01 00:00:0010두산베어스3
"기본키값""해당일시""차례값""이슈어값""건수값"
390652112020-10-02 15:00:001청와대22
391652122020-10-02 15:00:002페르소나6
392652132020-10-02 15:00:003서울신문5
393652142020-10-02 15:00:004jtbc5
394652152020-10-02 15:00:005중앙일보4
395652162020-10-02 15:00:006구글4
396652172020-10-02 15:00:007굿스마일4
397652182020-10-02 15:00:008천지일보4
398652192020-10-02 15:00:009헤럴드경제3
399652202020-10-02 15:00:0010산업통상자원부3