Overview

Dataset statistics

Number of variables7
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory62.3 B

Variable types

Numeric2
Categorical5

Alerts

측정일 has constant value ""Constant
강수량(mm) has constant value ""Constant
강우량(mm) has constant value ""Constant
기본키 is highly overall correlated with 측정시간 and 2 other fieldsHigh correlation
측정시간 is highly overall correlated with 기본키High correlation
지점 is highly overall correlated with 기본키 and 1 other fieldsHigh correlation
주소 is highly overall correlated with 기본키 and 1 other fieldsHigh correlation
지점 is highly imbalanced (71.4%)Imbalance
주소 is highly imbalanced (71.4%)Imbalance
기본키 has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:42:43.235733
Analysis finished2023-12-10 13:42:44.569917
Duration1.33 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기본키
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:42:44.711364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q125.75
median50.5
Q375.25
95-th percentile95.05
Maximum100
Range99
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityStrictly increasing
2023-12-10T22:42:45.017579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

측정일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210101
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210101
2nd row20210101
3rd row20210101
4th row20210101
5th row20210101

Common Values

ValueCountFrequency (%)
20210101 100
100.0%

Length

2023-12-10T22:42:45.291645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:42:45.454283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210101 100
100.0%

측정시간
Real number (ℝ)

HIGH CORRELATION 

Distinct95
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1128.65
Minimum15
Maximum2345
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:42:45.634448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile45
Q1511.25
median1122.5
Q31733.75
95-th percentile2230.75
Maximum2345
Range2330
Interquartile range (IQR)1222.5

Descriptive statistics

Standard deviation715.23742
Coefficient of variation (CV)0.63371056
Kurtosis-1.2427915
Mean1128.65
Median Absolute Deviation (MAD)615
Skewness0.039182625
Sum112865
Variance511564.57
MonotonicityNot monotonic
2023-12-10T22:42:45.963722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15 2
 
2.0%
45 2
 
2.0%
100 2
 
2.0%
115 2
 
2.0%
30 2
 
2.0%
1530 1
 
1.0%
1745 1
 
1.0%
1730 1
 
1.0%
1715 1
 
1.0%
1700 1
 
1.0%
Other values (85) 85
85.0%
ValueCountFrequency (%)
15 2
2.0%
30 2
2.0%
45 2
2.0%
100 2
2.0%
115 2
2.0%
130 1
1.0%
145 1
1.0%
200 1
1.0%
215 1
1.0%
230 1
1.0%
ValueCountFrequency (%)
2345 1
1.0%
2330 1
1.0%
2315 1
1.0%
2300 1
1.0%
2245 1
1.0%
2230 1
1.0%
2215 1
1.0%
2200 1
1.0%
2145 1
1.0%
2130 1
1.0%

지점
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
A-0010-1185E-8
95 
A-0010-3019E-6
 
5

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA-0010-1185E-8
2nd rowA-0010-1185E-8
3rd rowA-0010-1185E-8
4th rowA-0010-1185E-8
5th rowA-0010-1185E-8

Common Values

ValueCountFrequency (%)
A-0010-1185E-8 95
95.0%
A-0010-3019E-6 5
 
5.0%

Length

2023-12-10T22:42:46.901361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:42:47.184431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a-0010-1185e-8 95
95.0%
a-0010-3019e-6 5
 
5.0%

주소
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
대구 동구 안심3동
95 
충북 청주시 흥덕구 강서1동
 
5

Length

Max length15
Median length10
Mean length10.25
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대구 동구 안심3동
2nd row대구 동구 안심3동
3rd row대구 동구 안심3동
4th row대구 동구 안심3동
5th row대구 동구 안심3동

Common Values

ValueCountFrequency (%)
대구 동구 안심3동 95
95.0%
충북 청주시 흥덕구 강서1동 5
 
5.0%

Length

2023-12-10T22:42:47.471711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:42:47.786371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구 95
31.1%
동구 95
31.1%
안심3동 95
31.1%
충북 5
 
1.6%
청주시 5
 
1.6%
흥덕구 5
 
1.6%
강서1동 5
 
1.6%

강수량(mm)
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2023-12-10T22:42:48.142632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:42:48.404291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

강우량(mm)
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2023-12-10T22:42:48.651042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:42:48.834196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

Interactions

2023-12-10T22:42:43.904878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:42:43.549171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:42:44.058767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:42:43.748857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:42:49.012495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키측정시간지점주소
기본키1.0000.9770.8160.816
측정시간0.9771.0000.5850.585
지점0.8160.5851.0000.986
주소0.8160.5850.9861.000
2023-12-10T22:42:49.261141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주소지점
주소1.0000.894
지점0.8941.000
2023-12-10T22:42:49.396383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키측정시간지점주소
기본키1.0000.7290.6220.622
측정시간0.7291.0000.4330.433
지점0.6220.4331.0000.894
주소0.6220.4330.8941.000

Missing values

2023-12-10T22:42:44.287360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:42:44.497365image/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

기본키측정일측정시간지점주소강수량(mm)강우량(mm)
012021010115A-0010-1185E-8대구 동구 안심3동00
122021010130A-0010-1185E-8대구 동구 안심3동00
232021010145A-0010-1185E-8대구 동구 안심3동00
3420210101100A-0010-1185E-8대구 동구 안심3동00
4520210101115A-0010-1185E-8대구 동구 안심3동00
5620210101130A-0010-1185E-8대구 동구 안심3동00
6720210101145A-0010-1185E-8대구 동구 안심3동00
7820210101200A-0010-1185E-8대구 동구 안심3동00
8920210101215A-0010-1185E-8대구 동구 안심3동00
91020210101230A-0010-1185E-8대구 동구 안심3동00
기본키측정일측정시간지점주소강수량(mm)강우량(mm)
9091202101012245A-0010-1185E-8대구 동구 안심3동00
9192202101012300A-0010-1185E-8대구 동구 안심3동00
9293202101012315A-0010-1185E-8대구 동구 안심3동00
9394202101012330A-0010-1185E-8대구 동구 안심3동00
9495202101012345A-0010-1185E-8대구 동구 안심3동00
95962021010115A-0010-3019E-6충북 청주시 흥덕구 강서1동00
96972021010130A-0010-3019E-6충북 청주시 흥덕구 강서1동00
97982021010145A-0010-3019E-6충북 청주시 흥덕구 강서1동00
989920210101100A-0010-3019E-6충북 청주시 흥덕구 강서1동00
9910020210101115A-0010-3019E-6충북 청주시 흥덕구 강서1동00