Overview

Dataset statistics

Number of variables25
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.0 KiB
Average record size in memory227.7 B

Variable types

Categorical6
Numeric18
Text1

Dataset

Description기타 가축통계(면양)
Author농림축산식품부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220216000000001950

Alerts

2013 has constant value ""Constant
1.1 is highly imbalanced (52.2%)Imbalance
0.1 is highly imbalanced (81.7%)Imbalance
0.2 is highly imbalanced (81.7%)Imbalance
0.4 is highly imbalanced (81.7%)Imbalance
0.5 is highly imbalanced (81.7%)Imbalance
1 has unique valuesUnique
'94 has unique valuesUnique
32 has 7 (19.4%) zerosZeros
9 has 8 (22.2%) zerosZeros
5 has 11 (30.6%) zerosZeros
5.1 has 13 (36.1%) zerosZeros
5.2 has 16 (44.4%) zerosZeros
0 has 13 (36.1%) zerosZeros
2 has 12 (33.3%) zerosZeros
5.3 has 15 (41.7%) zerosZeros
1517 has 7 (19.4%) zerosZeros
22 has 7 (19.4%) zerosZeros
34 has 10 (27.8%) zerosZeros
77 has 12 (33.3%) zerosZeros
112 has 15 (41.7%) zerosZeros
0.3 has 13 (36.1%) zerosZeros
182 has 12 (33.3%) zerosZeros
680 has 15 (41.7%) zerosZeros
410 has 30 (83.3%) zerosZeros

Reproduction

Analysis started2023-12-11 03:37:05.687716
Analysis finished2023-12-11 03:37:05.890262
Duration0.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

2013
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
2013
36 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2013
2nd row2013
3rd row2013
4th row2013
5th row2013

Common Values

ValueCountFrequency (%)
2013 36
100.0%

Length

2023-12-11T12:37:05.944552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:37:06.023612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2013 36
100.0%

1
Real number (ℝ)

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.5
Minimum2
Maximum37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T12:37:06.106503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3.75
Q110.75
median19.5
Q328.25
95-th percentile35.25
Maximum37
Range35
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation10.535654
Coefficient of variation (CV)0.54028994
Kurtosis-1.2
Mean19.5
Median Absolute Deviation (MAD)9
Skewness0
Sum702
Variance111
MonotonicityStrictly increasing
2023-12-11T12:37:06.214503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
2 1
 
2.8%
21 1
 
2.8%
23 1
 
2.8%
24 1
 
2.8%
25 1
 
2.8%
26 1
 
2.8%
27 1
 
2.8%
28 1
 
2.8%
29 1
 
2.8%
30 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
2 1
2.8%
3 1
2.8%
4 1
2.8%
5 1
2.8%
6 1
2.8%
7 1
2.8%
8 1
2.8%
9 1
2.8%
10 1
2.8%
11 1
2.8%
ValueCountFrequency (%)
37 1
2.8%
36 1
2.8%
35 1
2.8%
34 1
2.8%
33 1
2.8%
32 1
2.8%
31 1
2.8%
30 1
2.8%
29 1
2.8%
28 1
2.8%

'94
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-11T12:37:06.402387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4.5
Mean length2.6111111
Min length2

Characters and Unicode

Total characters94
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row'95
2nd row'96
3rd row'97
4th row'98
5th row'99
ValueCountFrequency (%)
95 1
 
2.8%
96 1
 
2.8%
경기 1
 
2.8%
부산 1
 
2.8%
대구 1
 
2.8%
인천 1
 
2.8%
광주 1
 
2.8%
대전 1
 
2.8%
울산 1
 
2.8%
강원 1
 
2.8%
Other values (26) 26
72.2%
2023-12-11T12:37:06.738486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 18
19.1%
0 12
 
12.8%
1 7
 
7.4%
9 7
 
7.4%
3
 
3.2%
3
 
3.2%
2 3
 
3.2%
3
 
3.2%
3
 
3.2%
8 2
 
2.1%
Other values (24) 33
35.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40
42.6%
Other Letter 34
36.2%
Other Punctuation 19
20.2%
Initial Punctuation 1
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
 
8.8%
3
 
8.8%
3
 
8.8%
3
 
8.8%
2
 
5.9%
2
 
5.9%
2
 
5.9%
2
 
5.9%
2
 
5.9%
1
 
2.9%
Other values (11) 11
32.4%
Decimal Number
ValueCountFrequency (%)
0 12
30.0%
1 7
17.5%
9 7
17.5%
2 3
 
7.5%
8 2
 
5.0%
7 2
 
5.0%
3 2
 
5.0%
6 2
 
5.0%
5 2
 
5.0%
4 1
 
2.5%
Other Punctuation
ValueCountFrequency (%)
' 18
94.7%
. 1
 
5.3%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60
63.8%
Hangul 34
36.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
 
8.8%
3
 
8.8%
3
 
8.8%
3
 
8.8%
2
 
5.9%
2
 
5.9%
2
 
5.9%
2
 
5.9%
2
 
5.9%
1
 
2.9%
Other values (11) 11
32.4%
Common
ValueCountFrequency (%)
' 18
30.0%
0 12
20.0%
1 7
 
11.7%
9 7
 
11.7%
2 3
 
5.0%
8 2
 
3.3%
7 2
 
3.3%
3 2
 
3.3%
6 2
 
3.3%
5 2
 
3.3%
Other values (3) 3
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59
62.8%
Hangul 34
36.2%
Punctuation 1
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 18
30.5%
0 12
20.3%
1 7
 
11.9%
9 7
 
11.9%
2 3
 
5.1%
8 2
 
3.4%
7 2
 
3.4%
3 2
 
3.4%
6 2
 
3.4%
5 2
 
3.4%
Other values (2) 2
 
3.4%
Hangul
ValueCountFrequency (%)
3
 
8.8%
3
 
8.8%
3
 
8.8%
3
 
8.8%
2
 
5.9%
2
 
5.9%
2
 
5.9%
2
 
5.9%
2
 
5.9%
1
 
2.9%
Other values (11) 11
32.4%
Punctuation
ValueCountFrequency (%)
1
100.0%

32
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.25
Minimum0
Maximum179
Zeros7
Zeros (%)19.4%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T12:37:06.850163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.75
median25
Q365
95-th percentile170.5
Maximum179
Range179
Interquartile range (IQR)61.25

Descriptive statistics

Standard deviation57.822573
Coefficient of variation (CV)1.2778469
Kurtosis0.62248395
Mean45.25
Median Absolute Deviation (MAD)22
Skewness1.3974901
Sum1629
Variance3343.45
MonotonicityNot monotonic
2023-12-11T12:37:06.958513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 7
19.4%
32 3
 
8.3%
33 2
 
5.6%
3 2
 
5.6%
65 2
 
5.6%
4 2
 
5.6%
118 1
 
2.8%
11 1
 
2.8%
12 1
 
2.8%
15 1
 
2.8%
Other values (14) 14
38.9%
ValueCountFrequency (%)
0 7
19.4%
3 2
 
5.6%
4 2
 
5.6%
8 1
 
2.8%
9 1
 
2.8%
10 1
 
2.8%
11 1
 
2.8%
12 1
 
2.8%
15 1
 
2.8%
23 1
 
2.8%
ValueCountFrequency (%)
179 1
2.8%
178 1
2.8%
168 1
2.8%
162 1
2.8%
156 1
2.8%
118 1
2.8%
103 1
2.8%
74 1
2.8%
65 2
5.6%
36 1
2.8%

9
Real number (ℝ)

ZEROS 

Distinct23
Distinct (%)63.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.444444
Minimum0
Maximum94
Zeros8
Zeros (%)22.2%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T12:37:07.062675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7.5
Q327
95-th percentile85.25
Maximum94
Range94
Interquartile range (IQR)26

Descriptive statistics

Standard deviation27.729762
Coefficient of variation (CV)1.426102
Kurtosis1.5150192
Mean19.444444
Median Absolute Deviation (MAD)7.5
Skewness1.6455387
Sum700
Variance768.93968
MonotonicityNot monotonic
2023-12-11T12:37:07.164046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 8
22.2%
5 3
 
8.3%
8 2
 
5.6%
1 2
 
5.6%
9 2
 
5.6%
10 2
 
5.6%
66 1
 
2.8%
2 1
 
2.8%
3 1
 
2.8%
7 1
 
2.8%
Other values (13) 13
36.1%
ValueCountFrequency (%)
0 8
22.2%
1 2
 
5.6%
2 1
 
2.8%
3 1
 
2.8%
4 1
 
2.8%
5 3
 
8.3%
6 1
 
2.8%
7 1
 
2.8%
8 2
 
5.6%
9 2
 
5.6%
ValueCountFrequency (%)
94 1
2.8%
86 1
2.8%
85 1
2.8%
71 1
2.8%
66 1
2.8%
46 1
2.8%
44 1
2.8%
31 1
2.8%
30 1
2.8%
26 1
2.8%

5
Real number (ℝ)

ZEROS 

Distinct19
Distinct (%)52.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.5277778
Minimum0
Maximum42
Zeros11
Zeros (%)30.6%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T12:37:07.274376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3.5
Q313.5
95-th percentile35.5
Maximum42
Range42
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation11.823671
Coefficient of variation (CV)1.3864892
Kurtosis1.7795687
Mean8.5277778
Median Absolute Deviation (MAD)3.5
Skewness1.6149042
Sum307
Variance139.79921
MonotonicityNot monotonic
2023-12-11T12:37:07.400822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 11
30.6%
4 4
 
11.1%
2 4
 
11.1%
1 2
 
5.6%
26 1
 
2.8%
7 1
 
2.8%
17 1
 
2.8%
19 1
 
2.8%
34 1
 
2.8%
21 1
 
2.8%
Other values (9) 9
25.0%
ValueCountFrequency (%)
0 11
30.6%
1 2
 
5.6%
2 4
 
11.1%
3 1
 
2.8%
4 4
 
11.1%
5 1
 
2.8%
6 1
 
2.8%
7 1
 
2.8%
10 1
 
2.8%
13 1
 
2.8%
ValueCountFrequency (%)
42 1
2.8%
40 1
2.8%
34 1
2.8%
26 1
2.8%
23 1
2.8%
21 1
2.8%
19 1
2.8%
17 1
2.8%
15 1
2.8%
13 1
2.8%

5.1
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)36.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4722222
Minimum0
Maximum27
Zeros13
Zeros (%)36.1%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T12:37:07.547110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q35.25
95-th percentile24
Maximum27
Range27
Interquartile range (IQR)5.25

Descriptive statistics

Standard deviation7.9945914
Coefficient of variation (CV)1.4609406
Kurtosis1.6355923
Mean5.4722222
Median Absolute Deviation (MAD)2
Skewness1.6831218
Sum197
Variance63.913492
MonotonicityNot monotonic
2023-12-11T12:37:07.717373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 13
36.1%
5 4
 
11.1%
1 3
 
8.3%
3 3
 
8.3%
2 3
 
8.3%
9 2
 
5.6%
24 2
 
5.6%
6 1
 
2.8%
4 1
 
2.8%
15 1
 
2.8%
Other values (3) 3
 
8.3%
ValueCountFrequency (%)
0 13
36.1%
1 3
 
8.3%
2 3
 
8.3%
3 3
 
8.3%
4 1
 
2.8%
5 4
 
11.1%
6 1
 
2.8%
9 2
 
5.6%
15 1
 
2.8%
18 1
 
2.8%
ValueCountFrequency (%)
27 1
 
2.8%
24 2
5.6%
23 1
 
2.8%
18 1
 
2.8%
15 1
 
2.8%
9 2
5.6%
6 1
 
2.8%
5 4
11.1%
4 1
 
2.8%
3 3
8.3%

5.2
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0833333
Minimum0
Maximum16
Zeros16
Zeros (%)44.4%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T12:37:07.885735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q34
95-th percentile11.25
Maximum16
Range16
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.0523362
Coefficient of variation (CV)1.3142712
Kurtosis2.1073446
Mean3.0833333
Median Absolute Deviation (MAD)2
Skewness1.5671738
Sum111
Variance16.421429
MonotonicityNot monotonic
2023-12-11T12:37:08.063939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 16
44.4%
2 5
 
13.9%
4 4
 
11.1%
3 3
 
8.3%
6 2
 
5.6%
7 1
 
2.8%
8 1
 
2.8%
11 1
 
2.8%
12 1
 
2.8%
16 1
 
2.8%
ValueCountFrequency (%)
0 16
44.4%
2 5
 
13.9%
3 3
 
8.3%
4 4
 
11.1%
6 2
 
5.6%
7 1
 
2.8%
8 1
 
2.8%
10 1
 
2.8%
11 1
 
2.8%
12 1
 
2.8%
ValueCountFrequency (%)
16 1
 
2.8%
12 1
 
2.8%
11 1
 
2.8%
10 1
 
2.8%
8 1
 
2.8%
7 1
 
2.8%
6 2
 
5.6%
4 4
11.1%
3 3
8.3%
2 5
13.9%

0
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8333333
Minimum0
Maximum11
Zeros13
Zeros (%)36.1%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T12:37:08.235798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile10.25
Maximum11
Range11
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.4351128
Coefficient of variation (CV)1.2123928
Kurtosis0.81878292
Mean2.8333333
Median Absolute Deviation (MAD)2
Skewness1.3677792
Sum102
Variance11.8
MonotonicityNot monotonic
2023-12-11T12:37:08.369792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 13
36.1%
3 7
19.4%
2 6
16.7%
10 2
 
5.6%
11 2
 
5.6%
1 2
 
5.6%
4 1
 
2.8%
5 1
 
2.8%
9 1
 
2.8%
7 1
 
2.8%
ValueCountFrequency (%)
0 13
36.1%
1 2
 
5.6%
2 6
16.7%
3 7
19.4%
4 1
 
2.8%
5 1
 
2.8%
7 1
 
2.8%
9 1
 
2.8%
10 2
 
5.6%
11 2
 
5.6%
ValueCountFrequency (%)
11 2
 
5.6%
10 2
 
5.6%
9 1
 
2.8%
7 1
 
2.8%
5 1
 
2.8%
4 1
 
2.8%
3 7
19.4%
2 6
16.7%
1 2
 
5.6%
0 13
36.1%

2
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1388889
Minimum0
Maximum13
Zeros12
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T12:37:08.798435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.5
Q35
95-th percentile10.5
Maximum13
Range13
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.4488323
Coefficient of variation (CV)1.098743
Kurtosis1.4042672
Mean3.1388889
Median Absolute Deviation (MAD)2.5
Skewness1.2606482
Sum113
Variance11.894444
MonotonicityNot monotonic
2023-12-11T12:37:08.950761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 12
33.3%
5 6
16.7%
1 4
 
11.1%
3 3
 
8.3%
4 3
 
8.3%
2 2
 
5.6%
6 2
 
5.6%
13 1
 
2.8%
10 1
 
2.8%
12 1
 
2.8%
ValueCountFrequency (%)
0 12
33.3%
1 4
 
11.1%
2 2
 
5.6%
3 3
 
8.3%
4 3
 
8.3%
5 6
16.7%
6 2
 
5.6%
7 1
 
2.8%
10 1
 
2.8%
12 1
 
2.8%
ValueCountFrequency (%)
13 1
 
2.8%
12 1
 
2.8%
10 1
 
2.8%
7 1
 
2.8%
6 2
 
5.6%
5 6
16.7%
4 3
8.3%
3 3
8.3%
2 2
 
5.6%
1 4
11.1%

5.3
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4444444
Minimum0
Maximum8
Zeros15
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T12:37:09.097990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.5
Q34.25
95-th percentile7
Maximum8
Range8
Interquartile range (IQR)4.25

Descriptive statistics

Standard deviation2.6986181
Coefficient of variation (CV)1.1039801
Kurtosis-1.0413133
Mean2.4444444
Median Absolute Deviation (MAD)1.5
Skewness0.6695888
Sum88
Variance7.2825397
MonotonicityNot monotonic
2023-12-11T12:37:09.200463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 15
41.7%
6 4
 
11.1%
4 3
 
8.3%
7 3
 
8.3%
3 3
 
8.3%
2 3
 
8.3%
1 3
 
8.3%
8 1
 
2.8%
5 1
 
2.8%
ValueCountFrequency (%)
0 15
41.7%
1 3
 
8.3%
2 3
 
8.3%
3 3
 
8.3%
4 3
 
8.3%
5 1
 
2.8%
6 4
 
11.1%
7 3
 
8.3%
8 1
 
2.8%
ValueCountFrequency (%)
8 1
 
2.8%
7 3
 
8.3%
6 4
 
11.1%
5 1
 
2.8%
4 3
 
8.3%
3 3
 
8.3%
2 3
 
8.3%
1 3
 
8.3%
0 15
41.7%

1.1
Categorical

IMBALANCE 

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
0
30 
1
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.8%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 30
83.3%
1 5
 
13.9%
3 1
 
2.8%

Length

2023-12-11T12:37:09.316638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:37:09.429549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
83.3%
1 5
 
13.9%
3 1
 
2.8%

0.1
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
0
35 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 35
97.2%
2 1
 
2.8%

Length

2023-12-11T12:37:09.539611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:37:09.630939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 35
97.2%
2 1
 
2.8%

0.2
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
0
35 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 35
97.2%
1 1
 
2.8%

Length

2023-12-11T12:37:09.729027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:37:09.823643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 35
97.2%
1 1
 
2.8%

1517
Real number (ℝ)

ZEROS 

Distinct30
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1110
Minimum0
Maximum6918
Zeros7
Zeros (%)19.4%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T12:37:09.923923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q133.25
median819
Q31497.25
95-th percentile3080.25
Maximum6918
Range6918
Interquartile range (IQR)1464

Descriptive statistics

Standard deviation1408.669
Coefficient of variation (CV)1.2690712
Kurtosis7.2295434
Mean1110
Median Absolute Deviation (MAD)792
Skewness2.280847
Sum39960
Variance1984348.5
MonotonicityNot monotonic
2023-12-11T12:37:10.040589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 7
 
19.4%
1630 1
 
2.8%
2989 1
 
2.8%
53 1
 
2.8%
40 1
 
2.8%
104 1
 
2.8%
554 1
 
2.8%
350 1
 
2.8%
164 1
 
2.8%
13 1
 
2.8%
Other values (20) 20
55.6%
ValueCountFrequency (%)
0 7
19.4%
9 1
 
2.8%
13 1
 
2.8%
40 1
 
2.8%
53 1
 
2.8%
104 1
 
2.8%
110 1
 
2.8%
164 1
 
2.8%
350 1
 
2.8%
554 1
 
2.8%
ValueCountFrequency (%)
6918 1
2.8%
3216 1
2.8%
3035 1
2.8%
2989 1
2.8%
2971 1
2.8%
2522 1
2.8%
1800 1
2.8%
1630 1
2.8%
1624 1
2.8%
1455 1
2.8%

22
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.583333
Minimum0
Maximum274
Zeros7
Zeros (%)19.4%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T12:37:10.152243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.5
median18.5
Q365.75
95-th percentile197
Maximum274
Range274
Interquartile range (IQR)61.25

Descriptive statistics

Standard deviation68.777228
Coefficient of variation (CV)1.4454059
Kurtosis3.0350451
Mean47.583333
Median Absolute Deviation (MAD)18
Skewness1.9011372
Sum1713
Variance4730.3071
MonotonicityNot monotonic
2023-12-11T12:37:10.252207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 7
19.4%
19 2
 
5.6%
12 2
 
5.6%
153 2
 
5.6%
24 1
 
2.8%
3 1
 
2.8%
8 1
 
2.8%
5 1
 
2.8%
16 1
 
2.8%
1 1
 
2.8%
Other values (17) 17
47.2%
ValueCountFrequency (%)
0 7
19.4%
1 1
 
2.8%
3 1
 
2.8%
5 1
 
2.8%
8 1
 
2.8%
9 1
 
2.8%
10 1
 
2.8%
12 2
 
5.6%
16 1
 
2.8%
17 1
 
2.8%
ValueCountFrequency (%)
274 1
2.8%
215 1
2.8%
191 1
2.8%
153 2
5.6%
102 1
2.8%
94 1
2.8%
86 1
2.8%
71 1
2.8%
64 1
2.8%
39 1
2.8%

34
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)69.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.861111
Minimum0
Maximum335
Zeros10
Zeros (%)27.8%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T12:37:10.350560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median24
Q386.25
95-th percentile231.5
Maximum335
Range335
Interquartile range (IQR)86.25

Descriptive statistics

Standard deviation80.769567
Coefficient of variation (CV)1.4458998
Kurtosis4.103293
Mean55.861111
Median Absolute Deviation (MAD)24
Skewness2.0500183
Sum2011
Variance6523.723
MonotonicityNot monotonic
2023-12-11T12:37:10.454023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 10
27.8%
28 2
 
5.6%
12 2
 
5.6%
27 1
 
2.8%
136 1
 
2.8%
7 1
 
2.8%
14 1
 
2.8%
10 1
 
2.8%
5 1
 
2.8%
46 1
 
2.8%
Other values (15) 15
41.7%
ValueCountFrequency (%)
0 10
27.8%
5 1
 
2.8%
7 1
 
2.8%
10 1
 
2.8%
12 2
 
5.6%
14 1
 
2.8%
20 1
 
2.8%
21 1
 
2.8%
27 1
 
2.8%
28 2
 
5.6%
ValueCountFrequency (%)
335 1
2.8%
272 1
2.8%
218 1
2.8%
160 1
2.8%
136 1
2.8%
116 1
2.8%
106 1
2.8%
94 1
2.8%
93 1
2.8%
84 1
2.8%

77
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)69.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.25
Minimum0
Maximum320
Zeros12
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T12:37:10.564448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median30
Q372.5
95-th percentile302.75
Maximum320
Range320
Interquartile range (IQR)72.5

Descriptive statistics

Standard deviation100.32729
Coefficient of variation (CV)1.388613
Kurtosis1.266059
Mean72.25
Median Absolute Deviation (MAD)30
Skewness1.5945992
Sum2601
Variance10065.564
MonotonicityNot monotonic
2023-12-11T12:37:10.668906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 12
33.3%
74 1
 
2.8%
13 1
 
2.8%
14 1
 
2.8%
29 1
 
2.8%
15 1
 
2.8%
31 1
 
2.8%
26 1
 
2.8%
115 1
 
2.8%
259 1
 
2.8%
Other values (15) 15
41.7%
ValueCountFrequency (%)
0 12
33.3%
13 1
 
2.8%
14 1
 
2.8%
15 1
 
2.8%
25 1
 
2.8%
26 1
 
2.8%
29 1
 
2.8%
31 1
 
2.8%
41 1
 
2.8%
42 1
 
2.8%
ValueCountFrequency (%)
320 1
2.8%
305 1
2.8%
302 1
2.8%
290 1
2.8%
259 1
2.8%
195 1
2.8%
115 1
2.8%
112 1
2.8%
74 1
2.8%
72 1
2.8%

112
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.166667
Minimum0
Maximum401
Zeros15
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T12:37:10.774598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median47
Q393
95-th percentile252.75
Maximum401
Range401
Interquartile range (IQR)93

Descriptive statistics

Standard deviation96.796547
Coefficient of variation (CV)1.305122
Kurtosis2.7297098
Mean74.166667
Median Absolute Deviation (MAD)47
Skewness1.676967
Sum2670
Variance9369.5714
MonotonicityNot monotonic
2023-12-11T12:37:10.882580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 15
41.7%
93 3
 
8.3%
40 2
 
5.6%
148 2
 
5.6%
243 1
 
2.8%
50 1
 
2.8%
58 1
 
2.8%
249 1
 
2.8%
401 1
 
2.8%
264 1
 
2.8%
Other values (8) 8
22.2%
ValueCountFrequency (%)
0 15
41.7%
40 2
 
5.6%
46 1
 
2.8%
48 1
 
2.8%
50 1
 
2.8%
58 1
 
2.8%
64 1
 
2.8%
70 1
 
2.8%
79 1
 
2.8%
87 1
 
2.8%
ValueCountFrequency (%)
401 1
 
2.8%
264 1
 
2.8%
249 1
 
2.8%
243 1
 
2.8%
228 1
 
2.8%
148 2
5.6%
128 1
 
2.8%
93 3
8.3%
87 1
 
2.8%
79 1
 
2.8%

0.3
Real number (ℝ)

ZEROS 

Distinct23
Distinct (%)63.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean102.41667
Minimum0
Maximum423
Zeros13
Zeros (%)36.1%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T12:37:10.995859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median67.5
Q3111.5
95-th percentile372
Maximum423
Range423
Interquartile range (IQR)111.5

Descriptive statistics

Standard deviation126.08917
Coefficient of variation (CV)1.2311392
Kurtosis1.0897943
Mean102.41667
Median Absolute Deviation (MAD)67.5
Skewness1.441051
Sum3687
Variance15898.479
MonotonicityNot monotonic
2023-12-11T12:37:11.104214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 13
36.1%
110 2
 
5.6%
62 1
 
2.8%
45 1
 
2.8%
65 1
 
2.8%
49 1
 
2.8%
95 1
 
2.8%
254 1
 
2.8%
356 1
 
2.8%
423 1
 
2.8%
Other values (13) 13
36.1%
ValueCountFrequency (%)
0 13
36.1%
45 1
 
2.8%
49 1
 
2.8%
60 1
 
2.8%
62 1
 
2.8%
65 1
 
2.8%
70 1
 
2.8%
72 1
 
2.8%
85 1
 
2.8%
92 1
 
2.8%
ValueCountFrequency (%)
423 1
2.8%
414 1
2.8%
358 1
2.8%
356 1
2.8%
317 1
2.8%
254 1
2.8%
171 1
2.8%
158 1
2.8%
116 1
2.8%
110 2
5.6%

182
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean205
Minimum0
Maximum875
Zeros12
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T12:37:11.253320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median179
Q3330
95-th percentile665.25
Maximum875
Range875
Interquartile range (IQR)330

Descriptive statistics

Standard deviation223.98087
Coefficient of variation (CV)1.0925896
Kurtosis1.6679258
Mean205
Median Absolute Deviation (MAD)170.5
Skewness1.2845343
Sum7380
Variance50167.429
MonotonicityNot monotonic
2023-12-11T12:37:11.375393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 12
33.3%
330 2
 
5.6%
232 1
 
2.8%
251 1
 
2.8%
51 1
 
2.8%
99 1
 
2.8%
147 1
 
2.8%
417 1
 
2.8%
60 1
 
2.8%
774 1
 
2.8%
Other values (14) 14
38.9%
ValueCountFrequency (%)
0 12
33.3%
51 1
 
2.8%
60 1
 
2.8%
72 1
 
2.8%
80 1
 
2.8%
99 1
 
2.8%
147 1
 
2.8%
211 1
 
2.8%
222 1
 
2.8%
232 1
 
2.8%
ValueCountFrequency (%)
875 1
2.8%
774 1
2.8%
629 1
2.8%
417 1
2.8%
392 1
2.8%
358 1
2.8%
341 1
2.8%
333 1
2.8%
330 2
5.6%
320 1
2.8%

680
Real number (ℝ)

ZEROS 

Distinct22
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean406.97222
Minimum0
Maximum1336
Zeros15
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T12:37:11.502169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median249
Q3663.75
95-th percentile1325.75
Maximum1336
Range1336
Interquartile range (IQR)663.75

Descriptive statistics

Standard deviation466.15892
Coefficient of variation (CV)1.1454318
Kurtosis-0.58477303
Mean406.97222
Median Absolute Deviation (MAD)249
Skewness0.86138012
Sum14651
Variance217304.14
MonotonicityNot monotonic
2023-12-11T12:37:11.649244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 15
41.7%
675 1
 
2.8%
660 1
 
2.8%
103 1
 
2.8%
519 1
 
2.8%
622 1
 
2.8%
1002 1
 
2.8%
1131 1
 
2.8%
1336 1
 
2.8%
1323 1
 
2.8%
Other values (12) 12
33.3%
ValueCountFrequency (%)
0 15
41.7%
103 1
 
2.8%
200 1
 
2.8%
220 1
 
2.8%
278 1
 
2.8%
336 1
 
2.8%
362 1
 
2.8%
425 1
 
2.8%
519 1
 
2.8%
520 1
 
2.8%
ValueCountFrequency (%)
1336 1
2.8%
1334 1
2.8%
1323 1
2.8%
1261 1
2.8%
1131 1
2.8%
1058 1
2.8%
1002 1
2.8%
730 1
2.8%
675 1
2.8%
660 1
2.8%

410
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.388889
Minimum0
Maximum1170
Zeros30
Zeros (%)83.3%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-11T12:37:11.776986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile401
Maximum1170
Range1170
Interquartile range (IQR)0

Descriptive statistics

Standard deviation226.72
Coefficient of variation (CV)2.7188275
Kurtosis15.106253
Mean83.388889
Median Absolute Deviation (MAD)0
Skewness3.5993821
Sum3002
Variance51401.959
MonotonicityNot monotonic
2023-12-11T12:37:11.891202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 30
83.3%
401 2
 
5.6%
400 1
 
2.8%
300 1
 
2.8%
1170 1
 
2.8%
330 1
 
2.8%
ValueCountFrequency (%)
0 30
83.3%
300 1
 
2.8%
330 1
 
2.8%
400 1
 
2.8%
401 2
 
5.6%
1170 1
 
2.8%
ValueCountFrequency (%)
1170 1
 
2.8%
401 2
 
5.6%
400 1
 
2.8%
330 1
 
2.8%
300 1
 
2.8%
0 30
83.3%

0.4
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
0
35 
1050
 
1

Length

Max length4
Median length1
Mean length1.0833333
Min length1

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 35
97.2%
1050 1
 
2.8%

Length

2023-12-11T12:37:12.028142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:37:12.146056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 35
97.2%
1050 1
 
2.8%

0.5
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
0
35 
1200
 
1

Length

Max length4
Median length1
Mean length1.0833333
Min length1

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 35
97.2%
1200 1
 
2.8%

Length

2023-12-11T12:37:12.269673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:37:12.389073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 35
97.2%
1200 1
 
2.8%

Sample

20131'9432955.15.2025.31.10.10.215172234771120.31826804100.40.5
020132'9533846433410016301927749311023267540000
120133'96321061322800016242440137962721334000
220134'973210433417000145526284164158801058000
320135'98345105323600012421064617085222730000
420136'99321242235400010882928254897341520000
520137'00900003330008292120420110211425000
620138'012384302420008093929724072279278000
720139'02361654235100079122345346116320200000
8201310'032763542520009521821689360330362000
9201311'0465311554361000105786947087108392220000
20131'9432955.15.2025.31.10.10.215172234771120.31826804100.40.5
26201328경기10522001000011012122600600000
27201329강원3397303740001125174631095417519000
28201330충북312000000001311200000000
29201331충남851000200001641250001470000
30201332전북157212111000350161015584999103000
31201333전남1232222001005545142940650040100
32201334경북42000110000104800045510000
33201335경남11911000000040197140000000
34201336제주310020000005330050000000
35201337세종0000000000000000000000