Overview

Dataset statistics

Number of variables3
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory26.3 B

Variable types

Categorical2
Numeric1

Alerts

CTY_NM is highly overall correlated with RSTRNT_ID and 1 other fieldsHigh correlation
COUPON_CN is highly overall correlated with RSTRNT_ID and 1 other fieldsHigh correlation
RSTRNT_ID is highly overall correlated with CTY_NM and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-10 10:00:45.926732
Analysis finished2023-12-10 10:00:46.641604
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

CTY_NM
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
jeju
51 
busan
49 

Length

Max length5
Median length4
Mean length4.49
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
jeju 51
51.0%
busan 49
49.0%

Length

2023-12-10T19:00:46.821739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:00:47.083551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
jeju 51
51.0%
busan 49
49.0%

RSTRNT_ID
Real number (ℝ)

HIGH CORRELATION 

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1571.36
Minimum3
Maximum4271
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:00:47.346930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile9.9
Q148.5
median96.5
Q33938.25
95-th percentile4266.05
Maximum4271
Range4268
Interquartile range (IQR)3889.75

Descriptive statistics

Standard deviation1859.0614
Coefficient of variation (CV)1.1830907
Kurtosis-1.5496608
Mean1571.36
Median Absolute Deviation (MAD)89.5
Skewness0.57148662
Sum157136
Variance3456109.3
MonotonicityNot monotonic
2023-12-10T19:00:47.656897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 2
 
2.0%
3 1
 
1.0%
2184 1
 
1.0%
3914 1
 
1.0%
3909 1
 
1.0%
3804 1
 
1.0%
3716 1
 
1.0%
3653 1
 
1.0%
3295 1
 
1.0%
2985 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
3 1
1.0%
4 1
1.0%
6 1
1.0%
8 2
2.0%
10 1
1.0%
12 1
1.0%
13 1
1.0%
14 1
1.0%
15 1
1.0%
16 1
1.0%
ValueCountFrequency (%)
4271 1
1.0%
4270 1
1.0%
4269 1
1.0%
4268 1
1.0%
4267 1
1.0%
4266 1
1.0%
4265 1
1.0%
4264 1
1.0%
4263 1
1.0%
4261 1
1.0%

COUPON_CN
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
51 
飲み物１つ１テーブル当たり
36 
10％割引
6 
アメリカーノ1杯をプレゼント
 
2
1千ウォン割引１テーブル当たり
 
1
Other values (4)
 
4

Length

Max length16
Median length4
Mean length7.9
Min length4

Unique

Unique5 ?
Unique (%)5.0%

Sample

1st row飲み物１つ１テーブル当たり
2nd row飲み物１つ１テーブル当たり
3rd row飲み物１つ１テーブル当たり
4th row1千ウォン割引１テーブル当たり
5th row飲み物１つ１テーブル当たり

Common Values

ValueCountFrequency (%)
<NA> 51
51.0%
飲み物１つ１テーブル当たり 36
36.0%
10％割引 6
 
6.0%
アメリカーノ1杯をプレゼント 2
 
2.0%
1千ウォン割引１テーブル当たり 1
 
1.0%
野菜おにぎり1個１テーブル当たり 1
 
1.0%
3千ウォン割引１テーブル当たり 1
 
1.0%
昔のお菓子1個 1
 
1.0%
1千ウォン割引 1
 
1.0%

Length

2023-12-10T19:00:48.086866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:00:48.404504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 51
51.0%
飲み物１つ１テーブル当たり 36
36.0%
10％割引 6
 
6.0%
アメリカーノ1杯をプレゼント 2
 
2.0%
1千ウォン割引１テーブル当たり 1
 
1.0%
野菜おにぎり1個１テーブル当たり 1
 
1.0%
3千ウォン割引１テーブル当たり 1
 
1.0%
昔のお菓子1個 1
 
1.0%
1千ウォン割引 1
 
1.0%

Interactions

2023-12-10T19:00:46.190065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:00:48.614433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
CTY_NMRSTRNT_IDCOUPON_CN
CTY_NM1.0000.979NaN
RSTRNT_ID0.9791.000NaN
COUPON_CNNaNNaN1.000
2023-12-10T19:00:48.814428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
CTY_NMCOUPON_CN
CTY_NM1.0001.000
COUPON_CN1.0001.000
2023-12-10T19:00:48.964872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
RSTRNT_IDCTY_NMCOUPON_CN
RSTRNT_ID1.0000.8381.000
CTY_NM0.8381.0001.000
COUPON_CN1.0001.0001.000

Missing values

2023-12-10T19:00:46.410082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:00:46.586184image/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

CTY_NMRSTRNT_IDCOUPON_CN
0busan3飲み物１つ１テーブル当たり
1busan4飲み物１つ１テーブル当たり
2busan6飲み物１つ１テーブル当たり
3busan81千ウォン割引１テーブル当たり
4busan10飲み物１つ１テーブル当たり
5busan12飲み物１つ１テーブル当たり
6busan13飲み物１つ１テーブル当たり
7busan14飲み物１つ１テーブル当たり
8busan15飲み物１つ１テーブル当たり
9busan18飲み物１つ１テーブル当たり
CTY_NMRSTRNT_IDCOUPON_CN
90jeju4261<NA>
91jeju4263<NA>
92jeju4264<NA>
93jeju4265<NA>
94jeju4266<NA>
95jeju4267<NA>
96jeju4268<NA>
97jeju4269<NA>
98jeju4270<NA>
99jeju4271<NA>