Overview

Dataset statistics

Number of variables80
Number of observations63
Missing cells1885
Missing cells (%)37.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory43.9 KiB
Average record size in memory714.1 B

Variable types

Text1
Categorical41
Numeric31
Unsupported7

Dataset

Description법정감염병 중 4군에 속하는 모기매개 감염병인 뎅기열, 치쿤구니야열, 지카바이러스감염증의 국가별 발생현황. (단위: 건) * 국가명이 2개 이상인 경우, 추정하는 지역이 2개 이상임을 의미함.
Author질병관리청
URLhttps://www.data.go.kr/data/15033739/fileData.do

Alerts

Unnamed: 1 is highly imbalanced (73.1%)Imbalance
Unnamed: 2 is highly imbalanced (68.5%)Imbalance
Unnamed: 3 is highly imbalanced (79.8%)Imbalance
Unnamed: 4 is highly imbalanced (79.8%)Imbalance
Unnamed: 5 is highly imbalanced (79.8%)Imbalance
Unnamed: 6 is highly imbalanced (73.1%)Imbalance
Unnamed: 7 is highly imbalanced (72.6%)Imbalance
Unnamed: 10 is highly imbalanced (69.5%)Imbalance
Unnamed: 11 is highly imbalanced (68.5%)Imbalance
Unnamed: 12 is highly imbalanced (79.8%)Imbalance
Unnamed: 14 is highly imbalanced (68.5%)Imbalance
Unnamed: 15 is highly imbalanced (74.6%)Imbalance
Unnamed: 16 is highly imbalanced (68.5%)Imbalance
Unnamed: 17 is highly imbalanced (70.4%)Imbalance
Unnamed: 18 is highly imbalanced (79.8%)Imbalance
Unnamed: 19 is highly imbalanced (76.2%)Imbalance
Unnamed: 20 is highly imbalanced (71.4%)Imbalance
Unnamed: 22 is highly imbalanced (68.2%)Imbalance
Unnamed: 23 is highly imbalanced (66.7%)Imbalance
Unnamed: 25 is highly imbalanced (69.5%)Imbalance
Unnamed: 27 is highly imbalanced (66.7%)Imbalance
Unnamed: 28 is highly imbalanced (66.8%)Imbalance
Unnamed: 29 is highly imbalanced (66.8%)Imbalance
Unnamed: 30 is highly imbalanced (76.2%)Imbalance
Unnamed: 31 is highly imbalanced (70.4%)Imbalance
Unnamed: 37 is highly imbalanced (67.9%)Imbalance
Unnamed: 38 is highly imbalanced (74.2%)Imbalance
Unnamed: 40 is highly imbalanced (60.8%)Imbalance
Unnamed: 41 is highly imbalanced (71.4%)Imbalance
Unnamed: 42 is highly imbalanced (76.2%)Imbalance
Unnamed: 43 is highly imbalanced (73.1%)Imbalance
Unnamed: 45 is highly imbalanced (61.5%)Imbalance
Unnamed: 47 is highly imbalanced (59.7%)Imbalance
Unnamed: 48 is highly imbalanced (68.2%)Imbalance
Unnamed: 50 is highly imbalanced (64.7%)Imbalance
Unnamed: 51 is highly imbalanced (76.2%)Imbalance
Unnamed: 54 is highly imbalanced (66.8%)Imbalance
Unnamed: 55 is highly imbalanced (66.7%)Imbalance
Unnamed: 56 is highly imbalanced (68.2%)Imbalance
Unnamed: 58 is highly imbalanced (68.9%)Imbalance
Unnamed: 75 is highly imbalanced (66.7%)Imbalance
뎅기열 has 3 (4.8%) missing valuesMissing
Unnamed: 8 has 53 (84.1%) missing valuesMissing
Unnamed: 9 has 56 (88.9%) missing valuesMissing
Unnamed: 13 has 49 (77.8%) missing valuesMissing
Unnamed: 21 has 54 (85.7%) missing valuesMissing
Unnamed: 24 has 55 (87.3%) missing valuesMissing
Unnamed: 26 has 48 (76.2%) missing valuesMissing
Unnamed: 32 has 56 (88.9%) missing valuesMissing
Unnamed: 33 has 51 (81.0%) missing valuesMissing
Unnamed: 34 has 49 (77.8%) missing valuesMissing
Unnamed: 35 has 50 (79.4%) missing valuesMissing
Unnamed: 36 has 50 (79.4%) missing valuesMissing
Unnamed: 39 has 36 (57.1%) missing valuesMissing
Unnamed: 44 has 57 (90.5%) missing valuesMissing
Unnamed: 46 has 53 (84.1%) missing valuesMissing
Unnamed: 49 has 52 (82.5%) missing valuesMissing
Unnamed: 52 has 37 (58.7%) missing valuesMissing
Unnamed: 53 has 55 (87.3%) missing valuesMissing
Unnamed: 57 has 53 (84.1%) missing valuesMissing
Unnamed: 59 has 53 (84.1%) missing valuesMissing
Unnamed: 60 has 52 (82.5%) missing valuesMissing
Unnamed: 61 has 53 (84.1%) missing valuesMissing
Unnamed: 62 has 49 (77.8%) missing valuesMissing
Unnamed: 63 has 50 (79.4%) missing valuesMissing
Unnamed: 64 has 52 (82.5%) missing valuesMissing
Unnamed: 65 has 34 (54.0%) missing valuesMissing
Unnamed: 66 has 52 (82.5%) missing valuesMissing
Unnamed: 67 has 52 (82.5%) missing valuesMissing
Unnamed: 68 has 50 (79.4%) missing valuesMissing
Unnamed: 69 has 52 (82.5%) missing valuesMissing
Unnamed: 70 has 52 (82.5%) missing valuesMissing
Unnamed: 71 has 55 (87.3%) missing valuesMissing
Unnamed: 72 has 53 (84.1%) missing valuesMissing
Unnamed: 73 has 51 (81.0%) missing valuesMissing
Unnamed: 74 has 54 (85.7%) missing valuesMissing
Unnamed: 76 has 55 (87.3%) missing valuesMissing
Unnamed: 77 has 56 (88.9%) missing valuesMissing
Unnamed: 78 has 41 (65.1%) missing valuesMissing
Unnamed: 79 has 2 (3.2%) missing valuesMissing
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 26 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 39 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 52 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 65 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 78 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 79 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 04:52:55.648031
Analysis finished2023-12-12 04:52:56.588784
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

뎅기열
Text

MISSING 

Distinct60
Distinct (%)100.0%
Missing3
Missing (%)4.8%
Memory size636.0 B
2023-12-12T13:52:56.843409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length10
Mean length5.2666667
Min length2

Characters and Unicode

Total characters316
Distinct characters81
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st row가나
2nd row과테말라
3rd row기니
4th row네팔
5th row대만
ValueCountFrequency (%)
가나 1
 
1.7%
과테말라 1
 
1.7%
싱가포르 1
 
1.7%
싱가포르,말레이시아 1
 
1.7%
싱가포르,인도네시아 1
 
1.7%
아이티 1
 
1.7%
앙골라 1
 
1.7%
에티오피아 1
 
1.7%
인도 1
 
1.7%
인도,태국 1
 
1.7%
Other values (50) 50
83.3%
2023-12-12T13:52:57.368594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 25
 
7.9%
아 22
 
7.0%
시 17
 
5.4%
라 14
 
4.4%
도 11
 
3.5%
인 10
 
3.2%
이 10
 
3.2%
스 10
 
3.2%
국 8
 
2.5%
네 8
 
2.5%
Other values (71) 181
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 291
92.1%
Other Punctuation 25
 
7.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 22
 
7.6%
시 17
 
5.8%
라 14
 
4.8%
도 11
 
3.8%
인 10
 
3.4%
이 10
 
3.4%
스 10
 
3.4%
국 8
 
2.7%
네 8
 
2.7%
오 7
 
2.4%
Other values (70) 174
59.8%
Other Punctuation
ValueCountFrequency (%)
, 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 291
92.1%
Common 25
 
7.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 22
 
7.6%
시 17
 
5.8%
라 14
 
4.8%
도 11
 
3.8%
인 10
 
3.4%
이 10
 
3.4%
스 10
 
3.4%
국 8
 
2.7%
네 8
 
2.7%
오 7
 
2.4%
Other values (70) 174
59.8%
Common
ValueCountFrequency (%)
, 25
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 291
92.1%
ASCII 25
 
7.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 25
100.0%
Hangul
ValueCountFrequency (%)
아 22
 
7.6%
시 17
 
5.8%
라 14
 
4.8%
도 11
 
3.8%
인 10
 
3.4%
이 10
 
3.4%
스 10
 
3.4%
국 8
 
2.7%
네 8
 
2.7%
오 7
 
2.4%
Other values (70) 174
59.8%

Unnamed: 1
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
57 
1
 
3
2011
 
1
4
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.7619048
Min length1

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row2011
3rd row1
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 57
90.5%
1 3
 
4.8%
2011 1
 
1.6%
4 1
 
1.6%
6 1
 
1.6%

Length

2023-12-12T13:52:57.551407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:52:57.702817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 57
90.5%
1 3
 
4.8%
2011 1
 
1.6%
4 1
 
1.6%
6 1
 
1.6%

Unnamed: 2
Categorical

IMBALANCE 

Distinct4
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
56 
1
 
5
2
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.6666667
Min length1

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st row<NA>
2nd row<NA>
3rd row2
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 56
88.9%
1 5
 
7.9%
2 1
 
1.6%
5 1
 
1.6%

Length

2023-12-12T13:52:57.844097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:52:57.959603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 56
88.9%
1 5
 
7.9%
2 1
 
1.6%
5 1
 
1.6%

Unnamed: 3
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
60 
1
 
2
3
 
1

Length

Max length4
Median length4
Mean length3.8571429
Min length1

Unique

Unique1 ?
Unique (%)1.6%

Sample

1st row<NA>
2nd row<NA>
3rd row3
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 60
95.2%
1 2
 
3.2%
3 1
 
1.6%

Length

2023-12-12T13:52:58.090018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:52:58.266714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 60
95.2%
1 2
 
3.2%
3 1
 
1.6%

Unnamed: 4
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
60 
1
 
2
4
 
1

Length

Max length4
Median length4
Mean length3.8571429
Min length1

Unique

Unique1 ?
Unique (%)1.6%

Sample

1st row<NA>
2nd row<NA>
3rd row4
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 60
95.2%
1 2
 
3.2%
4 1
 
1.6%

Length

2023-12-12T13:52:58.403868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:52:58.534989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 60
95.2%
1 2
 
3.2%
4 1
 
1.6%

Unnamed: 5
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
60 
1
 
2
5
 
1

Length

Max length4
Median length4
Mean length3.8571429
Min length1

Unique

Unique1 ?
Unique (%)1.6%

Sample

1st row<NA>
2nd row<NA>
3rd row5
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 60
95.2%
1 2
 
3.2%
5 1
 
1.6%

Length

2023-12-12T13:52:58.662426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:52:58.781950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 60
95.2%
1 2
 
3.2%
5 1
 
1.6%

Unnamed: 6
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
57 
1
 
3
6
 
1
2
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.7142857
Min length1

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row<NA>
3rd row6
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 57
90.5%
1 3
 
4.8%
6 1
 
1.6%
2 1
 
1.6%
5 1
 
1.6%

Length

2023-12-12T13:52:58.917570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:52:59.066419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 57
90.5%
1 3
 
4.8%
6 1
 
1.6%
2 1
 
1.6%
5 1
 
1.6%

Unnamed: 7
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
57 
7
 
2
1
 
2
2
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.7142857
Min length1

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st row<NA>
2nd row<NA>
3rd row7
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 57
90.5%
7 2
 
3.2%
1 2
 
3.2%
2 1
 
1.6%
3 1
 
1.6%

Length

2023-12-12T13:52:59.222691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:52:59.358511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 57
90.5%
7 2
 
3.2%
1 2
 
3.2%
2 1
 
1.6%
3 1
 
1.6%

Unnamed: 8
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)60.0%
Missing53
Missing (%)84.1%
Infinite0
Infinite (%)0.0%
Mean4.2
Minimum1
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:52:59.486415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1.5
Q36
95-th percentile12.95
Maximum17
Range16
Interquartile range (IQR)5

Descriptive statistics

Standard deviation5.2025635
Coefficient of variation (CV)1.2387056
Kurtosis3.9020342
Mean4.2
Median Absolute Deviation (MAD)0.5
Skewness1.9704193
Sum42
Variance27.066667
MonotonicityNot monotonic
2023-12-12T13:52:59.618527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 5
 
7.9%
8 1
 
1.6%
2 1
 
1.6%
7 1
 
1.6%
3 1
 
1.6%
17 1
 
1.6%
(Missing) 53
84.1%
ValueCountFrequency (%)
1 5
7.9%
2 1
 
1.6%
3 1
 
1.6%
7 1
 
1.6%
8 1
 
1.6%
17 1
 
1.6%
ValueCountFrequency (%)
17 1
 
1.6%
8 1
 
1.6%
7 1
 
1.6%
3 1
 
1.6%
2 1
 
1.6%
1 5
7.9%

Unnamed: 9
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)85.7%
Missing56
Missing (%)88.9%
Infinite0
Infinite (%)0.0%
Mean5
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:52:59.735016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.3
Q12.5
median3
Q36.5
95-th percentile11.8
Maximum13
Range12
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.3588989
Coefficient of variation (CV)0.87177979
Kurtosis0.70415512
Mean5
Median Absolute Deviation (MAD)1
Skewness1.3185367
Sum35
Variance19
MonotonicityNot monotonic
2023-12-12T13:52:59.863303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 2
 
3.2%
9 1
 
1.6%
1 1
 
1.6%
4 1
 
1.6%
2 1
 
1.6%
13 1
 
1.6%
(Missing) 56
88.9%
ValueCountFrequency (%)
1 1
1.6%
2 1
1.6%
3 2
3.2%
4 1
1.6%
9 1
1.6%
13 1
1.6%
ValueCountFrequency (%)
13 1
1.6%
9 1
1.6%
4 1
1.6%
3 2
3.2%
2 1
1.6%
1 1
1.6%

Unnamed: 10
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
56 
1
 
3
2
 
2
10
 
1
7
 
1

Length

Max length4
Median length4
Mean length3.6825397
Min length1

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st row<NA>
2nd row<NA>
3rd row10
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 56
88.9%
1 3
 
4.8%
2 2
 
3.2%
10 1
 
1.6%
7 1
 
1.6%

Length

2023-12-12T13:53:00.043199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:00.171472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 56
88.9%
1 3
 
4.8%
2 2
 
3.2%
10 1
 
1.6%
7 1
 
1.6%

Unnamed: 11
Categorical

IMBALANCE 

Distinct4
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
56 
1
 
5
11
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.6825397
Min length1

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st row<NA>
2nd row<NA>
3rd row11
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 56
88.9%
1 5
 
7.9%
11 1
 
1.6%
5 1
 
1.6%

Length

2023-12-12T13:53:00.299659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:00.448075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 56
88.9%
1 5
 
7.9%
11 1
 
1.6%
5 1
 
1.6%

Unnamed: 12
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
59 
12
 
1
3
 
1
1
 
1
4
 
1

Length

Max length4
Median length4
Mean length3.8253968
Min length1

Unique

Unique4 ?
Unique (%)6.3%

Sample

1st row<NA>
2nd row<NA>
3rd row12
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 59
93.7%
12 1
 
1.6%
3 1
 
1.6%
1 1
 
1.6%
4 1
 
1.6%

Length

2023-12-12T13:53:00.610589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:00.744756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
93.7%
12 1
 
1.6%
3 1
 
1.6%
1 1
 
1.6%
4 1
 
1.6%

Unnamed: 13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing49
Missing (%)77.8%
Memory size636.0 B

Unnamed: 14
Categorical

IMBALANCE 

Distinct4
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
56 
1
 
5
2012
 
1
4
 
1

Length

Max length4
Median length4
Mean length3.7142857
Min length1

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st row<NA>
2nd row2012
3rd row1
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 56
88.9%
1 5
 
7.9%
2012 1
 
1.6%
4 1
 
1.6%

Length

2023-12-12T13:53:00.879553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:01.006999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 56
88.9%
1 5
 
7.9%
2012 1
 
1.6%
4 1
 
1.6%

Unnamed: 15
Categorical

IMBALANCE 

Distinct4
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
58 
2
 
3
3
 
1
7
 
1

Length

Max length4
Median length4
Mean length3.7619048
Min length1

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st row<NA>
2nd row<NA>
3rd row2
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 58
92.1%
2 3
 
4.8%
3 1
 
1.6%
7 1
 
1.6%

Length

2023-12-12T13:53:01.142041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:01.278670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 58
92.1%
2 3
 
4.8%
3 1
 
1.6%
7 1
 
1.6%

Unnamed: 16
Categorical

IMBALANCE 

Distinct4
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
56 
1
 
5
3
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.6666667
Min length1

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st row<NA>
2nd row<NA>
3rd row3
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 56
88.9%
1 5
 
7.9%
3 1
 
1.6%
5 1
 
1.6%

Length

2023-12-12T13:53:01.401745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:01.526843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 56
88.9%
1 5
 
7.9%
3 1
 
1.6%
5 1
 
1.6%

Unnamed: 17
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
56 
1
 
4
4
 
1
2
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.6666667
Min length1

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row<NA>
3rd row4
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 56
88.9%
1 4
 
6.3%
4 1
 
1.6%
2 1
 
1.6%
6 1
 
1.6%

Length

2023-12-12T13:53:01.701741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:01.885654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 56
88.9%
1 4
 
6.3%
4 1
 
1.6%
2 1
 
1.6%
6 1
 
1.6%

Unnamed: 18
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
59 
5
 
1
1
 
1
2
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.8095238
Min length1

Unique

Unique4 ?
Unique (%)6.3%

Sample

1st row<NA>
2nd row<NA>
3rd row5
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 59
93.7%
5 1
 
1.6%
1 1
 
1.6%
2 1
 
1.6%
3 1
 
1.6%

Length

2023-12-12T13:53:02.096273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:02.285502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
93.7%
5 1
 
1.6%
1 1
 
1.6%
2 1
 
1.6%
3 1
 
1.6%

Unnamed: 19
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
58 
6
 
2
1
 
1
2
 
1
9
 
1

Length

Max length4
Median length4
Mean length3.7619048
Min length1

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row<NA>
3rd row6
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 58
92.1%
6 2
 
3.2%
1 1
 
1.6%
2 1
 
1.6%
9 1
 
1.6%

Length

2023-12-12T13:53:02.501418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:02.686961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 58
92.1%
6 2
 
3.2%
1 1
 
1.6%
2 1
 
1.6%
9 1
 
1.6%

Unnamed: 20
Categorical

IMBALANCE 

Distinct6
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
56 
2
 
3
7
 
1
5
 
1
9
 
1

Length

Max length4
Median length4
Mean length3.6825397
Min length1

Unique

Unique4 ?
Unique (%)6.3%

Sample

1st row<NA>
2nd row<NA>
3rd row7
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 56
88.9%
2 3
 
4.8%
7 1
 
1.6%
5 1
 
1.6%
9 1
 
1.6%
20 1
 
1.6%

Length

2023-12-12T13:53:02.854618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:03.030813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 56
88.9%
2 3
 
4.8%
7 1
 
1.6%
5 1
 
1.6%
9 1
 
1.6%
20 1
 
1.6%

Unnamed: 21
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)66.7%
Missing54
Missing (%)85.7%
Infinite0
Infinite (%)0.0%
Mean6.6666667
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:03.161254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q38
95-th percentile20.8
Maximum26
Range25
Interquartile range (IQR)7

Descriptive statistics

Standard deviation8.3516465
Coefficient of variation (CV)1.252747
Kurtosis3.4464173
Mean6.6666667
Median Absolute Deviation (MAD)2
Skewness1.8499438
Sum60
Variance69.75
MonotonicityNot monotonic
2023-12-12T13:53:03.282744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 4
 
6.3%
8 1
 
1.6%
6 1
 
1.6%
3 1
 
1.6%
13 1
 
1.6%
26 1
 
1.6%
(Missing) 54
85.7%
ValueCountFrequency (%)
1 4
6.3%
3 1
 
1.6%
6 1
 
1.6%
8 1
 
1.6%
13 1
 
1.6%
26 1
 
1.6%
ValueCountFrequency (%)
26 1
 
1.6%
13 1
 
1.6%
8 1
 
1.6%
6 1
 
1.6%
3 1
 
1.6%
1 4
6.3%

Unnamed: 22
Categorical

IMBALANCE 

Distinct6
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
55 
1
 
3
9
 
2
5
 
1
7
 
1

Length

Max length4
Median length4
Mean length3.6349206
Min length1

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row<NA>
3rd row9
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 55
87.3%
1 3
 
4.8%
9 2
 
3.2%
5 1
 
1.6%
7 1
 
1.6%
24 1
 
1.6%

Length

2023-12-12T13:53:03.469523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:03.639998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 55
87.3%
1 3
 
4.8%
9 2
 
3.2%
5 1
 
1.6%
7 1
 
1.6%
24 1
 
1.6%

Unnamed: 23
Categorical

IMBALANCE 

Distinct6
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
54 
1
 
5
10
 
1
2
 
1
11
 
1

Length

Max length4
Median length4
Mean length3.6190476
Min length1

Unique

Unique4 ?
Unique (%)6.3%

Sample

1st row<NA>
2nd row<NA>
3rd row10
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 54
85.7%
1 5
 
7.9%
10 1
 
1.6%
2 1
 
1.6%
11 1
 
1.6%
18 1
 
1.6%

Length

2023-12-12T13:53:03.811328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:03.992099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 54
85.7%
1 5
 
7.9%
10 1
 
1.6%
2 1
 
1.6%
11 1
 
1.6%
18 1
 
1.6%

Unnamed: 24
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)87.5%
Missing55
Missing (%)87.3%
Infinite0
Infinite (%)0.0%
Mean5.375
Minimum1
Maximum16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:04.157266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11.75
median3.5
Q36.5
95-th percentile14.25
Maximum16
Range15
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation5.3702221
Coefficient of variation (CV)0.99911109
Kurtosis1.1364743
Mean5.375
Median Absolute Deviation (MAD)2
Skewness1.4210919
Sum43
Variance28.839286
MonotonicityNot monotonic
2023-12-12T13:53:04.313060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 2
 
3.2%
11 1
 
1.6%
3 1
 
1.6%
2 1
 
1.6%
4 1
 
1.6%
5 1
 
1.6%
16 1
 
1.6%
(Missing) 55
87.3%
ValueCountFrequency (%)
1 2
3.2%
2 1
1.6%
3 1
1.6%
4 1
1.6%
5 1
1.6%
11 1
1.6%
16 1
1.6%
ValueCountFrequency (%)
16 1
1.6%
11 1
1.6%
5 1
1.6%
4 1
1.6%
3 1
1.6%
2 1
1.6%
1 2
3.2%

Unnamed: 25
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
56 
1
 
3
4
 
2
12
 
1
11
 
1

Length

Max length4
Median length4
Mean length3.6984127
Min length1

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st row<NA>
2nd row<NA>
3rd row12
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 56
88.9%
1 3
 
4.8%
4 2
 
3.2%
12 1
 
1.6%
11 1
 
1.6%

Length

2023-12-12T13:53:04.518135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:04.678980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 56
88.9%
1 3
 
4.8%
4 2
 
3.2%
12 1
 
1.6%
11 1
 
1.6%

Unnamed: 26
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)76.2%
Memory size636.0 B

Unnamed: 27
Categorical

IMBALANCE 

Distinct6
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
54 
1
 
5
2013
 
1
4
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.6349206
Min length1

Unique

Unique4 ?
Unique (%)6.3%

Sample

1st row<NA>
2nd row2013
3rd row1
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 54
85.7%
1 5
 
7.9%
2013 1
 
1.6%
4 1
 
1.6%
6 1
 
1.6%
14 1
 
1.6%

Length

2023-12-12T13:53:04.804696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:04.923362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 54
85.7%
1 5
 
7.9%
2013 1
 
1.6%
4 1
 
1.6%
6 1
 
1.6%
14 1
 
1.6%

Unnamed: 28
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
55 
2
 
4
3
 
2
1
 
1
13
 
1

Length

Max length4
Median length4
Mean length3.6349206
Min length1

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st row<NA>
2nd row<NA>
3rd row2
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 55
87.3%
2 4
 
6.3%
3 2
 
3.2%
1 1
 
1.6%
13 1
 
1.6%

Length

2023-12-12T13:53:05.039752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:05.409004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 55
87.3%
2 4
 
6.3%
3 2
 
3.2%
1 1
 
1.6%
13 1
 
1.6%

Unnamed: 29
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
55 
1
 
4
2
 
2
3
 
1
8
 
1

Length

Max length4
Median length4
Mean length3.6190476
Min length1

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st row<NA>
2nd row<NA>
3rd row3
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 55
87.3%
1 4
 
6.3%
2 2
 
3.2%
3 1
 
1.6%
8 1
 
1.6%

Length

2023-12-12T13:53:05.509735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:05.602108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 55
87.3%
1 4
 
6.3%
2 2
 
3.2%
3 1
 
1.6%
8 1
 
1.6%

Unnamed: 30
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
58 
2
 
2
4
 
1
3
 
1
7
 
1

Length

Max length4
Median length4
Mean length3.7619048
Min length1

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row<NA>
3rd row4
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 58
92.1%
2 2
 
3.2%
4 1
 
1.6%
3 1
 
1.6%
7 1
 
1.6%

Length

2023-12-12T13:53:05.731381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:05.863456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 58
92.1%
2 2
 
3.2%
4 1
 
1.6%
3 1
 
1.6%
7 1
 
1.6%

Unnamed: 31
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
56 
1
 
4
5
 
1
6
 
1
10
 
1

Length

Max length4
Median length4
Mean length3.6825397
Min length1

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row<NA>
3rd row5
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 56
88.9%
1 4
 
6.3%
5 1
 
1.6%
6 1
 
1.6%
10 1
 
1.6%

Length

2023-12-12T13:53:05.986486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:06.099903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 56
88.9%
1 4
 
6.3%
5 1
 
1.6%
6 1
 
1.6%
10 1
 
1.6%

Unnamed: 32
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)100.0%
Missing56
Missing (%)88.9%
Infinite0
Infinite (%)0.0%
Mean5.1428571
Minimum1
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:06.187100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.3
Q12.5
median4
Q35.5
95-th percentile12.3
Maximum15
Range14
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.6700668
Coefficient of variation (CV)0.90806854
Kurtosis4.2699186
Mean5.1428571
Median Absolute Deviation (MAD)2
Skewness1.9355829
Sum36
Variance21.809524
MonotonicityNot monotonic
2023-12-12T13:53:06.281893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
6 1
 
1.6%
1 1
 
1.6%
4 1
 
1.6%
2 1
 
1.6%
3 1
 
1.6%
5 1
 
1.6%
15 1
 
1.6%
(Missing) 56
88.9%
ValueCountFrequency (%)
1 1
1.6%
2 1
1.6%
3 1
1.6%
4 1
1.6%
5 1
1.6%
6 1
1.6%
15 1
1.6%
ValueCountFrequency (%)
15 1
1.6%
6 1
1.6%
5 1
1.6%
4 1
1.6%
3 1
1.6%
2 1
1.6%
1 1
1.6%

Unnamed: 33
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)66.7%
Missing51
Missing (%)81.0%
Infinite0
Infinite (%)0.0%
Mean6.5833333
Minimum1
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:06.384878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11.75
median3.5
Q37
95-th percentile21.15
Maximum36
Range35
Interquartile range (IQR)5.25

Descriptive statistics

Standard deviation9.662094
Coefficient of variation (CV)1.4676598
Kurtosis9.5784796
Mean6.5833333
Median Absolute Deviation (MAD)2.5
Skewness2.9862248
Sum79
Variance93.356061
MonotonicityNot monotonic
2023-12-12T13:53:06.488416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 3
 
4.8%
7 2
 
3.2%
2 2
 
3.2%
6 1
 
1.6%
4 1
 
1.6%
3 1
 
1.6%
9 1
 
1.6%
36 1
 
1.6%
(Missing) 51
81.0%
ValueCountFrequency (%)
1 3
4.8%
2 2
3.2%
3 1
 
1.6%
4 1
 
1.6%
6 1
 
1.6%
7 2
3.2%
9 1
 
1.6%
36 1
 
1.6%
ValueCountFrequency (%)
36 1
 
1.6%
9 1
 
1.6%
7 2
3.2%
6 1
 
1.6%
4 1
 
1.6%
3 1
 
1.6%
2 2
3.2%
1 3
4.8%

Unnamed: 34
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)50.0%
Missing49
Missing (%)77.8%
Infinite0
Infinite (%)0.0%
Mean8.8571429
Minimum1
Maximum58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:06.621800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q37
95-th percentile41.75
Maximum58
Range57
Interquartile range (IQR)6

Descriptive statistics

Standard deviation16.459073
Coefficient of variation (CV)1.8582825
Kurtosis6.4997624
Mean8.8571429
Median Absolute Deviation (MAD)1
Skewness2.5940441
Sum124
Variance270.9011
MonotonicityNot monotonic
2023-12-12T13:53:06.745344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 6
 
9.5%
8 2
 
3.2%
2 2
 
3.2%
4 1
 
1.6%
3 1
 
1.6%
33 1
 
1.6%
58 1
 
1.6%
(Missing) 49
77.8%
ValueCountFrequency (%)
1 6
9.5%
2 2
 
3.2%
3 1
 
1.6%
4 1
 
1.6%
8 2
 
3.2%
33 1
 
1.6%
58 1
 
1.6%
ValueCountFrequency (%)
58 1
 
1.6%
33 1
 
1.6%
8 2
 
3.2%
4 1
 
1.6%
3 1
 
1.6%
2 2
 
3.2%
1 6
9.5%

Unnamed: 35
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)53.8%
Missing50
Missing (%)79.4%
Infinite0
Infinite (%)0.0%
Mean5.9230769
Minimum1
Maximum34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:06.877287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q36
95-th percentile21.4
Maximum34
Range33
Interquartile range (IQR)5

Descriptive statistics

Standard deviation9.1965713
Coefficient of variation (CV)1.5526679
Kurtosis8.1659667
Mean5.9230769
Median Absolute Deviation (MAD)1
Skewness2.756857
Sum77
Variance84.576923
MonotonicityNot monotonic
2023-12-12T13:53:07.008175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 4
 
6.3%
1 4
 
6.3%
9 1
 
1.6%
3 1
 
1.6%
6 1
 
1.6%
13 1
 
1.6%
34 1
 
1.6%
(Missing) 50
79.4%
ValueCountFrequency (%)
1 4
6.3%
2 4
6.3%
3 1
 
1.6%
6 1
 
1.6%
9 1
 
1.6%
13 1
 
1.6%
34 1
 
1.6%
ValueCountFrequency (%)
34 1
 
1.6%
13 1
 
1.6%
9 1
 
1.6%
6 1
 
1.6%
3 1
 
1.6%
2 4
6.3%
1 4
6.3%

Unnamed: 36
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)46.2%
Missing50
Missing (%)79.4%
Infinite0
Infinite (%)0.0%
Mean5.8461538
Minimum1
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:07.111728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile21.6
Maximum33
Range32
Interquartile range (IQR)2

Descriptive statistics

Standard deviation9.0539692
Coefficient of variation (CV)1.5487053
Kurtosis7.3872387
Mean5.8461538
Median Absolute Deviation (MAD)1
Skewness2.6459329
Sum76
Variance81.974359
MonotonicityNot monotonic
2023-12-12T13:53:07.208990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 4
 
6.3%
3 3
 
4.8%
2 3
 
4.8%
10 1
 
1.6%
14 1
 
1.6%
33 1
 
1.6%
(Missing) 50
79.4%
ValueCountFrequency (%)
1 4
6.3%
2 3
4.8%
3 3
4.8%
10 1
 
1.6%
14 1
 
1.6%
33 1
 
1.6%
ValueCountFrequency (%)
33 1
 
1.6%
14 1
 
1.6%
10 1
 
1.6%
3 3
4.8%
2 3
4.8%
1 4
6.3%

Unnamed: 37
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
55 
1
 
5
11
 
1
9
 
1
14
 
1

Length

Max length4
Median length4
Mean length3.6507937
Min length1

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row<NA>
3rd row11
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 55
87.3%
1 5
 
7.9%
11 1
 
1.6%
9 1
 
1.6%
14 1
 
1.6%

Length

2023-12-12T13:53:07.353190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:07.470184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 55
87.3%
1 5
 
7.9%
11 1
 
1.6%
9 1
 
1.6%
14 1
 
1.6%

Unnamed: 38
Categorical

IMBALANCE 

Distinct6
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
57 
1
 
2
12
 
1
2
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.7301587
Min length1

Unique

Unique4 ?
Unique (%)6.3%

Sample

1st row<NA>
2nd row<NA>
3rd row12
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 57
90.5%
1 2
 
3.2%
12 1
 
1.6%
2 1
 
1.6%
5 1
 
1.6%
9 1
 
1.6%

Length

2023-12-12T13:53:07.605836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:07.730755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 57
90.5%
1 2
 
3.2%
12 1
 
1.6%
2 1
 
1.6%
5 1
 
1.6%
9 1
 
1.6%

Unnamed: 39
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)57.1%
Memory size636.0 B

Unnamed: 40
Categorical

IMBALANCE 

Distinct6
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
52 
1
 
5
2
 
3
2014
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.5396825
Min length1

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row2014
3rd row1
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 52
82.5%
1 5
 
7.9%
2 3
 
4.8%
2014 1
 
1.6%
3 1
 
1.6%
13 1
 
1.6%

Length

2023-12-12T13:53:07.896756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:08.018584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
82.5%
1 5
 
7.9%
2 3
 
4.8%
2014 1
 
1.6%
3 1
 
1.6%
13 1
 
1.6%

Unnamed: 41
Categorical

IMBALANCE 

Distinct4
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
57 
2
 
4
1
 
1
7
 
1

Length

Max length4
Median length4
Mean length3.7142857
Min length1

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st row<NA>
2nd row<NA>
3rd row2
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 57
90.5%
2 4
 
6.3%
1 1
 
1.6%
7 1
 
1.6%

Length

2023-12-12T13:53:08.168749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:08.311140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 57
90.5%
2 4
 
6.3%
1 1
 
1.6%
7 1
 
1.6%

Unnamed: 42
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
58 
2
 
2
3
 
1
1
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.7619048
Min length1

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row<NA>
3rd row3
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 58
92.1%
2 2
 
3.2%
3 1
 
1.6%
1 1
 
1.6%
5 1
 
1.6%

Length

2023-12-12T13:53:08.459934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:08.588673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 58
92.1%
2 2
 
3.2%
3 1
 
1.6%
1 1
 
1.6%
5 1
 
1.6%

Unnamed: 43
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
57 
1
 
3
4
 
1
3
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.7142857
Min length1

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row<NA>
3rd row4
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 57
90.5%
1 3
 
4.8%
4 1
 
1.6%
3 1
 
1.6%
6 1
 
1.6%

Length

2023-12-12T13:53:08.846863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:09.000712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 57
90.5%
1 3
 
4.8%
4 1
 
1.6%
3 1
 
1.6%
6 1
 
1.6%

Unnamed: 44
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)100.0%
Missing57
Missing (%)90.5%
Infinite0
Infinite (%)0.0%
Mean4.1666667
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:09.139187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.25
Q12.25
median3.5
Q34.75
95-th percentile8.75
Maximum10
Range9
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation3.1885211
Coefficient of variation (CV)0.76524506
Kurtosis2.4377318
Mean4.1666667
Median Absolute Deviation (MAD)1.5
Skewness1.4395903
Sum25
Variance10.166667
MonotonicityNot monotonic
2023-12-12T13:53:09.286784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
5 1
 
1.6%
1 1
 
1.6%
4 1
 
1.6%
3 1
 
1.6%
2 1
 
1.6%
10 1
 
1.6%
(Missing) 57
90.5%
ValueCountFrequency (%)
1 1
1.6%
2 1
1.6%
3 1
1.6%
4 1
1.6%
5 1
1.6%
10 1
1.6%
ValueCountFrequency (%)
10 1
1.6%
5 1
1.6%
4 1
1.6%
3 1
1.6%
2 1
1.6%
1 1
1.6%

Unnamed: 45
Categorical

IMBALANCE 

Distinct6
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
52 
1
6 
3
 
2
6
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.4920635
Min length1

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row<NA>
3rd row6
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 52
82.5%
1 6
 
9.5%
3 2
 
3.2%
6 1
 
1.6%
2 1
 
1.6%
14 1
 
1.6%

Length

2023-12-12T13:53:09.433827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:09.569361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
82.5%
1 6
 
9.5%
3 2
 
3.2%
6 1
 
1.6%
2 1
 
1.6%
14 1
 
1.6%

Unnamed: 46
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)70.0%
Missing53
Missing (%)84.1%
Infinite0
Infinite (%)0.0%
Mean7.1
Minimum1
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:09.680574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.45
Q12
median4
Q36.75
95-th percentile22.55
Maximum32
Range31
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation9.2550287
Coefficient of variation (CV)1.3035252
Kurtosis7.2100204
Mean7.1
Median Absolute Deviation (MAD)2
Skewness2.5950139
Sum71
Variance85.655556
MonotonicityNot monotonic
2023-12-12T13:53:09.796961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 3
 
4.8%
4 2
 
3.2%
7 1
 
1.6%
6 1
 
1.6%
1 1
 
1.6%
11 1
 
1.6%
32 1
 
1.6%
(Missing) 53
84.1%
ValueCountFrequency (%)
1 1
 
1.6%
2 3
4.8%
4 2
3.2%
6 1
 
1.6%
7 1
 
1.6%
11 1
 
1.6%
32 1
 
1.6%
ValueCountFrequency (%)
32 1
 
1.6%
11 1
 
1.6%
7 1
 
1.6%
6 1
 
1.6%
4 2
3.2%
2 3
4.8%
1 1
 
1.6%

Unnamed: 47
Categorical

IMBALANCE 

Distinct6
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
51 
1
7 
2
 
2
8
 
1
15
 
1

Length

Max length4
Median length4
Mean length3.4603175
Min length1

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row<NA>
3rd row8
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 51
81.0%
1 7
 
11.1%
2 2
 
3.2%
8 1
 
1.6%
15 1
 
1.6%
26 1
 
1.6%

Length

2023-12-12T13:53:09.930107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:10.068142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 51
81.0%
1 7
 
11.1%
2 2
 
3.2%
8 1
 
1.6%
15 1
 
1.6%
26 1
 
1.6%

Unnamed: 48
Categorical

IMBALANCE 

Distinct6
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
55 
1
 
3
2
 
2
9
 
1
4
 
1

Length

Max length4
Median length4
Mean length3.6349206
Min length1

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row<NA>
3rd row9
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 55
87.3%
1 3
 
4.8%
2 2
 
3.2%
9 1
 
1.6%
4 1
 
1.6%
11 1
 
1.6%

Length

2023-12-12T13:53:10.221045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:10.346716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 55
87.3%
1 3
 
4.8%
2 2
 
3.2%
9 1
 
1.6%
4 1
 
1.6%
11 1
 
1.6%

Unnamed: 49
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)54.5%
Missing52
Missing (%)82.5%
Infinite0
Infinite (%)0.0%
Mean4.1818182
Minimum1
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:10.478362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11.5
median2
Q33.5
95-th percentile14
Maximum18
Range17
Interquartile range (IQR)2

Descriptive statistics

Standard deviation5.2501082
Coefficient of variation (CV)1.2554607
Kurtosis5.0041473
Mean4.1818182
Median Absolute Deviation (MAD)1
Skewness2.2766629
Sum46
Variance27.563636
MonotonicityNot monotonic
2023-12-12T13:53:10.613052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 4
 
6.3%
1 3
 
4.8%
10 1
 
1.6%
3 1
 
1.6%
4 1
 
1.6%
18 1
 
1.6%
(Missing) 52
82.5%
ValueCountFrequency (%)
1 3
4.8%
2 4
6.3%
3 1
 
1.6%
4 1
 
1.6%
10 1
 
1.6%
18 1
 
1.6%
ValueCountFrequency (%)
18 1
 
1.6%
10 1
 
1.6%
4 1
 
1.6%
3 1
 
1.6%
2 4
6.3%
1 3
4.8%

Unnamed: 50
Categorical

IMBALANCE 

Distinct6
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
53 
1
6 
11
 
1
4
 
1
7
 
1

Length

Max length4
Median length4
Mean length3.5555556
Min length1

Unique

Unique4 ?
Unique (%)6.3%

Sample

1st row<NA>
2nd row<NA>
3rd row11
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 53
84.1%
1 6
 
9.5%
11 1
 
1.6%
4 1
 
1.6%
7 1
 
1.6%
17 1
 
1.6%

Length

2023-12-12T13:53:10.754606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:10.899253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 53
84.1%
1 6
 
9.5%
11 1
 
1.6%
4 1
 
1.6%
7 1
 
1.6%
17 1
 
1.6%

Unnamed: 51
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
58 
2
 
2
12
 
1
1
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.7777778
Min length1

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row<NA>
3rd row12
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 58
92.1%
2 2
 
3.2%
12 1
 
1.6%
1 1
 
1.6%
5 1
 
1.6%

Length

2023-12-12T13:53:11.065412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:11.216888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 58
92.1%
2 2
 
3.2%
12 1
 
1.6%
1 1
 
1.6%
5 1
 
1.6%

Unnamed: 52
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing37
Missing (%)58.7%
Memory size636.0 B

Unnamed: 53
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)75.0%
Missing55
Missing (%)87.3%
Infinite0
Infinite (%)0.0%
Mean254.75
Minimum1
Maximum2015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:11.352594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2.5
Q35.75
95-th percentile1313.6
Maximum2015
Range2014
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation711.25618
Coefficient of variation (CV)2.7919772
Kurtosis7.9994747
Mean254.75
Median Absolute Deviation (MAD)1.5
Skewness2.8283037
Sum2038
Variance505885.36
MonotonicityNot monotonic
2023-12-12T13:53:11.484401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 3
 
4.8%
2015 1
 
1.6%
4 1
 
1.6%
3 1
 
1.6%
2 1
 
1.6%
11 1
 
1.6%
(Missing) 55
87.3%
ValueCountFrequency (%)
1 3
4.8%
2 1
 
1.6%
3 1
 
1.6%
4 1
 
1.6%
11 1
 
1.6%
2015 1
 
1.6%
ValueCountFrequency (%)
2015 1
 
1.6%
11 1
 
1.6%
4 1
 
1.6%
3 1
 
1.6%
2 1
 
1.6%
1 3
4.8%

Unnamed: 54
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
55 
1
 
4
4
 
2
2
 
1
12
 
1

Length

Max length4
Median length4
Mean length3.6349206
Min length1

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st row<NA>
2nd row<NA>
3rd row2
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 55
87.3%
1 4
 
6.3%
4 2
 
3.2%
2 1
 
1.6%
12 1
 
1.6%

Length

2023-12-12T13:53:11.692125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:11.818947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 55
87.3%
1 4
 
6.3%
4 2
 
3.2%
2 1
 
1.6%
12 1
 
1.6%

Unnamed: 55
Categorical

IMBALANCE 

Distinct6
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
54 
1
 
5
3
 
1
4
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.5873016
Min length1

Unique

Unique4 ?
Unique (%)6.3%

Sample

1st row<NA>
2nd row<NA>
3rd row3
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 54
85.7%
1 5
 
7.9%
3 1
 
1.6%
4 1
 
1.6%
6 1
 
1.6%
15 1
 
1.6%

Length

2023-12-12T13:53:11.984275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:12.141086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 54
85.7%
1 5
 
7.9%
3 1
 
1.6%
4 1
 
1.6%
6 1
 
1.6%
15 1
 
1.6%

Unnamed: 56
Categorical

IMBALANCE 

Distinct6
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
55 
1
 
3
2
 
2
4
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.6349206
Min length1

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row<NA>
3rd row4
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 55
87.3%
1 3
 
4.8%
2 2
 
3.2%
4 1
 
1.6%
3 1
 
1.6%
10 1
 
1.6%

Length

2023-12-12T13:53:12.314406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:12.464947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 55
87.3%
1 3
 
4.8%
2 2
 
3.2%
4 1
 
1.6%
3 1
 
1.6%
10 1
 
1.6%

Unnamed: 57
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)60.0%
Missing53
Missing (%)84.1%
Infinite0
Infinite (%)0.0%
Mean3.5
Minimum1
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:12.609522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33.75
95-th percentile10.5
Maximum15
Range14
Interquartile range (IQR)2.75

Descriptive statistics

Standard deviation4.2752518
Coefficient of variation (CV)1.2215005
Kurtosis7.1991258
Mean3.5
Median Absolute Deviation (MAD)1
Skewness2.5861006
Sum35
Variance18.277778
MonotonicityNot monotonic
2023-12-12T13:53:12.792274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 4
 
6.3%
2 2
 
3.2%
5 1
 
1.6%
3 1
 
1.6%
4 1
 
1.6%
15 1
 
1.6%
(Missing) 53
84.1%
ValueCountFrequency (%)
1 4
6.3%
2 2
3.2%
3 1
 
1.6%
4 1
 
1.6%
5 1
 
1.6%
15 1
 
1.6%
ValueCountFrequency (%)
15 1
 
1.6%
5 1
 
1.6%
4 1
 
1.6%
3 1
 
1.6%
2 2
3.2%
1 4
6.3%

Unnamed: 58
Categorical

IMBALANCE 

Distinct6
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
55 
1
 
4
6
 
1
2
 
1
4
 
1

Length

Max length4
Median length4
Mean length3.6349206
Min length1

Unique

Unique4 ?
Unique (%)6.3%

Sample

1st row<NA>
2nd row<NA>
3rd row6
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 55
87.3%
1 4
 
6.3%
6 1
 
1.6%
2 1
 
1.6%
4 1
 
1.6%
10 1
 
1.6%

Length

2023-12-12T13:53:13.022676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:13.172279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 55
87.3%
1 4
 
6.3%
6 1
 
1.6%
2 1
 
1.6%
4 1
 
1.6%
10 1
 
1.6%

Unnamed: 59
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)70.0%
Missing53
Missing (%)84.1%
Infinite0
Infinite (%)0.0%
Mean5.1
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:13.291202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3.5
Q35.75
95-th percentile15.25
Maximum22
Range21
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation6.3499781
Coefficient of variation (CV)1.2450938
Kurtosis6.7672375
Mean5.1
Median Absolute Deviation (MAD)2.5
Skewness2.4670771
Sum51
Variance40.322222
MonotonicityNot monotonic
2023-12-12T13:53:13.408121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 4
 
6.3%
7 1
 
1.6%
5 1
 
1.6%
3 1
 
1.6%
6 1
 
1.6%
4 1
 
1.6%
22 1
 
1.6%
(Missing) 53
84.1%
ValueCountFrequency (%)
1 4
6.3%
3 1
 
1.6%
4 1
 
1.6%
5 1
 
1.6%
6 1
 
1.6%
7 1
 
1.6%
22 1
 
1.6%
ValueCountFrequency (%)
22 1
 
1.6%
7 1
 
1.6%
6 1
 
1.6%
5 1
 
1.6%
4 1
 
1.6%
3 1
 
1.6%
1 4
6.3%

Unnamed: 60
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)72.7%
Missing52
Missing (%)82.5%
Infinite0
Infinite (%)0.0%
Mean7.2727273
Minimum1
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:13.551525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q36.5
95-th percentile27
Maximum36
Range35
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation10.771174
Coefficient of variation (CV)1.4810364
Kurtosis5.3911728
Mean7.2727273
Median Absolute Deviation (MAD)2
Skewness2.3163685
Sum80
Variance116.01818
MonotonicityNot monotonic
2023-12-12T13:53:13.708466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 4
 
6.3%
8 1
 
1.6%
3 1
 
1.6%
5 1
 
1.6%
4 1
 
1.6%
2 1
 
1.6%
18 1
 
1.6%
36 1
 
1.6%
(Missing) 52
82.5%
ValueCountFrequency (%)
1 4
6.3%
2 1
 
1.6%
3 1
 
1.6%
4 1
 
1.6%
5 1
 
1.6%
8 1
 
1.6%
18 1
 
1.6%
36 1
 
1.6%
ValueCountFrequency (%)
36 1
 
1.6%
18 1
 
1.6%
8 1
 
1.6%
5 1
 
1.6%
4 1
 
1.6%
3 1
 
1.6%
2 1
 
1.6%
1 4
6.3%

Unnamed: 61
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)60.0%
Missing53
Missing (%)84.1%
Infinite0
Infinite (%)0.0%
Mean5.7
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:13.845620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q37.5
95-th percentile19.05
Maximum24
Range23
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation7.6165026
Coefficient of variation (CV)1.3362285
Kurtosis3.2804362
Mean5.7
Median Absolute Deviation (MAD)1
Skewness1.8914388
Sum57
Variance58.011111
MonotonicityNot monotonic
2023-12-12T13:53:14.027293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 4
 
6.3%
2 2
 
3.2%
9 1
 
1.6%
3 1
 
1.6%
13 1
 
1.6%
24 1
 
1.6%
(Missing) 53
84.1%
ValueCountFrequency (%)
1 4
6.3%
2 2
3.2%
3 1
 
1.6%
9 1
 
1.6%
13 1
 
1.6%
24 1
 
1.6%
ValueCountFrequency (%)
24 1
 
1.6%
13 1
 
1.6%
9 1
 
1.6%
3 1
 
1.6%
2 2
3.2%
1 4
6.3%

Unnamed: 62
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)42.9%
Missing49
Missing (%)77.8%
Infinite0
Infinite (%)0.0%
Mean6.5714286
Minimum1
Maximum41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:14.144113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile27.35
Maximum41
Range40
Interquartile range (IQR)3

Descriptive statistics

Standard deviation11.209298
Coefficient of variation (CV)1.7057627
Kurtosis7.3586229
Mean6.5714286
Median Absolute Deviation (MAD)1
Skewness2.6720662
Sum92
Variance125.64835
MonotonicityNot monotonic
2023-12-12T13:53:14.270321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 7
 
11.1%
4 2
 
3.2%
3 2
 
3.2%
10 1
 
1.6%
20 1
 
1.6%
41 1
 
1.6%
(Missing) 49
77.8%
ValueCountFrequency (%)
1 7
11.1%
3 2
 
3.2%
4 2
 
3.2%
10 1
 
1.6%
20 1
 
1.6%
41 1
 
1.6%
ValueCountFrequency (%)
41 1
 
1.6%
20 1
 
1.6%
10 1
 
1.6%
4 2
 
3.2%
3 2
 
3.2%
1 7
11.1%

Unnamed: 63
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)61.5%
Missing50
Missing (%)79.4%
Infinite0
Infinite (%)0.0%
Mean6.8461538
Minimum1
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:14.419828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile27
Maximum39
Range38
Interquartile range (IQR)4

Descriptive statistics

Standard deviation11.006408
Coefficient of variation (CV)1.6076776
Kurtosis6.3969564
Mean6.8461538
Median Absolute Deviation (MAD)1
Skewness2.4900264
Sum89
Variance121.14103
MonotonicityNot monotonic
2023-12-12T13:53:14.550298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 6
 
9.5%
11 1
 
1.6%
2 1
 
1.6%
3 1
 
1.6%
4 1
 
1.6%
5 1
 
1.6%
19 1
 
1.6%
39 1
 
1.6%
(Missing) 50
79.4%
ValueCountFrequency (%)
1 6
9.5%
2 1
 
1.6%
3 1
 
1.6%
4 1
 
1.6%
5 1
 
1.6%
11 1
 
1.6%
19 1
 
1.6%
39 1
 
1.6%
ValueCountFrequency (%)
39 1
 
1.6%
19 1
 
1.6%
11 1
 
1.6%
5 1
 
1.6%
4 1
 
1.6%
3 1
 
1.6%
2 1
 
1.6%
1 6
9.5%

Unnamed: 64
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)54.5%
Missing52
Missing (%)82.5%
Infinite0
Infinite (%)0.0%
Mean4.7272727
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:15.006301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q34
95-th percentile16
Maximum20
Range19
Interquartile range (IQR)2

Descriptive statistics

Standard deviation5.9513177
Coefficient of variation (CV)1.2589326
Kurtosis4.2919531
Mean4.7272727
Median Absolute Deviation (MAD)1
Skewness2.1668799
Sum52
Variance35.418182
MonotonicityNot monotonic
2023-12-12T13:53:15.129473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 5
 
7.9%
1 2
 
3.2%
12 1
 
1.6%
3 1
 
1.6%
5 1
 
1.6%
20 1
 
1.6%
(Missing) 52
82.5%
ValueCountFrequency (%)
1 2
 
3.2%
2 5
7.9%
3 1
 
1.6%
5 1
 
1.6%
12 1
 
1.6%
20 1
 
1.6%
ValueCountFrequency (%)
20 1
 
1.6%
12 1
 
1.6%
5 1
 
1.6%
3 1
 
1.6%
2 5
7.9%
1 2
 
3.2%

Unnamed: 65
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing34
Missing (%)54.0%
Memory size636.0 B

Unnamed: 66
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)63.6%
Missing52
Missing (%)82.5%
Infinite0
Infinite (%)0.0%
Mean189.18182
Minimum1
Maximum2016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:15.257555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median5
Q38
95-th percentile1024
Maximum2016
Range2015
Interquartile range (IQR)7

Descriptive statistics

Standard deviation605.95261
Coefficient of variation (CV)3.2030172
Kurtosis10.993638
Mean189.18182
Median Absolute Deviation (MAD)4
Skewness3.3153179
Sum2081
Variance367178.56
MonotonicityNot monotonic
2023-12-12T13:53:15.381529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 4
 
6.3%
5 2
 
3.2%
2016 1
 
1.6%
3 1
 
1.6%
9 1
 
1.6%
7 1
 
1.6%
32 1
 
1.6%
(Missing) 52
82.5%
ValueCountFrequency (%)
1 4
6.3%
3 1
 
1.6%
5 2
3.2%
7 1
 
1.6%
9 1
 
1.6%
32 1
 
1.6%
2016 1
 
1.6%
ValueCountFrequency (%)
2016 1
 
1.6%
32 1
 
1.6%
9 1
 
1.6%
7 1
 
1.6%
5 2
3.2%
3 1
 
1.6%
1 4
6.3%

Unnamed: 67
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)63.6%
Missing52
Missing (%)82.5%
Infinite0
Infinite (%)0.0%
Mean6.7272727
Minimum1
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:15.537230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11.5
median2
Q36
95-th percentile25
Maximum36
Range35
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation10.45075
Coefficient of variation (CV)1.5534899
Kurtosis7.2371401
Mean6.7272727
Median Absolute Deviation (MAD)1
Skewness2.6267573
Sum74
Variance109.21818
MonotonicityNot monotonic
2023-12-12T13:53:15.672762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 3
 
4.8%
1 3
 
4.8%
5 1
 
1.6%
7 1
 
1.6%
3 1
 
1.6%
14 1
 
1.6%
36 1
 
1.6%
(Missing) 52
82.5%
ValueCountFrequency (%)
1 3
4.8%
2 3
4.8%
3 1
 
1.6%
5 1
 
1.6%
7 1
 
1.6%
14 1
 
1.6%
36 1
 
1.6%
ValueCountFrequency (%)
36 1
 
1.6%
14 1
 
1.6%
7 1
 
1.6%
5 1
 
1.6%
3 1
 
1.6%
2 3
4.8%
1 3
4.8%

Unnamed: 68
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)53.8%
Missing50
Missing (%)79.4%
Infinite0
Infinite (%)0.0%
Mean5.1538462
Minimum1
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:15.806382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile19.4
Maximum32
Range31
Interquartile range (IQR)3

Descriptive statistics

Standard deviation8.5619911
Coefficient of variation (CV)1.6612819
Kurtosis9.4790521
Mean5.1538462
Median Absolute Deviation (MAD)1
Skewness2.9915987
Sum67
Variance73.307692
MonotonicityNot monotonic
2023-12-12T13:53:15.969481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 6
 
9.5%
3 2
 
3.2%
2 1
 
1.6%
6 1
 
1.6%
4 1
 
1.6%
11 1
 
1.6%
32 1
 
1.6%
(Missing) 50
79.4%
ValueCountFrequency (%)
1 6
9.5%
2 1
 
1.6%
3 2
 
3.2%
4 1
 
1.6%
6 1
 
1.6%
11 1
 
1.6%
32 1
 
1.6%
ValueCountFrequency (%)
32 1
 
1.6%
11 1
 
1.6%
6 1
 
1.6%
4 1
 
1.6%
3 2
 
3.2%
2 1
 
1.6%
1 6
9.5%

Unnamed: 69
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)54.5%
Missing52
Missing (%)82.5%
Infinite0
Infinite (%)0.0%
Mean4.5454545
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:16.124801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33.5
95-th percentile16.5
Maximum23
Range22
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation6.6687875
Coefficient of variation (CV)1.4671333
Kurtosis6.7450331
Mean4.5454545
Median Absolute Deviation (MAD)1
Skewness2.5552582
Sum50
Variance44.472727
MonotonicityNot monotonic
2023-12-12T13:53:16.257806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 5
 
7.9%
3 2
 
3.2%
4 1
 
1.6%
10 1
 
1.6%
2 1
 
1.6%
23 1
 
1.6%
(Missing) 52
82.5%
ValueCountFrequency (%)
1 5
7.9%
2 1
 
1.6%
3 2
 
3.2%
4 1
 
1.6%
10 1
 
1.6%
23 1
 
1.6%
ValueCountFrequency (%)
23 1
 
1.6%
10 1
 
1.6%
4 1
 
1.6%
3 2
 
3.2%
2 1
 
1.6%
1 5
7.9%

Unnamed: 70
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)54.5%
Missing52
Missing (%)82.5%
Infinite0
Infinite (%)0.0%
Mean3.7272727
Minimum1
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:16.374048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q34.5
95-th percentile12
Maximum18
Range17
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation5.0811595
Coefficient of variation (CV)1.3632379
Kurtosis7.3486172
Mean3.7272727
Median Absolute Deviation (MAD)0
Skewness2.6035147
Sum41
Variance25.818182
MonotonicityNot monotonic
2023-12-12T13:53:16.491709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 6
 
9.5%
5 1
 
1.6%
2 1
 
1.6%
6 1
 
1.6%
4 1
 
1.6%
18 1
 
1.6%
(Missing) 52
82.5%
ValueCountFrequency (%)
1 6
9.5%
2 1
 
1.6%
4 1
 
1.6%
5 1
 
1.6%
6 1
 
1.6%
18 1
 
1.6%
ValueCountFrequency (%)
18 1
 
1.6%
6 1
 
1.6%
5 1
 
1.6%
4 1
 
1.6%
2 1
 
1.6%
1 6
9.5%

Unnamed: 71
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)87.5%
Missing55
Missing (%)87.3%
Infinite0
Infinite (%)0.0%
Mean6.25
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:16.612843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11.75
median3.5
Q37.25
95-th percentile18.15
Maximum22
Range21
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation7.1663898
Coefficient of variation (CV)1.1466224
Kurtosis3.4228872
Mean6.25
Median Absolute Deviation (MAD)2.5
Skewness1.8642891
Sum50
Variance51.357143
MonotonicityNot monotonic
2023-12-12T13:53:16.721612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 2
 
3.2%
6 1
 
1.6%
3 1
 
1.6%
2 1
 
1.6%
11 1
 
1.6%
4 1
 
1.6%
22 1
 
1.6%
(Missing) 55
87.3%
ValueCountFrequency (%)
1 2
3.2%
2 1
1.6%
3 1
1.6%
4 1
1.6%
6 1
1.6%
11 1
1.6%
22 1
1.6%
ValueCountFrequency (%)
22 1
1.6%
11 1
1.6%
6 1
1.6%
4 1
1.6%
3 1
1.6%
2 1
1.6%
1 2
3.2%

Unnamed: 72
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)60.0%
Missing53
Missing (%)84.1%
Infinite0
Infinite (%)0.0%
Mean8.5
Minimum1
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:16.840303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median5
Q37
95-th percentile29.55
Maximum39
Range38
Interquartile range (IQR)6

Descriptive statistics

Standard deviation11.90938
Coefficient of variation (CV)1.4011035
Kurtosis5.2800661
Mean8.5
Median Absolute Deviation (MAD)4
Skewness2.2553296
Sum85
Variance141.83333
MonotonicityNot monotonic
2023-12-12T13:53:16.945861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 4
 
6.3%
7 2
 
3.2%
4 1
 
1.6%
6 1
 
1.6%
18 1
 
1.6%
39 1
 
1.6%
(Missing) 53
84.1%
ValueCountFrequency (%)
1 4
6.3%
4 1
 
1.6%
6 1
 
1.6%
7 2
3.2%
18 1
 
1.6%
39 1
 
1.6%
ValueCountFrequency (%)
39 1
 
1.6%
18 1
 
1.6%
7 2
3.2%
6 1
 
1.6%
4 1
 
1.6%
1 4
6.3%

Unnamed: 73
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)50.0%
Missing51
Missing (%)81.0%
Infinite0
Infinite (%)0.0%
Mean7.6666667
Minimum1
Maximum42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:17.053696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q36.5
95-th percentile30.45
Maximum42
Range41
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation12.249923
Coefficient of variation (CV)1.597816
Kurtosis5.9976306
Mean7.6666667
Median Absolute Deviation (MAD)1
Skewness2.4303869
Sum92
Variance150.06061
MonotonicityNot monotonic
2023-12-12T13:53:17.152641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 6
 
9.5%
6 2
 
3.2%
8 1
 
1.6%
3 1
 
1.6%
21 1
 
1.6%
42 1
 
1.6%
(Missing) 51
81.0%
ValueCountFrequency (%)
1 6
9.5%
3 1
 
1.6%
6 2
 
3.2%
8 1
 
1.6%
21 1
 
1.6%
42 1
 
1.6%
ValueCountFrequency (%)
42 1
 
1.6%
21 1
 
1.6%
8 1
 
1.6%
6 2
 
3.2%
3 1
 
1.6%
1 6
9.5%

Unnamed: 74
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)77.8%
Missing54
Missing (%)85.7%
Infinite0
Infinite (%)0.0%
Mean6.3333333
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:17.260702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q39
95-th percentile18.8
Maximum24
Range23
Interquartile range (IQR)7

Descriptive statistics

Standard deviation7.5166482
Coefficient of variation (CV)1.1868392
Kurtosis3.8542228
Mean6.3333333
Median Absolute Deviation (MAD)2
Skewness1.9370403
Sum57
Variance56.5
MonotonicityNot monotonic
2023-12-12T13:53:17.367221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 2
 
3.2%
1 2
 
3.2%
9 1
 
1.6%
3 1
 
1.6%
4 1
 
1.6%
11 1
 
1.6%
24 1
 
1.6%
(Missing) 54
85.7%
ValueCountFrequency (%)
1 2
3.2%
2 2
3.2%
3 1
1.6%
4 1
1.6%
9 1
1.6%
11 1
1.6%
24 1
1.6%
ValueCountFrequency (%)
24 1
1.6%
11 1
1.6%
9 1
1.6%
4 1
1.6%
3 1
1.6%
2 2
3.2%
1 2
3.2%

Unnamed: 75
Categorical

IMBALANCE 

Distinct6
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
<NA>
54 
1
 
5
10
 
1
2
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.6031746
Min length1

Unique

Unique4 ?
Unique (%)6.3%

Sample

1st row<NA>
2nd row<NA>
3rd row10
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 54
85.7%
1 5
 
7.9%
10 1
 
1.6%
2 1
 
1.6%
6 1
 
1.6%
13 1
 
1.6%

Length

2023-12-12T13:53:17.511081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:53:17.653295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 54
85.7%
1 5
 
7.9%
10 1
 
1.6%
2 1
 
1.6%
6 1
 
1.6%
13 1
 
1.6%

Unnamed: 76
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)75.0%
Missing55
Missing (%)87.3%
Infinite0
Infinite (%)0.0%
Mean5.875
Minimum1
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:17.759778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median4
Q38
95-th percentile15.55
Maximum18
Range17
Interquartile range (IQR)7

Descriptive statistics

Standard deviation6.1047405
Coefficient of variation (CV)1.0391048
Kurtosis1.0800867
Mean5.875
Median Absolute Deviation (MAD)3
Skewness1.2665815
Sum47
Variance37.267857
MonotonicityNot monotonic
2023-12-12T13:53:17.863137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 3
 
4.8%
11 1
 
1.6%
7 1
 
1.6%
2 1
 
1.6%
6 1
 
1.6%
18 1
 
1.6%
(Missing) 55
87.3%
ValueCountFrequency (%)
1 3
4.8%
2 1
 
1.6%
6 1
 
1.6%
7 1
 
1.6%
11 1
 
1.6%
18 1
 
1.6%
ValueCountFrequency (%)
18 1
 
1.6%
11 1
 
1.6%
7 1
 
1.6%
6 1
 
1.6%
2 1
 
1.6%
1 3
4.8%

Unnamed: 77
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)85.7%
Missing56
Missing (%)88.9%
Infinite0
Infinite (%)0.0%
Mean5.7142857
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T13:53:17.983035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11.5
median4
Q39
95-th percentile13.4
Maximum14
Range13
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation5.3139529
Coefficient of variation (CV)0.92994175
Kurtosis-1.0334311
Mean5.7142857
Median Absolute Deviation (MAD)3
Skewness0.85739472
Sum40
Variance28.238095
MonotonicityNot monotonic
2023-12-12T13:53:18.097177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 2
 
3.2%
12 1
 
1.6%
4 1
 
1.6%
2 1
 
1.6%
6 1
 
1.6%
14 1
 
1.6%
(Missing) 56
88.9%
ValueCountFrequency (%)
1 2
3.2%
2 1
1.6%
4 1
1.6%
6 1
1.6%
12 1
1.6%
14 1
1.6%
ValueCountFrequency (%)
14 1
1.6%
12 1
1.6%
6 1
1.6%
4 1
1.6%
2 1
1.6%
1 2
3.2%

Unnamed: 78
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing41
Missing (%)65.1%
Memory size636.0 B

Unnamed: 79
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)3.2%
Memory size636.0 B

Sample

뎅기열Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33Unnamed: 34Unnamed: 35Unnamed: 36Unnamed: 37Unnamed: 38Unnamed: 39Unnamed: 40Unnamed: 41Unnamed: 42Unnamed: 43Unnamed: 44Unnamed: 45Unnamed: 46Unnamed: 47Unnamed: 48Unnamed: 49Unnamed: 50Unnamed: 51Unnamed: 52Unnamed: 53Unnamed: 54Unnamed: 55Unnamed: 56Unnamed: 57Unnamed: 58Unnamed: 59Unnamed: 60Unnamed: 61Unnamed: 62Unnamed: 63Unnamed: 64Unnamed: 65Unnamed: 66Unnamed: 67Unnamed: 68Unnamed: 69Unnamed: 70Unnamed: 71Unnamed: 72Unnamed: 73Unnamed: 74Unnamed: 75Unnamed: 76Unnamed: 77Unnamed: 78Unnamed: 79
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaNNaN
1<NA>2011<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2011 소계2012<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2012 소계2013<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2013 소계2014<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2014 소계2015<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2015 소계2016<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2016 소계총합계
2<NA>123456789101112NaN123456789101112NaN123456789101112NaN123456789101112NaN123456789101112NaN123456789101112NaNNaN
3가나<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN2
4과테말라<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN1
5기니<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN1
6네팔<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA>1<NA><NA><NA><NA>11
7대만<NA><NA><NA><NA><NA><NA><NA>1<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN2
8동티모르<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN1
9라오스<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>612<NA><NA><NA>9<NA><NA><NA><NA><NA><NA>2<NA><NA><NA><NA><NA>2<NA><NA><NA><NA>2<NA><NA><NA><NA>1<NA><NA>3<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN14
뎅기열Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33Unnamed: 34Unnamed: 35Unnamed: 36Unnamed: 37Unnamed: 38Unnamed: 39Unnamed: 40Unnamed: 41Unnamed: 42Unnamed: 43Unnamed: 44Unnamed: 45Unnamed: 46Unnamed: 47Unnamed: 48Unnamed: 49Unnamed: 50Unnamed: 51Unnamed: 52Unnamed: 53Unnamed: 54Unnamed: 55Unnamed: 56Unnamed: 57Unnamed: 58Unnamed: 59Unnamed: 60Unnamed: 61Unnamed: 62Unnamed: 63Unnamed: 64Unnamed: 65Unnamed: 66Unnamed: 67Unnamed: 68Unnamed: 69Unnamed: 70Unnamed: 71Unnamed: 72Unnamed: 73Unnamed: 74Unnamed: 75Unnamed: 76Unnamed: 77Unnamed: 78Unnamed: 79
53파라과이<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>11
54파키스탄<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA>1<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN1
55프랑스<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA>1<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN1
56피지<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA>11
57필리핀411<NA><NA><NA>33221<NA>1713122691371154646312159331314951013221231115447256246244418132019510171411244182111666110449
58필리핀,태국<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN1
59헝가리<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>11
60호주<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN1
61홍콩<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN1
62총합계6511157171375472475639202624181611149141387101536583433149251137561014322611181751641112151015102236244139202553236322318223942241318143131204