Overview

Dataset statistics

Number of variables5
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory43.3 B

Variable types

Categorical3
Numeric2

Alerts

상수도구경단위() has constant value ""Constant
적용금액단위() has constant value ""Constant
상수도구경() is highly overall correlated with 적용금액()High correlation
적용금액() is highly overall correlated with 상수도구경()High correlation
적용금액() has 15 (15.0%) zerosZeros

Reproduction

Analysis started2023-12-10 10:20:56.181631
Analysis finished2023-12-10 10:20:57.658370
Duration1.48 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지자체()
Categorical

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
동두천시
16 
양주시
15 
단양군
14 
서산시
13 
논산시
12 
Other values (3)
30 

Length

Max length4
Median length3
Mean length3.16
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동두천시 16
16.0%
양주시 15
15.0%
단양군 14
14.0%
서산시 13
13.0%
논산시 12
12.0%
광주시 11
11.0%
파주시 10
10.0%
금산군 9
9.0%

Length

2023-12-10T19:20:57.815567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:20:58.007679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동두천시 16
16.0%
양주시 15
15.0%
단양군 14
14.0%
서산시 13
13.0%
논산시 12
12.0%
광주시 11
11.0%
파주시 10
10.0%
금산군 9
9.0%

상수도구경()
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.82
Minimum13
Maximum700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:20:58.596424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile13
Q125
median50
Q3112.5
95-th percentile252.5
Maximum700
Range687
Interquartile range (IQR)87.5

Descriptive statistics

Standard deviation111.92606
Coefficient of variation (CV)1.1804056
Kurtosis11.283466
Mean94.82
Median Absolute Deviation (MAD)30
Skewness2.8734589
Sum9482
Variance12527.442
MonotonicityNot monotonic
2023-12-10T19:20:58.733809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
20 8
 
8.0%
25 8
 
8.0%
32 8
 
8.0%
40 8
 
8.0%
50 8
 
8.0%
13 7
 
7.0%
150 7
 
7.0%
200 7
 
7.0%
100 7
 
7.0%
80 7
 
7.0%
Other values (7) 25
25.0%
ValueCountFrequency (%)
13 7
7.0%
15 6
6.0%
20 8
8.0%
25 8
8.0%
30 1
 
1.0%
32 8
8.0%
40 8
8.0%
50 8
8.0%
75 7
7.0%
80 7
7.0%
ValueCountFrequency (%)
700 1
 
1.0%
600 1
 
1.0%
300 3
 
3.0%
250 6
6.0%
200 7
7.0%
150 7
7.0%
100 7
7.0%
80 7
7.0%
75 7
7.0%
50 8
8.0%

상수도구경단위()
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
mm
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
mm 100
100.0%

Length

2023-12-10T19:20:58.954270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:20:59.084074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mm 100
100.0%

적용금액()
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct73
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66332.52
Minimum0
Maximum524180
Zeros15
Zeros (%)15.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:20:59.227705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11302.5
median9143.5
Q369592.5
95-th percentile398590
Maximum524180
Range524180
Interquartile range (IQR)68290

Descriptive statistics

Standard deviation122412.99
Coefficient of variation (CV)1.8454445
Kurtosis5.6632564
Mean66332.52
Median Absolute Deviation (MAD)9143.5
Skewness2.4715934
Sum6633252
Variance1.4984939 × 1010
MonotonicityNot monotonic
2023-12-10T19:20:59.452684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 15
 
15.0%
524180 3
 
3.0%
600 2
 
2.0%
398590 2
 
2.0%
75540 2
 
2.0%
38668 2
 
2.0%
23910 2
 
2.0%
1500 2
 
2.0%
1250 2
 
2.0%
1194 2
 
2.0%
Other values (63) 66
66.0%
ValueCountFrequency (%)
0 15
15.0%
600 2
 
2.0%
800 1
 
1.0%
810 2
 
2.0%
930 1
 
1.0%
1194 2
 
2.0%
1250 2
 
2.0%
1320 1
 
1.0%
1500 2
 
2.0%
1570 1
 
1.0%
ValueCountFrequency (%)
524180 3
3.0%
421010 1
 
1.0%
398590 2
2.0%
309290 1
 
1.0%
304116 1
 
1.0%
280620 1
 
1.0%
218350 1
 
1.0%
208539 1
 
1.0%
179580 1
 
1.0%
178110 1
 
1.0%

적용금액단위()
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
원/톤
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row원/톤
2nd row원/톤
3rd row원/톤
4th row원/톤
5th row원/톤

Common Values

ValueCountFrequency (%)
원/톤 100
100.0%

Length

2023-12-10T19:20:59.625459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:20:59.746567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원/톤 100
100.0%

Interactions

2023-12-10T19:20:57.056700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:20:56.445809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:20:57.204741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:20:56.763868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:20:59.832507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지자체()상수도구경()적용금액()
지자체()1.0000.0000.183
상수도구경()0.0001.0000.779
적용금액()0.1830.7791.000
2023-12-10T19:20:59.983828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상수도구경()적용금액()지자체()
상수도구경()1.0000.6810.000
적용금액()0.6811.0000.085
지자체()0.0000.0851.000

Missing values

2023-12-10T19:20:57.399056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:20:57.582352image/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

지자체()상수도구경()상수도구경단위()적용금액()적용금액단위()
0동두천시13mm1250원/톤
1동두천시15mm1250원/톤
2동두천시20mm3330원/톤
3동두천시25mm5850원/톤
4동두천시32mm10590원/톤
5동두천시40mm17790원/톤
6동두천시50mm28770원/톤
7동두천시75mm59170원/톤
8동두천시80mm59170원/톤
9동두천시100mm100470원/톤
지자체()상수도구경()상수도구경단위()적용금액()적용금액단위()
90논산시250mm168240원/톤
91금산군13mm600원/톤
92금산군15mm600원/톤
93금산군20mm810원/톤
94금산군25mm930원/톤
95금산군32mm1320원/톤
96금산군40mm1710원/톤
97금산군50mm3300원/톤
98금산군75mm6900원/톤
99금산군80mm6900원/톤