Overview

Dataset statistics

Number of variables88
Number of observations818
Missing cells46934
Missing cells (%)65.2%
Duplicate rows73
Duplicate rows (%)8.9%
Total size in memory619.2 KiB
Average record size in memory775.2 B

Variable types

Categorical23
Unsupported20
Numeric43
Text2

Dataset

Description법정감염병 중 3군에 속하는 모기매개감염병인 말라리아의 직업별 국내발생현황. (단위: 건) * 국내에서만 발생한 사례 * 환자의 직업분류 : "민간인/제대군인/현역군인"
Author질병관리청
URLhttps://www.data.go.kr/data/15033736/fileData.do

Alerts

Dataset has 73 (8.9%) duplicate rowsDuplicates
<말라리아 발생현황 공공데이터 제공> is highly imbalanced (68.8%)Imbalance
Unnamed: 10 is highly imbalanced (73.7%)Imbalance
Unnamed: 30 is highly imbalanced (95.7%)Imbalance
Unnamed: 31 is highly imbalanced (93.9%)Imbalance
Unnamed: 38 is highly imbalanced (96.7%)Imbalance
Unnamed: 40 is highly imbalanced (97.4%)Imbalance
Unnamed: 41 is highly imbalanced (95.6%)Imbalance
Unnamed: 48 is highly imbalanced (97.2%)Imbalance
Unnamed: 49 is highly imbalanced (96.5%)Imbalance
Unnamed: 51 is highly imbalanced (95.9%)Imbalance
Unnamed: 52 is highly imbalanced (97.2%)Imbalance
Unnamed: 60 is highly imbalanced (96.2%)Imbalance
Unnamed: 61 is highly imbalanced (97.6%)Imbalance
Unnamed: 63 is highly imbalanced (96.9%)Imbalance
Unnamed: 64 is highly imbalanced (97.6%)Imbalance
Unnamed: 65 is highly imbalanced (97.4%)Imbalance
Unnamed: 73 is highly imbalanced (95.8%)Imbalance
Unnamed: 74 is highly imbalanced (97.6%)Imbalance
Unnamed: 76 is highly imbalanced (96.9%)Imbalance
Unnamed: 77 is highly imbalanced (96.9%)Imbalance
Unnamed: 78 is highly imbalanced (94.7%)Imbalance
Unnamed: 84 is highly imbalanced (97.6%)Imbalance
Unnamed: 85 is highly imbalanced (97.6%)Imbalance
Unnamed: 1 has 717 (87.7%) missing valuesMissing
Unnamed: 2 has 705 (86.2%) missing valuesMissing
Unnamed: 3 has 696 (85.1%) missing valuesMissing
Unnamed: 4 has 708 (86.6%) missing valuesMissing
Unnamed: 5 has 710 (86.8%) missing valuesMissing
Unnamed: 6 has 651 (79.6%) missing valuesMissing
감염병감시과, 2018.5.24 has 818 (100.0%) missing valuesMissing
Unnamed: 8 has 818 (100.0%) missing valuesMissing
Unnamed: 9 has 818 (100.0%) missing valuesMissing
Unnamed: 11 has 732 (89.5%) missing valuesMissing
Unnamed: 12 has 734 (89.7%) missing valuesMissing
Unnamed: 13 has 725 (88.6%) missing valuesMissing
Unnamed: 14 has 728 (89.0%) missing valuesMissing
Unnamed: 15 has 740 (90.5%) missing valuesMissing
Unnamed: 16 has 691 (84.5%) missing valuesMissing
Unnamed: 17 has 818 (100.0%) missing valuesMissing
Unnamed: 18 has 818 (100.0%) missing valuesMissing
Unnamed: 20 has 522 (63.8%) missing valuesMissing
Unnamed: 21 has 464 (56.7%) missing valuesMissing
Unnamed: 22 has 439 (53.7%) missing valuesMissing
Unnamed: 23 has 437 (53.4%) missing valuesMissing
Unnamed: 24 has 505 (61.7%) missing valuesMissing
Unnamed: 26 has 818 (100.0%) missing valuesMissing
Unnamed: 27 has 818 (100.0%) missing valuesMissing
Unnamed: 28 has 648 (79.2%) missing valuesMissing
Unnamed: 29 has 812 (99.3%) missing valuesMissing
Unnamed: 32 has 795 (97.2%) missing valuesMissing
Unnamed: 33 has 779 (95.2%) missing valuesMissing
Unnamed: 34 has 773 (94.5%) missing valuesMissing
Unnamed: 35 has 787 (96.2%) missing valuesMissing
Unnamed: 36 has 795 (97.2%) missing valuesMissing
Unnamed: 37 has 798 (97.6%) missing valuesMissing
Unnamed: 39 has 737 (90.1%) missing valuesMissing
Unnamed: 42 has 799 (97.7%) missing valuesMissing
Unnamed: 43 has 795 (97.2%) missing valuesMissing
Unnamed: 44 has 776 (94.9%) missing valuesMissing
Unnamed: 45 has 777 (95.0%) missing valuesMissing
Unnamed: 46 has 786 (96.1%) missing valuesMissing
Unnamed: 47 has 793 (96.9%) missing valuesMissing
Unnamed: 50 has 742 (90.7%) missing valuesMissing
Unnamed: 53 has 804 (98.3%) missing valuesMissing
Unnamed: 54 has 793 (96.9%) missing valuesMissing
Unnamed: 55 has 784 (95.8%) missing valuesMissing
Unnamed: 56 has 784 (95.8%) missing valuesMissing
Unnamed: 57 has 777 (95.0%) missing valuesMissing
Unnamed: 58 has 795 (97.2%) missing valuesMissing
Unnamed: 59 has 806 (98.5%) missing valuesMissing
Unnamed: 62 has 736 (90.0%) missing valuesMissing
Unnamed: 66 has 798 (97.6%) missing valuesMissing
Unnamed: 67 has 790 (96.6%) missing valuesMissing
Unnamed: 68 has 781 (95.5%) missing valuesMissing
Unnamed: 69 has 778 (95.1%) missing valuesMissing
Unnamed: 70 has 789 (96.5%) missing valuesMissing
Unnamed: 71 has 795 (97.2%) missing valuesMissing
Unnamed: 72 has 802 (98.0%) missing valuesMissing
Unnamed: 75 has 725 (88.6%) missing valuesMissing
Unnamed: 79 has 787 (96.2%) missing valuesMissing
Unnamed: 80 has 784 (95.8%) missing valuesMissing
Unnamed: 81 has 793 (96.9%) missing valuesMissing
Unnamed: 82 has 793 (96.9%) missing valuesMissing
Unnamed: 83 has 801 (97.9%) missing valuesMissing
Unnamed: 86 has 754 (92.2%) missing valuesMissing
Unnamed: 87 has 649 (79.3%) missing valuesMissing
Unnamed: 1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
감염병감시과, 2018.5.24 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 16 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 17 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 18 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 20 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 25 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: 27 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 29 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: 50 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 62 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 75 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 86 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 87 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 19:50:11.118235
Analysis finished2023-12-12 19:50:12.330022
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

<말라리아 발생현황 공공데이터 제공>
Categorical

IMBALANCE 

Distinct38
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
650 
기타
 
19
무직
 
18
(전업)주부
 
13
농업 및 어업숙련 종사자
 
13
Other values (33)
105 

Length

Max length31
Median length4
Mean length4.4413203
Min length2

Unique

Unique23 ?
Unique (%)2.8%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row2013~2017년 말라리아 국내발생 연령별/직업별 현황
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 650
79.5%
기타 19
 
2.3%
무직 18
 
2.2%
(전업)주부 13
 
1.6%
농업 및 어업숙련 종사자 13
 
1.6%
판매종사자 10
 
1.2%
서비스종사자 10
 
1.2%
사무종사자 10
 
1.2%
단순노무 종사자 10
 
1.2%
군인 8
 
1.0%
Other values (28) 57
 
7.0%

Length

2023-12-13T04:50:12.421409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 650
70.7%
및 34
 
3.7%
종사자 30
 
3.3%
기타 19
 
2.1%
무직 18
 
2.0%
전업)주부 13
 
1.4%
농업 13
 
1.4%
어업숙련 13
 
1.4%
판매종사자 10
 
1.1%
서비스종사자 10
 
1.1%
Other values (38) 110
 
12.0%

Unnamed: 1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing717
Missing (%)87.7%
Memory size6.5 KiB

Unnamed: 2
Real number (ℝ)

MISSING 

Distinct30
Distinct (%)26.5%
Missing705
Missing (%)86.2%
Infinite0
Infinite (%)0.0%
Mean32.637168
Minimum1
Maximum2014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:12.563757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q38
95-th percentile48
Maximum2014
Range2013
Interquartile range (IQR)7

Descriptive statistics

Standard deviation196.04997
Coefficient of variation (CV)6.006954
Kurtosis95.680088
Mean32.637168
Median Absolute Deviation (MAD)2
Skewness9.55758
Sum3688
Variance38435.59
MonotonicityNot monotonic
2023-12-13T04:50:12.732522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 38
 
4.6%
2 17
 
2.1%
3 12
 
1.5%
4 10
 
1.2%
5 3
 
0.4%
6 3
 
0.4%
27 3
 
0.4%
44 2
 
0.2%
31 2
 
0.2%
8 2
 
0.2%
Other values (20) 21
 
2.6%
(Missing) 705
86.2%
ValueCountFrequency (%)
1 38
4.6%
2 17
2.1%
3 12
 
1.5%
4 10
 
1.2%
5 3
 
0.4%
6 3
 
0.4%
7 1
 
0.1%
8 2
 
0.2%
11 2
 
0.2%
12 1
 
0.1%
ValueCountFrequency (%)
2014 1
0.1%
558 1
0.1%
164 1
0.1%
82 1
0.1%
55 1
0.1%
51 1
0.1%
46 1
0.1%
44 2
0.2%
42 1
0.1%
35 1
0.1%

Unnamed: 3
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)23.8%
Missing696
Missing (%)85.1%
Infinite0
Infinite (%)0.0%
Mean31.959016
Minimum1
Maximum2015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:12.896489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q37.75
95-th percentile51.5
Maximum2015
Range2014
Interquartile range (IQR)6.75

Descriptive statistics

Standard deviation191.50031
Coefficient of variation (CV)5.9920591
Kurtosis97.617664
Mean31.959016
Median Absolute Deviation (MAD)1
Skewness9.5947055
Sum3899
Variance36672.37
MonotonicityNot monotonic
2023-12-13T04:50:13.042171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 43
 
5.3%
2 21
 
2.6%
3 12
 
1.5%
4 7
 
0.9%
5 4
 
0.5%
7 3
 
0.4%
9 3
 
0.4%
10 2
 
0.2%
12 2
 
0.2%
30 2
 
0.2%
Other values (19) 23
 
2.8%
(Missing) 696
85.1%
ValueCountFrequency (%)
1 43
5.3%
2 21
2.6%
3 12
 
1.5%
4 7
 
0.9%
5 4
 
0.5%
6 1
 
0.1%
7 3
 
0.4%
8 2
 
0.2%
9 3
 
0.4%
10 2
 
0.2%
ValueCountFrequency (%)
2015 1
0.1%
628 1
0.1%
251 1
0.1%
147 1
0.1%
59 1
0.1%
53 1
0.1%
52 1
0.1%
42 1
0.1%
39 1
0.1%
37 1
0.1%

Unnamed: 4
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)28.2%
Missing708
Missing (%)86.6%
Infinite0
Infinite (%)0.0%
Mean34.745455
Minimum1
Maximum2016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:13.198999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q37.5
95-th percentile42.1
Maximum2016
Range2015
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation201.45896
Coefficient of variation (CV)5.7981387
Kurtosis88.228559
Mean34.745455
Median Absolute Deviation (MAD)1
Skewness9.1143754
Sum3822
Variance40585.714
MonotonicityNot monotonic
2023-12-13T04:50:13.335805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 40
 
4.9%
2 22
 
2.7%
3 9
 
1.1%
4 8
 
1.0%
11 3
 
0.4%
18 2
 
0.2%
5 2
 
0.2%
10 1
 
0.1%
15 1
 
0.1%
12 1
 
0.1%
Other values (21) 21
 
2.6%
(Missing) 708
86.6%
ValueCountFrequency (%)
1 40
4.9%
2 22
2.7%
3 9
 
1.1%
4 8
 
1.0%
5 2
 
0.2%
6 1
 
0.1%
8 1
 
0.1%
10 1
 
0.1%
11 3
 
0.4%
12 1
 
0.1%
ValueCountFrequency (%)
2016 1
0.1%
602 1
0.1%
289 1
0.1%
163 1
0.1%
71 1
0.1%
43 1
0.1%
41 1
0.1%
37 1
0.1%
35 1
0.1%
34 1
0.1%

Unnamed: 5
Real number (ℝ)

MISSING 

Distinct28
Distinct (%)25.9%
Missing710
Missing (%)86.8%
Infinite0
Infinite (%)0.0%
Mean30.787037
Minimum1
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:13.477190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q36.25
95-th percentile35.95
Maximum2017
Range2016
Interquartile range (IQR)5.25

Descriptive statistics

Standard deviation198.10396
Coefficient of variation (CV)6.4346549
Kurtosis96.974378
Mean30.787037
Median Absolute Deviation (MAD)1
Skewness9.6784203
Sum3325
Variance39245.179
MonotonicityNot monotonic
2023-12-13T04:50:13.626086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 42
 
5.1%
2 20
 
2.4%
3 9
 
1.1%
4 6
 
0.7%
18 3
 
0.4%
6 2
 
0.2%
5 2
 
0.2%
7 2
 
0.2%
8 2
 
0.2%
14 2
 
0.2%
Other values (18) 18
 
2.2%
(Missing) 710
86.8%
ValueCountFrequency (%)
1 42
5.1%
2 20
2.4%
3 9
 
1.1%
4 6
 
0.7%
5 2
 
0.2%
6 2
 
0.2%
7 2
 
0.2%
8 2
 
0.2%
13 1
 
0.1%
14 2
 
0.2%
ValueCountFrequency (%)
2017 1
0.1%
436 1
0.1%
155 1
0.1%
81 1
0.1%
42 1
0.1%
37 1
0.1%
34 1
0.1%
32 1
0.1%
31 1
0.1%
28 1
0.1%

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing651
Missing (%)79.6%
Memory size6.5 KiB

감염병감시과, 2018.5.24
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing818
Missing (%)100.0%
Memory size7.3 KiB

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing818
Missing (%)100.0%
Memory size7.3 KiB

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing818
Missing (%)100.0%
Memory size7.3 KiB

Unnamed: 10
Categorical

IMBALANCE 

Distinct31
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
690 
군인
 
12
기타
 
12
농업 및 어업숙련 종사자
 
10
학생
 
10
Other values (26)
84 

Length

Max length30
Median length4
Mean length4.2958435
Min length2

Unique

Unique16 ?
Unique (%)2.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row2013~2017년 말라리아 국내발생 월별/직업별 현황
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 690
84.4%
군인 12
 
1.5%
기타 12
 
1.5%
농업 및 어업숙련 종사자 10
 
1.2%
학생 10
 
1.2%
무직 9
 
1.1%
기술공 및 준전문가 8
 
1.0%
단순노무 종사자 8
 
1.0%
서비스종사자 8
 
1.0%
판매종사자 7
 
0.9%
Other values (21) 44
 
5.4%

Length

2023-12-13T04:50:13.775653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 690
76.4%
및 29
 
3.2%
종사자 23
 
2.5%
기타 12
 
1.3%
군인 12
 
1.3%
농업 10
 
1.1%
어업숙련 10
 
1.1%
학생 10
 
1.1%
무직 9
 
1.0%
단순노무 8
 
0.9%
Other values (31) 90
 
10.0%

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing732
Missing (%)89.5%
Memory size6.5 KiB

Unnamed: 12
Real number (ℝ)

MISSING 

Distinct28
Distinct (%)33.3%
Missing734
Missing (%)89.7%
Infinite0
Infinite (%)0.0%
Mean43.904762
Minimum1
Maximum2014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:13.920748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q310
95-th percentile97.75
Maximum2014
Range2013
Interquartile range (IQR)8

Descriptive statistics

Standard deviation227.15212
Coefficient of variation (CV)5.1737468
Kurtosis70.513093
Mean43.904762
Median Absolute Deviation (MAD)3
Skewness8.1926054
Sum3688
Variance51598.087
MonotonicityNot monotonic
2023-12-13T04:50:14.070282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 18
 
2.2%
2 13
 
1.6%
3 9
 
1.1%
5 8
 
1.0%
4 6
 
0.7%
10 3
 
0.4%
9 3
 
0.4%
7 2
 
0.2%
41 2
 
0.2%
6 2
 
0.2%
Other values (18) 18
 
2.2%
(Missing) 734
89.7%
ValueCountFrequency (%)
1 18
2.2%
2 13
1.6%
3 9
1.1%
4 6
 
0.7%
5 8
1.0%
6 2
 
0.2%
7 2
 
0.2%
9 3
 
0.4%
10 3
 
0.4%
11 1
 
0.1%
ValueCountFrequency (%)
2014 1
0.1%
558 1
0.1%
153 1
0.1%
130 1
0.1%
100 1
0.1%
85 1
0.1%
73 1
0.1%
66 1
0.1%
44 1
0.1%
41 2
0.2%

Unnamed: 13
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)31.2%
Missing725
Missing (%)88.6%
Infinite0
Infinite (%)0.0%
Mean41.924731
Minimum1
Maximum2015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:14.233564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q312
95-th percentile97.4
Maximum2015
Range2014
Interquartile range (IQR)11

Descriptive statistics

Standard deviation218.08217
Coefficient of variation (CV)5.2017547
Kurtosis75.244707
Mean41.924731
Median Absolute Deviation (MAD)2
Skewness8.4402606
Sum3899
Variance47559.831
MonotonicityNot monotonic
2023-12-13T04:50:14.413405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 28
 
3.4%
2 13
 
1.6%
3 10
 
1.2%
6 4
 
0.5%
4 4
 
0.5%
12 3
 
0.4%
10 3
 
0.4%
35 3
 
0.4%
14 3
 
0.4%
8 2
 
0.2%
Other values (19) 20
 
2.4%
(Missing) 725
88.6%
ValueCountFrequency (%)
1 28
3.4%
2 13
1.6%
3 10
 
1.2%
4 4
 
0.5%
5 2
 
0.2%
6 4
 
0.5%
7 1
 
0.1%
8 2
 
0.2%
10 3
 
0.4%
11 1
 
0.1%
ValueCountFrequency (%)
2015 1
0.1%
628 1
0.1%
144 1
0.1%
131 1
0.1%
122 1
0.1%
81 1
0.1%
71 1
0.1%
69 1
0.1%
53 1
0.1%
51 1
0.1%

Unnamed: 14
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)32.2%
Missing728
Missing (%)89.0%
Infinite0
Infinite (%)0.0%
Mean42.466667
Minimum1
Maximum2016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:14.546549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q310.75
95-th percentile85.85
Maximum2016
Range2015
Interquartile range (IQR)9.75

Descriptive statistics

Standard deviation220.9621
Coefficient of variation (CV)5.2031893
Kurtosis73.881368
Mean42.466667
Median Absolute Deviation (MAD)2
Skewness8.3719179
Sum3822
Variance48824.252
MonotonicityNot monotonic
2023-12-13T04:50:14.696970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 30
 
3.7%
4 11
 
1.3%
2 11
 
1.3%
3 6
 
0.7%
8 3
 
0.4%
30 2
 
0.2%
5 2
 
0.2%
10 2
 
0.2%
71 2
 
0.2%
15 2
 
0.2%
Other values (19) 19
 
2.3%
(Missing) 728
89.0%
ValueCountFrequency (%)
1 30
3.7%
2 11
 
1.3%
3 6
 
0.7%
4 11
 
1.3%
5 2
 
0.2%
7 1
 
0.1%
8 3
 
0.4%
9 1
 
0.1%
10 2
 
0.2%
11 1
 
0.1%
ValueCountFrequency (%)
2016 1
0.1%
602 1
0.1%
152 1
0.1%
136 1
0.1%
98 1
0.1%
71 2
0.2%
64 1
0.1%
51 1
0.1%
48 1
0.1%
45 1
0.1%

Unnamed: 15
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)33.3%
Missing740
Missing (%)90.5%
Infinite0
Infinite (%)0.0%
Mean42.628205
Minimum1
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:14.854264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11.25
median3
Q39.75
95-th percentile81.7
Maximum2017
Range2016
Interquartile range (IQR)8.5

Descriptive statistics

Standard deviation232.53265
Coefficient of variation (CV)5.4549012
Kurtosis69.964063
Mean42.628205
Median Absolute Deviation (MAD)2
Skewness8.219943
Sum3325
Variance54071.431
MonotonicityNot monotonic
2023-12-13T04:50:15.001693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 20
 
2.4%
2 17
 
2.1%
3 9
 
1.1%
6 3
 
0.4%
9 2
 
0.2%
5 2
 
0.2%
10 2
 
0.2%
7 2
 
0.2%
31 2
 
0.2%
4 2
 
0.2%
Other values (16) 17
 
2.1%
(Missing) 740
90.5%
ValueCountFrequency (%)
1 20
2.4%
2 17
2.1%
3 9
1.1%
4 2
 
0.2%
5 2
 
0.2%
6 3
 
0.4%
7 2
 
0.2%
8 1
 
0.1%
9 2
 
0.2%
10 2
 
0.2%
ValueCountFrequency (%)
2017 1
0.1%
436 1
0.1%
122 1
0.1%
97 1
0.1%
79 1
0.1%
67 1
0.1%
53 1
0.1%
49 1
0.1%
31 2
0.2%
30 1
0.1%

Unnamed: 16
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing691
Missing (%)84.5%
Memory size6.5 KiB

Unnamed: 17
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing818
Missing (%)100.0%
Memory size7.3 KiB

Unnamed: 18
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing818
Missing (%)100.0%
Memory size7.3 KiB

Unnamed: 19
Text

Distinct208
Distinct (%)25.6%
Missing7
Missing (%)0.9%
Memory size6.5 KiB
2023-12-13T04:50:15.228741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length2
Mean length3.7694205
Min length2

Characters and Unicode

Total characters3057
Distinct characters170
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique189 ?
Unique (%)23.3%

Sample

1st row2013~2017년 말라리아 국내발생 지역별/직업별 현황
2nd row지역별/직업별
3rd row서울
4th row중구
5th row군인
ValueCountFrequency (%)
기타 155
15.6%
학생 101
 
10.2%
군인 87
 
8.8%
무직 58
 
5.8%
및 50
 
5.0%
종사자 43
 
4.3%
사무종사자 42
 
4.2%
서비스종사자 27
 
2.7%
전업)주부 27
 
2.7%
단순노무 21
 
2.1%
Other values (216) 381
38.4%
2023-12-13T04:50:15.944737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
205
 
6.7%
기 202
 
6.6%
사 187
 
6.1%
타 155
 
5.1%
종 143
 
4.7%
자 142
 
4.6%
무 122
 
4.0%
군 121
 
4.0%
구 105
 
3.4%
생 102
 
3.3%
Other values (160) 1573
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2778
90.9%
Space Separator 205
 
6.7%
Close Punctuation 27
 
0.9%
Open Punctuation 27
 
0.9%
Other Punctuation 11
 
0.4%
Decimal Number 8
 
0.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 202
 
7.3%
사 187
 
6.7%
타 155
 
5.6%
종 143
 
5.1%
자 142
 
5.1%
무 122
 
4.4%
군 121
 
4.4%
구 105
 
3.8%
생 102
 
3.7%
학 101
 
3.6%
Other values (149) 1398
50.3%
Decimal Number
ValueCountFrequency (%)
1 2
25.0%
0 2
25.0%
2 2
25.0%
7 1
12.5%
3 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 9
81.8%
/ 2
 
18.2%
Space Separator
ValueCountFrequency (%)
205
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2778
90.9%
Common 279
 
9.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 202
 
7.3%
사 187
 
6.7%
타 155
 
5.6%
종 143
 
5.1%
자 142
 
5.1%
무 122
 
4.4%
군 121
 
4.4%
구 105
 
3.8%
생 102
 
3.7%
학 101
 
3.6%
Other values (149) 1398
50.3%
Common
ValueCountFrequency (%)
205
73.5%
) 27
 
9.7%
( 27
 
9.7%
, 9
 
3.2%
1 2
 
0.7%
0 2
 
0.7%
2 2
 
0.7%
/ 2
 
0.7%
7 1
 
0.4%
~ 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2778
90.9%
ASCII 279
 
9.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
205
73.5%
) 27
 
9.7%
( 27
 
9.7%
, 9
 
3.2%
1 2
 
0.7%
0 2
 
0.7%
2 2
 
0.7%
/ 2
 
0.7%
7 1
 
0.4%
~ 1
 
0.4%
Hangul
ValueCountFrequency (%)
기 202
 
7.3%
사 187
 
6.7%
타 155
 
5.6%
종 143
 
5.1%
자 142
 
5.1%
무 122
 
4.4%
군 121
 
4.4%
구 105
 
3.8%
생 102
 
3.7%
학 101
 
3.6%
Other values (149) 1398
50.3%

Unnamed: 20
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing522
Missing (%)63.8%
Memory size6.5 KiB

Unnamed: 21
Real number (ℝ)

MISSING 

Distinct30
Distinct (%)8.5%
Missing464
Missing (%)56.7%
Infinite0
Infinite (%)0.0%
Mean11.99435
Minimum1
Maximum2014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:16.094539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile13.35
Maximum2014
Range2013
Interquartile range (IQR)2

Descriptive statistics

Standard deviation112.14474
Coefficient of variation (CV)9.3497967
Kurtosis291.35699
Mean11.99435
Median Absolute Deviation (MAD)0
Skewness16.583534
Sum4246
Variance12576.442
MonotonicityNot monotonic
2023-12-13T04:50:16.322428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 195
23.8%
2 50
 
6.1%
3 29
 
3.5%
4 19
 
2.3%
5 11
 
1.3%
11 7
 
0.9%
6 7
 
0.9%
9 4
 
0.5%
7 4
 
0.5%
10 3
 
0.4%
Other values (20) 25
 
3.1%
(Missing) 464
56.7%
ValueCountFrequency (%)
1 195
23.8%
2 50
 
6.1%
3 29
 
3.5%
4 19
 
2.3%
5 11
 
1.3%
6 7
 
0.9%
7 4
 
0.5%
8 3
 
0.4%
9 4
 
0.5%
10 3
 
0.4%
ValueCountFrequency (%)
2014 1
0.1%
558 1
0.1%
289 1
0.1%
123 1
0.1%
76 1
0.1%
73 1
0.1%
44 1
0.1%
37 1
0.1%
32 1
0.1%
30 1
0.1%

Unnamed: 22
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)7.7%
Missing439
Missing (%)53.7%
Infinite0
Infinite (%)0.0%
Mean11.944591
Minimum1
Maximum2015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:16.516735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile13
Maximum2015
Range2014
Interquartile range (IQR)2

Descriptive statistics

Standard deviation110.36373
Coefficient of variation (CV)9.2396408
Kurtosis291.6447
Mean11.944591
Median Absolute Deviation (MAD)0
Skewness16.47956
Sum4527
Variance12180.153
MonotonicityNot monotonic
2023-12-13T04:50:16.713188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 208
25.4%
2 61
 
7.5%
3 39
 
4.8%
4 14
 
1.7%
6 12
 
1.5%
5 6
 
0.7%
7 6
 
0.7%
9 4
 
0.5%
11 3
 
0.4%
10 3
 
0.4%
Other values (19) 23
 
2.8%
(Missing) 439
53.7%
ValueCountFrequency (%)
1 208
25.4%
2 61
 
7.5%
3 39
 
4.8%
4 14
 
1.7%
5 6
 
0.7%
6 12
 
1.5%
7 6
 
0.7%
8 2
 
0.2%
9 4
 
0.5%
10 3
 
0.4%
ValueCountFrequency (%)
2015 1
0.1%
628 1
0.1%
398 1
0.1%
105 1
0.1%
75 2
0.2%
72 1
0.1%
64 1
0.1%
52 1
0.1%
46 1
0.1%
36 1
0.1%

Unnamed: 23
Real number (ℝ)

MISSING 

Distinct30
Distinct (%)7.9%
Missing437
Missing (%)53.4%
Infinite0
Infinite (%)0.0%
Mean11.611549
Minimum1
Maximum2016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:16.928753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile17
Maximum2016
Range2015
Interquartile range (IQR)2

Descriptive statistics

Standard deviation109.3359
Coefficient of variation (CV)9.4161339
Kurtosis301.49594
Mean11.611549
Median Absolute Deviation (MAD)0
Skewness16.804594
Sum4424
Variance11954.338
MonotonicityNot monotonic
2023-12-13T04:50:17.118774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 212
25.9%
2 57
 
7.0%
3 39
 
4.8%
4 15
 
1.8%
5 10
 
1.2%
7 8
 
1.0%
6 7
 
0.9%
9 6
 
0.7%
8 2
 
0.2%
23 2
 
0.2%
Other values (20) 23
 
2.8%
(Missing) 437
53.4%
ValueCountFrequency (%)
1 212
25.9%
2 57
 
7.0%
3 39
 
4.8%
4 15
 
1.8%
5 10
 
1.2%
6 7
 
0.9%
7 8
 
1.0%
8 2
 
0.2%
9 6
 
0.7%
10 1
 
0.1%
ValueCountFrequency (%)
2016 1
0.1%
602 1
0.1%
363 1
0.1%
80 1
0.1%
75 1
0.1%
68 1
0.1%
53 1
0.1%
50 1
0.1%
49 1
0.1%
39 2
0.2%

Unnamed: 24
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)9.3%
Missing505
Missing (%)61.7%
Infinite0
Infinite (%)0.0%
Mean12.015974
Minimum1
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:17.299739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile14.2
Maximum2017
Range2016
Interquartile range (IQR)1

Descriptive statistics

Standard deviation117.47819
Coefficient of variation (CV)9.7768341
Kurtosis274.81362
Mean12.015974
Median Absolute Deviation (MAD)0
Skewness16.221695
Sum3761
Variance13801.125
MonotonicityNot monotonic
2023-12-13T04:50:17.487456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 180
 
22.0%
2 57
 
7.0%
3 24
 
2.9%
4 11
 
1.3%
5 6
 
0.7%
8 5
 
0.6%
7 3
 
0.4%
10 2
 
0.2%
6 2
 
0.2%
12 2
 
0.2%
Other values (19) 21
 
2.6%
(Missing) 505
61.7%
ValueCountFrequency (%)
1 180
22.0%
2 57
 
7.0%
3 24
 
2.9%
4 11
 
1.3%
5 6
 
0.7%
6 2
 
0.2%
7 3
 
0.4%
8 5
 
0.6%
9 2
 
0.2%
10 2
 
0.2%
ValueCountFrequency (%)
2017 1
0.1%
436 1
0.1%
270 1
0.1%
72 1
0.1%
55 1
0.1%
43 1
0.1%
38 1
0.1%
37 1
0.1%
33 1
0.1%
29 1
0.1%

Unnamed: 25
Unsupported

REJECTED  UNSUPPORTED 

Missing7
Missing (%)0.9%
Memory size6.5 KiB

Unnamed: 26
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing818
Missing (%)100.0%
Memory size7.3 KiB

Unnamed: 27
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing818
Missing (%)100.0%
Memory size7.3 KiB

Unnamed: 28
Text

MISSING 

Distinct71
Distinct (%)41.8%
Missing648
Missing (%)79.2%
Memory size6.5 KiB
2023-12-13T04:50:17.856867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length14
Mean length5.2176471
Min length2

Characters and Unicode

Total characters887
Distinct characters103
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)25.9%

Sample

1st row2013~2017년 말라리아 국내발생 지역별/연령별/월별/직업별 현황 (인천, 강원지역)
2nd row지역/연령/직업
3rd row서울
4th row부산
5th row대구
ValueCountFrequency (%)
및 22
 
9.1%
기타 21
 
8.7%
종사자 21
 
8.7%
어업숙련 16
 
6.6%
농업 16
 
6.6%
무직 13
 
5.4%
전업)주부 10
 
4.1%
서비스종사자 7
 
2.9%
군인 6
 
2.5%
학생 6
 
2.5%
Other values (71) 103
42.7%
2023-12-13T04:50:18.462659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
76
 
8.6%
업 44
 
5.0%
사 41
 
4.6%
종 37
 
4.2%
자 36
 
4.1%
세 33
 
3.7%
- 32
 
3.6%
기 30
 
3.4%
4 24
 
2.7%
5 24
 
2.7%
Other values (93) 510
57.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 614
69.2%
Decimal Number 136
 
15.3%
Space Separator 76
 
8.6%
Dash Punctuation 32
 
3.6%
Close Punctuation 11
 
1.2%
Open Punctuation 11
 
1.2%
Other Punctuation 6
 
0.7%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 44
 
7.2%
사 41
 
6.7%
종 37
 
6.0%
자 36
 
5.9%
세 33
 
5.4%
기 30
 
4.9%
및 22
 
3.6%
타 21
 
3.4%
무 21
 
3.4%
전 19
 
3.1%
Other values (76) 310
50.5%
Decimal Number
ValueCountFrequency (%)
4 24
17.6%
5 24
17.6%
0 20
14.7%
9 18
13.2%
2 10
7.4%
1 10
7.4%
7 9
 
6.6%
6 8
 
5.9%
3 7
 
5.1%
8 6
 
4.4%
Other Punctuation
ValueCountFrequency (%)
/ 5
83.3%
, 1
 
16.7%
Space Separator
ValueCountFrequency (%)
76
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 614
69.2%
Common 273
30.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 44
 
7.2%
사 41
 
6.7%
종 37
 
6.0%
자 36
 
5.9%
세 33
 
5.4%
기 30
 
4.9%
및 22
 
3.6%
타 21
 
3.4%
무 21
 
3.4%
전 19
 
3.1%
Other values (76) 310
50.5%
Common
ValueCountFrequency (%)
76
27.8%
- 32
11.7%
4 24
 
8.8%
5 24
 
8.8%
0 20
 
7.3%
9 18
 
6.6%
) 11
 
4.0%
( 11
 
4.0%
2 10
 
3.7%
1 10
 
3.7%
Other values (7) 37
13.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 614
69.2%
ASCII 273
30.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
76
27.8%
- 32
11.7%
4 24
 
8.8%
5 24
 
8.8%
0 20
 
7.3%
9 18
 
6.6%
) 11
 
4.0%
( 11
 
4.0%
2 10
 
3.7%
1 10
 
3.7%
Other values (7) 37
13.6%
Hangul
ValueCountFrequency (%)
업 44
 
7.2%
사 41
 
6.7%
종 37
 
6.0%
자 36
 
5.9%
세 33
 
5.4%
기 30
 
4.9%
및 22
 
3.6%
타 21
 
3.4%
무 21
 
3.4%
전 19
 
3.1%
Other values (76) 310
50.5%

Unnamed: 29
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)99.3%
Memory size6.5 KiB

Unnamed: 30
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
809 
1
 
4
2
 
2
3
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.9669927
Min length1

Unique

Unique3 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 809
98.9%
1 4
 
0.5%
2 2
 
0.2%
3 1
 
0.1%
5 1
 
0.1%
7 1
 
0.1%

Length

2023-12-13T04:50:18.684876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:18.824982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 809
98.9%
1 4
 
0.5%
2 2
 
0.2%
3 1
 
0.1%
5 1
 
0.1%
7 1
 
0.1%

Unnamed: 31
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
803 
1
 
11
4
 
1
2
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.9462103
Min length1

Unique

Unique4 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 803
98.2%
1 11
 
1.3%
4 1
 
0.1%
2 1
 
0.1%
6 1
 
0.1%
12 1
 
0.1%

Length

2023-12-13T04:50:18.964901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:19.135060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 803
98.2%
1 11
 
1.3%
4 1
 
0.1%
2 1
 
0.1%
6 1
 
0.1%
12 1
 
0.1%

Unnamed: 32
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)30.4%
Missing795
Missing (%)97.2%
Infinite0
Infinite (%)0.0%
Mean5.4782609
Minimum1
Maximum47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:19.275811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34.5
95-th percentile24.9
Maximum47
Range46
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation10.535091
Coefficient of variation (CV)1.9230722
Kurtosis12.021329
Mean5.4782609
Median Absolute Deviation (MAD)1
Skewness3.4261016
Sum126
Variance110.98814
MonotonicityNot monotonic
2023-12-13T04:50:19.407338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 11
 
1.3%
4 4
 
0.5%
5 3
 
0.4%
2 2
 
0.2%
6 1
 
0.1%
27 1
 
0.1%
47 1
 
0.1%
(Missing) 795
97.2%
ValueCountFrequency (%)
1 11
1.3%
2 2
 
0.2%
4 4
 
0.5%
5 3
 
0.4%
6 1
 
0.1%
27 1
 
0.1%
47 1
 
0.1%
ValueCountFrequency (%)
47 1
 
0.1%
27 1
 
0.1%
6 1
 
0.1%
5 3
 
0.4%
4 4
 
0.5%
2 2
 
0.2%
1 11
1.3%

Unnamed: 33
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)25.6%
Missing779
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean5.2307692
Minimum1
Maximum75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:19.528546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32.5
95-th percentile16.1
Maximum75
Range74
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation12.872781
Coefficient of variation (CV)2.4609729
Kurtosis24.23923
Mean5.2307692
Median Absolute Deviation (MAD)1
Skewness4.7452458
Sum204
Variance165.7085
MonotonicityNot monotonic
2023-12-13T04:50:19.644908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 19
 
2.3%
2 10
 
1.2%
6 2
 
0.2%
7 2
 
0.2%
14 1
 
0.1%
3 1
 
0.1%
35 1
 
0.1%
8 1
 
0.1%
4 1
 
0.1%
75 1
 
0.1%
(Missing) 779
95.2%
ValueCountFrequency (%)
1 19
2.3%
2 10
1.2%
3 1
 
0.1%
4 1
 
0.1%
6 2
 
0.2%
7 2
 
0.2%
8 1
 
0.1%
14 1
 
0.1%
35 1
 
0.1%
75 1
 
0.1%
ValueCountFrequency (%)
75 1
 
0.1%
35 1
 
0.1%
14 1
 
0.1%
8 1
 
0.1%
7 2
 
0.2%
6 2
 
0.2%
4 1
 
0.1%
3 1
 
0.1%
2 10
1.2%
1 19
2.3%

Unnamed: 34
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)20.0%
Missing773
Missing (%)94.5%
Infinite0
Infinite (%)0.0%
Mean5.3333333
Minimum1
Maximum91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:19.761579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile17.8
Maximum91
Range90
Interquartile range (IQR)1

Descriptive statistics

Standard deviation15.240496
Coefficient of variation (CV)2.8575931
Kurtosis24.73873
Mean5.3333333
Median Absolute Deviation (MAD)0
Skewness4.8264715
Sum240
Variance232.27273
MonotonicityNot monotonic
2023-12-13T04:50:19.927789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 31
 
3.8%
2 5
 
0.6%
9 2
 
0.2%
4 2
 
0.2%
7 1
 
0.1%
20 1
 
0.1%
50 1
 
0.1%
5 1
 
0.1%
91 1
 
0.1%
(Missing) 773
94.5%
ValueCountFrequency (%)
1 31
3.8%
2 5
 
0.6%
4 2
 
0.2%
5 1
 
0.1%
7 1
 
0.1%
9 2
 
0.2%
20 1
 
0.1%
50 1
 
0.1%
91 1
 
0.1%
ValueCountFrequency (%)
91 1
 
0.1%
50 1
 
0.1%
20 1
 
0.1%
9 2
 
0.2%
7 1
 
0.1%
5 1
 
0.1%
4 2
 
0.2%
2 5
 
0.6%
1 31
3.8%

Unnamed: 35
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)29.0%
Missing787
Missing (%)96.2%
Infinite0
Infinite (%)0.0%
Mean5.1290323
Minimum1
Maximum62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:20.026357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32.5
95-th percentile23
Maximum62
Range61
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation12.107138
Coefficient of variation (CV)2.3605112
Kurtosis17.379828
Mean5.1290323
Median Absolute Deviation (MAD)0
Skewness4.0295045
Sum159
Variance146.5828
MonotonicityNot monotonic
2023-12-13T04:50:20.136465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 21
 
2.6%
4 2
 
0.2%
2 2
 
0.2%
8 1
 
0.1%
7 1
 
0.1%
15 1
 
0.1%
3 1
 
0.1%
31 1
 
0.1%
62 1
 
0.1%
(Missing) 787
96.2%
ValueCountFrequency (%)
1 21
2.6%
2 2
 
0.2%
3 1
 
0.1%
4 2
 
0.2%
7 1
 
0.1%
8 1
 
0.1%
15 1
 
0.1%
31 1
 
0.1%
62 1
 
0.1%
ValueCountFrequency (%)
62 1
 
0.1%
31 1
 
0.1%
15 1
 
0.1%
8 1
 
0.1%
7 1
 
0.1%
4 2
 
0.2%
3 1
 
0.1%
2 2
 
0.2%
1 21
2.6%

Unnamed: 36
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)34.8%
Missing795
Missing (%)97.2%
Infinite0
Infinite (%)0.0%
Mean5.3043478
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:20.245714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32.5
95-th percentile27
Maximum50
Range49
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation11.431356
Coefficient of variation (CV)2.1550916
Kurtosis11.626316
Mean5.3043478
Median Absolute Deviation (MAD)0
Skewness3.3796457
Sum122
Variance130.67589
MonotonicityNot monotonic
2023-12-13T04:50:20.353098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 14
 
1.7%
2 3
 
0.4%
9 1
 
0.1%
4 1
 
0.1%
7 1
 
0.1%
3 1
 
0.1%
29 1
 
0.1%
50 1
 
0.1%
(Missing) 795
97.2%
ValueCountFrequency (%)
1 14
1.7%
2 3
 
0.4%
3 1
 
0.1%
4 1
 
0.1%
7 1
 
0.1%
9 1
 
0.1%
29 1
 
0.1%
50 1
 
0.1%
ValueCountFrequency (%)
50 1
 
0.1%
29 1
 
0.1%
9 1
 
0.1%
7 1
 
0.1%
4 1
 
0.1%
3 1
 
0.1%
2 3
 
0.4%
1 14
1.7%

Unnamed: 37
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)45.0%
Missing798
Missing (%)97.6%
Infinite0
Infinite (%)0.0%
Mean5.15
Minimum1
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:20.443858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1.5
Q34.25
95-th percentile18.85
Maximum35
Range34
Interquartile range (IQR)3.25

Descriptive statistics

Standard deviation8.3808993
Coefficient of variation (CV)1.6273591
Kurtosis8.5733472
Mean5.15
Median Absolute Deviation (MAD)0.5
Skewness2.8147888
Sum103
Variance70.239474
MonotonicityNot monotonic
2023-12-13T04:50:20.539102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 10
 
1.2%
2 3
 
0.4%
10 1
 
0.1%
3 1
 
0.1%
12 1
 
0.1%
4 1
 
0.1%
5 1
 
0.1%
18 1
 
0.1%
35 1
 
0.1%
(Missing) 798
97.6%
ValueCountFrequency (%)
1 10
1.2%
2 3
 
0.4%
3 1
 
0.1%
4 1
 
0.1%
5 1
 
0.1%
10 1
 
0.1%
12 1
 
0.1%
18 1
 
0.1%
35 1
 
0.1%
ValueCountFrequency (%)
35 1
 
0.1%
18 1
 
0.1%
12 1
 
0.1%
10 1
 
0.1%
5 1
 
0.1%
4 1
 
0.1%
3 1
 
0.1%
2 3
 
0.4%
1 10
1.2%

Unnamed: 38
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
812 
1
 
3
11
 
1
2
 
1
4
 
1

Length

Max length4
Median length4
Mean length3.9792176
Min length1

Unique

Unique3 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 812
99.3%
1 3
 
0.4%
11 1
 
0.1%
2 1
 
0.1%
4 1
 
0.1%

Length

2023-12-13T04:50:20.684704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:20.804208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 812
99.3%
1 3
 
0.4%
11 1
 
0.1%
2 1
 
0.1%
4 1
 
0.1%

Unnamed: 39
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing737
Missing (%)90.1%
Memory size6.5 KiB

Unnamed: 40
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
814 
1
 
2
2014
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.9889976
Min length1

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 814
99.5%
1 2
 
0.2%
2014 1
 
0.1%
2 1
 
0.1%

Length

2023-12-13T04:50:20.926111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:21.025196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 814
99.5%
1 2
 
0.2%
2014 1
 
0.1%
2 1
 
0.1%

Unnamed: 41
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
809 
1
 
6
4
 
1
5
 
1
10
 
1

Length

Max length4
Median length4
Mean length3.9682152
Min length1

Unique

Unique3 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 809
98.9%
1 6
 
0.7%
4 1
 
0.1%
5 1
 
0.1%
10 1
 
0.1%

Length

2023-12-13T04:50:21.124900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:21.258548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 809
98.9%
1 6
 
0.7%
4 1
 
0.1%
5 1
 
0.1%
10 1
 
0.1%

Unnamed: 42
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)31.6%
Missing799
Missing (%)97.7%
Infinite0
Infinite (%)0.0%
Mean3.1052632
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:21.344615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32.5
95-th percentile11.1
Maximum21
Range20
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation4.9091155
Coefficient of variation (CV)1.5809016
Kurtosis10.469703
Mean3.1052632
Median Absolute Deviation (MAD)0
Skewness3.1222364
Sum59
Variance24.099415
MonotonicityNot monotonic
2023-12-13T04:50:21.445724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 13
 
1.6%
5 2
 
0.2%
3 1
 
0.1%
2 1
 
0.1%
10 1
 
0.1%
21 1
 
0.1%
(Missing) 799
97.7%
ValueCountFrequency (%)
1 13
1.6%
2 1
 
0.1%
3 1
 
0.1%
5 2
 
0.2%
10 1
 
0.1%
21 1
 
0.1%
ValueCountFrequency (%)
21 1
 
0.1%
10 1
 
0.1%
5 2
 
0.2%
3 1
 
0.1%
2 1
 
0.1%
1 13
1.6%

Unnamed: 43
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)43.5%
Missing795
Missing (%)97.2%
Infinite0
Infinite (%)0.0%
Mean10.217391
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:21.567799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile55.2
Maximum100
Range99
Interquartile range (IQR)4

Descriptive statistics

Standard deviation23.186902
Coefficient of variation (CV)2.2693563
Kurtosis11.165414
Mean10.217391
Median Absolute Deviation (MAD)1
Skewness3.3153501
Sum235
Variance537.63241
MonotonicityNot monotonic
2023-12-13T04:50:21.690630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 9
 
1.1%
2 5
 
0.6%
3 2
 
0.2%
6 1
 
0.1%
12 1
 
0.1%
21 1
 
0.1%
8 1
 
0.1%
4 1
 
0.1%
59 1
 
0.1%
100 1
 
0.1%
(Missing) 795
97.2%
ValueCountFrequency (%)
1 9
1.1%
2 5
0.6%
3 2
 
0.2%
4 1
 
0.1%
6 1
 
0.1%
8 1
 
0.1%
12 1
 
0.1%
21 1
 
0.1%
59 1
 
0.1%
100 1
 
0.1%
ValueCountFrequency (%)
100 1
 
0.1%
59 1
 
0.1%
21 1
 
0.1%
12 1
 
0.1%
8 1
 
0.1%
6 1
 
0.1%
4 1
 
0.1%
3 2
 
0.2%
2 5
0.6%
1 9
1.1%

Unnamed: 44
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)28.6%
Missing776
Missing (%)94.9%
Infinite0
Infinite (%)0.0%
Mean8.9761905
Minimum1
Maximum153
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:21.790860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33.75
95-th percentile35.25
Maximum153
Range152
Interquartile range (IQR)2.75

Descriptive statistics

Standard deviation26.176221
Coefficient of variation (CV)2.9161838
Kurtosis23.971861
Mean8.9761905
Median Absolute Deviation (MAD)1
Skewness4.7262963
Sum377
Variance685.19454
MonotonicityNot monotonic
2023-12-13T04:50:21.916649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 18
 
2.2%
2 11
 
1.3%
6 2
 
0.2%
4 2
 
0.2%
3 2
 
0.2%
7 1
 
0.1%
21 1
 
0.1%
36 1
 
0.1%
12 1
 
0.1%
77 1
 
0.1%
Other values (2) 2
 
0.2%
(Missing) 776
94.9%
ValueCountFrequency (%)
1 18
2.2%
2 11
1.3%
3 2
 
0.2%
4 2
 
0.2%
5 1
 
0.1%
6 2
 
0.2%
7 1
 
0.1%
12 1
 
0.1%
21 1
 
0.1%
36 1
 
0.1%
ValueCountFrequency (%)
153 1
0.1%
77 1
0.1%
36 1
0.1%
21 1
0.1%
12 1
0.1%
7 1
0.1%
6 2
0.2%
5 1
0.1%
4 2
0.2%
3 2
0.2%

Unnamed: 45
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)26.8%
Missing777
Missing (%)95.0%
Infinite0
Infinite (%)0.0%
Mean7.8780488
Minimum1
Maximum130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:22.030145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile34
Maximum130
Range129
Interquartile range (IQR)2

Descriptive statistics

Standard deviation22.350833
Coefficient of variation (CV)2.8371027
Kurtosis23.71102
Mean7.8780488
Median Absolute Deviation (MAD)0
Skewness4.6823738
Sum323
Variance499.55976
MonotonicityNot monotonic
2023-12-13T04:50:22.151825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 21
 
2.6%
2 8
 
1.0%
3 4
 
0.5%
8 1
 
0.1%
16 1
 
0.1%
34 1
 
0.1%
9 1
 
0.1%
11 1
 
0.1%
62 1
 
0.1%
4 1
 
0.1%
(Missing) 777
95.0%
ValueCountFrequency (%)
1 21
2.6%
2 8
 
1.0%
3 4
 
0.5%
4 1
 
0.1%
8 1
 
0.1%
9 1
 
0.1%
11 1
 
0.1%
16 1
 
0.1%
34 1
 
0.1%
62 1
 
0.1%
ValueCountFrequency (%)
130 1
 
0.1%
62 1
 
0.1%
34 1
 
0.1%
16 1
 
0.1%
11 1
 
0.1%
9 1
 
0.1%
8 1
 
0.1%
4 1
 
0.1%
3 4
0.5%
2 8
1.0%

Unnamed: 46
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)31.2%
Missing786
Missing (%)96.1%
Infinite0
Infinite (%)0.0%
Mean6.4375
Minimum1
Maximum85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:22.247296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32.25
95-th percentile28.5
Maximum85
Range84
Interquartile range (IQR)1.25

Descriptive statistics

Standard deviation16.519661
Coefficient of variation (CV)2.5661609
Kurtosis17.890379
Mean6.4375
Median Absolute Deviation (MAD)0
Skewness4.1171827
Sum206
Variance272.89919
MonotonicityNot monotonic
2023-12-13T04:50:22.361574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 20
 
2.4%
2 4
 
0.5%
9 1
 
0.1%
15 1
 
0.1%
12 1
 
0.1%
5 1
 
0.1%
45 1
 
0.1%
3 1
 
0.1%
4 1
 
0.1%
85 1
 
0.1%
(Missing) 786
96.1%
ValueCountFrequency (%)
1 20
2.4%
2 4
 
0.5%
3 1
 
0.1%
4 1
 
0.1%
5 1
 
0.1%
9 1
 
0.1%
12 1
 
0.1%
15 1
 
0.1%
45 1
 
0.1%
85 1
 
0.1%
ValueCountFrequency (%)
85 1
 
0.1%
45 1
 
0.1%
15 1
 
0.1%
12 1
 
0.1%
9 1
 
0.1%
5 1
 
0.1%
4 1
 
0.1%
3 1
 
0.1%
2 4
 
0.5%
1 20
2.4%

Unnamed: 47
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)32.0%
Missing793
Missing (%)96.9%
Infinite0
Infinite (%)0.0%
Mean4.8
Minimum1
Maximum44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:22.467224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile20
Maximum44
Range43
Interquartile range (IQR)1

Descriptive statistics

Standard deviation9.4780448
Coefficient of variation (CV)1.9745927
Kurtosis12.870656
Mean4.8
Median Absolute Deviation (MAD)0
Skewness3.4550625
Sum120
Variance89.833333
MonotonicityNot monotonic
2023-12-13T04:50:22.562385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 14
 
1.7%
2 5
 
0.6%
10 1
 
0.1%
5 1
 
0.1%
12 1
 
0.1%
3 1
 
0.1%
22 1
 
0.1%
44 1
 
0.1%
(Missing) 793
96.9%
ValueCountFrequency (%)
1 14
1.7%
2 5
 
0.6%
3 1
 
0.1%
5 1
 
0.1%
10 1
 
0.1%
12 1
 
0.1%
22 1
 
0.1%
44 1
 
0.1%
ValueCountFrequency (%)
44 1
 
0.1%
22 1
 
0.1%
12 1
 
0.1%
10 1
 
0.1%
5 1
 
0.1%
3 1
 
0.1%
2 5
 
0.6%
1 14
1.7%

Unnamed: 48
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
813 
2
 
2
11
 
1
1
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.9828851
Min length1

Unique

Unique3 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 813
99.4%
2 2
 
0.2%
11 1
 
0.1%
1 1
 
0.1%
5 1
 
0.1%

Length

2023-12-13T04:50:22.696377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:22.815289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 813
99.4%
2 2
 
0.2%
11 1
 
0.1%
1 1
 
0.1%
5 1
 
0.1%

Unnamed: 49
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
811 
1
 
3
12
 
1
2
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.9755501
Min length1

Unique

Unique4 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 811
99.1%
1 3
 
0.4%
12 1
 
0.1%
2 1
 
0.1%
6 1
 
0.1%
9 1
 
0.1%

Length

2023-12-13T04:50:22.962527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:23.110555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 811
99.1%
1 3
 
0.4%
12 1
 
0.1%
2 1
 
0.1%
6 1
 
0.1%
9 1
 
0.1%

Unnamed: 50
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing742
Missing (%)90.7%
Memory size6.5 KiB

Unnamed: 51
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
810 
1
 
5
2015
 
1
2
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.9743276
Min length1

Unique

Unique3 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 810
99.0%
1 5
 
0.6%
2015 1
 
0.1%
2 1
 
0.1%
3 1
 
0.1%

Length

2023-12-13T04:50:23.271769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:23.527976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 810
99.0%
1 5
 
0.6%
2015 1
 
0.1%
2 1
 
0.1%
3 1
 
0.1%

Unnamed: 52
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
813 
1
 
2
3
 
1
6
 
1
8
 
1

Length

Max length4
Median length4
Mean length3.9816626
Min length1

Unique

Unique3 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 813
99.4%
1 2
 
0.2%
3 1
 
0.1%
6 1
 
0.1%
8 1
 
0.1%

Length

2023-12-13T04:50:23.698604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:23.854324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 813
99.4%
1 2
 
0.2%
3 1
 
0.1%
6 1
 
0.1%
8 1
 
0.1%

Unnamed: 53
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)50.0%
Missing804
Missing (%)98.3%
Infinite0
Infinite (%)0.0%
Mean5.9285714
Minimum1
Maximum34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:23.998394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile25.55
Maximum34
Range33
Interquartile range (IQR)3

Descriptive statistics

Standard deviation9.6433659
Coefficient of variation (CV)1.6265918
Kurtosis5.7346185
Mean5.9285714
Median Absolute Deviation (MAD)1
Skewness2.4684101
Sum83
Variance92.994505
MonotonicityNot monotonic
2023-12-13T04:50:24.134241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 6
 
0.7%
4 2
 
0.2%
2 2
 
0.2%
7 1
 
0.1%
3 1
 
0.1%
21 1
 
0.1%
34 1
 
0.1%
(Missing) 804
98.3%
ValueCountFrequency (%)
1 6
0.7%
2 2
 
0.2%
3 1
 
0.1%
4 2
 
0.2%
7 1
 
0.1%
21 1
 
0.1%
34 1
 
0.1%
ValueCountFrequency (%)
34 1
 
0.1%
21 1
 
0.1%
7 1
 
0.1%
4 2
 
0.2%
3 1
 
0.1%
2 2
 
0.2%
1 6
0.7%

Unnamed: 54
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)36.0%
Missing793
Missing (%)96.9%
Infinite0
Infinite (%)0.0%
Mean7.52
Minimum1
Maximum81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:24.287663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile48
Maximum81
Range80
Interquartile range (IQR)2

Descriptive statistics

Standard deviation18.995877
Coefficient of variation (CV)2.5260474
Kurtosis11.04606
Mean7.52
Median Absolute Deviation (MAD)0
Skewness3.3891365
Sum188
Variance360.84333
MonotonicityNot monotonic
2023-12-13T04:50:24.447187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 17
 
2.1%
5 1
 
0.1%
7 1
 
0.1%
12 1
 
0.1%
4 1
 
0.1%
3 1
 
0.1%
2 1
 
0.1%
57 1
 
0.1%
81 1
 
0.1%
(Missing) 793
96.9%
ValueCountFrequency (%)
1 17
2.1%
2 1
 
0.1%
3 1
 
0.1%
4 1
 
0.1%
5 1
 
0.1%
7 1
 
0.1%
12 1
 
0.1%
57 1
 
0.1%
81 1
 
0.1%
ValueCountFrequency (%)
81 1
 
0.1%
57 1
 
0.1%
12 1
 
0.1%
7 1
 
0.1%
5 1
 
0.1%
4 1
 
0.1%
3 1
 
0.1%
2 1
 
0.1%
1 17
2.1%

Unnamed: 55
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)29.4%
Missing784
Missing (%)95.8%
Infinite0
Infinite (%)0.0%
Mean8.5294118
Minimum1
Maximum122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:25.041525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33.75
95-th percentile40.1
Maximum122
Range121
Interquartile range (IQR)2.75

Descriptive statistics

Standard deviation24.547092
Coefficient of variation (CV)2.8779349
Kurtosis16.391723
Mean8.5294118
Median Absolute Deviation (MAD)0
Skewness4.0589309
Sum290
Variance602.55971
MonotonicityNot monotonic
2023-12-13T04:50:25.227253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 19
 
2.3%
2 5
 
0.6%
4 3
 
0.4%
6 1
 
0.1%
10 1
 
0.1%
17 1
 
0.1%
8 1
 
0.1%
83 1
 
0.1%
3 1
 
0.1%
122 1
 
0.1%
(Missing) 784
95.8%
ValueCountFrequency (%)
1 19
2.3%
2 5
 
0.6%
3 1
 
0.1%
4 3
 
0.4%
6 1
 
0.1%
8 1
 
0.1%
10 1
 
0.1%
17 1
 
0.1%
83 1
 
0.1%
122 1
 
0.1%
ValueCountFrequency (%)
122 1
 
0.1%
83 1
 
0.1%
17 1
 
0.1%
10 1
 
0.1%
8 1
 
0.1%
6 1
 
0.1%
4 3
 
0.4%
3 1
 
0.1%
2 5
 
0.6%
1 19
2.3%

Unnamed: 56
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)29.4%
Missing784
Missing (%)95.8%
Infinite0
Infinite (%)0.0%
Mean10
Minimum1
Maximum144
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:25.368805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile49.3
Maximum144
Range143
Interquartile range (IQR)2

Descriptive statistics

Standard deviation28.162946
Coefficient of variation (CV)2.8162946
Kurtosis17.384003
Mean10
Median Absolute Deviation (MAD)1
Skewness4.1130743
Sum340
Variance793.15152
MonotonicityNot monotonic
2023-12-13T04:50:25.526346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 14
 
1.7%
2 8
 
1.0%
3 4
 
0.5%
7 2
 
0.2%
14 1
 
0.1%
29 1
 
0.1%
6 1
 
0.1%
4 1
 
0.1%
87 1
 
0.1%
144 1
 
0.1%
(Missing) 784
95.8%
ValueCountFrequency (%)
1 14
1.7%
2 8
1.0%
3 4
 
0.5%
4 1
 
0.1%
6 1
 
0.1%
7 2
 
0.2%
14 1
 
0.1%
29 1
 
0.1%
87 1
 
0.1%
144 1
 
0.1%
ValueCountFrequency (%)
144 1
 
0.1%
87 1
 
0.1%
29 1
 
0.1%
14 1
 
0.1%
7 2
 
0.2%
6 1
 
0.1%
4 1
 
0.1%
3 4
 
0.5%
2 8
1.0%
1 14
1.7%

Unnamed: 57
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)26.8%
Missing777
Missing (%)95.0%
Infinite0
Infinite (%)0.0%
Mean7.7560976
Minimum1
Maximum131
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:25.730609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile27
Maximum131
Range130
Interquartile range (IQR)2

Descriptive statistics

Standard deviation23.07464
Coefficient of variation (CV)2.9750322
Kurtosis22.39405
Mean7.7560976
Median Absolute Deviation (MAD)0
Skewness4.6235628
Sum318
Variance532.43902
MonotonicityNot monotonic
2023-12-13T04:50:25.908539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 23
 
2.8%
3 5
 
0.6%
2 4
 
0.5%
4 2
 
0.2%
8 1
 
0.1%
12 1
 
0.1%
27 1
 
0.1%
7 1
 
0.1%
74 1
 
0.1%
5 1
 
0.1%
(Missing) 777
95.0%
ValueCountFrequency (%)
1 23
2.8%
2 4
 
0.5%
3 5
 
0.6%
4 2
 
0.2%
5 1
 
0.1%
7 1
 
0.1%
8 1
 
0.1%
12 1
 
0.1%
27 1
 
0.1%
74 1
 
0.1%
ValueCountFrequency (%)
131 1
 
0.1%
74 1
 
0.1%
27 1
 
0.1%
12 1
 
0.1%
8 1
 
0.1%
7 1
 
0.1%
5 1
 
0.1%
4 2
 
0.2%
3 5
0.6%
2 4
0.5%

Unnamed: 58
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)34.8%
Missing795
Missing (%)97.2%
Infinite0
Infinite (%)0.0%
Mean7.3043478
Minimum1
Maximum71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:26.038657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32.5
95-th percentile41.7
Maximum71
Range70
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation16.737098
Coefficient of variation (CV)2.2913884
Kurtosis10.630271
Mean7.3043478
Median Absolute Deviation (MAD)0
Skewness3.2709948
Sum168
Variance280.13043
MonotonicityNot monotonic
2023-12-13T04:50:26.180532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 14
 
1.7%
2 3
 
0.4%
9 1
 
0.1%
12 1
 
0.1%
8 1
 
0.1%
3 1
 
0.1%
45 1
 
0.1%
71 1
 
0.1%
(Missing) 795
97.2%
ValueCountFrequency (%)
1 14
1.7%
2 3
 
0.4%
3 1
 
0.1%
8 1
 
0.1%
9 1
 
0.1%
12 1
 
0.1%
45 1
 
0.1%
71 1
 
0.1%
ValueCountFrequency (%)
71 1
 
0.1%
45 1
 
0.1%
12 1
 
0.1%
9 1
 
0.1%
8 1
 
0.1%
3 1
 
0.1%
2 3
 
0.4%
1 14
1.7%

Unnamed: 59
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)50.0%
Missing806
Missing (%)98.5%
Infinite0
Infinite (%)0.0%
Mean5.9166667
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:26.344710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q35.5
95-th percentile23.6
Maximum28
Range27
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation8.9995791
Coefficient of variation (CV)1.5210556
Kurtosis2.7354955
Mean5.9166667
Median Absolute Deviation (MAD)0
Skewness1.9055028
Sum71
Variance80.992424
MonotonicityNot monotonic
2023-12-13T04:50:26.477590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 7
 
0.9%
10 1
 
0.1%
4 1
 
0.1%
2 1
 
0.1%
20 1
 
0.1%
28 1
 
0.1%
(Missing) 806
98.5%
ValueCountFrequency (%)
1 7
0.9%
2 1
 
0.1%
4 1
 
0.1%
10 1
 
0.1%
20 1
 
0.1%
28 1
 
0.1%
ValueCountFrequency (%)
28 1
 
0.1%
20 1
 
0.1%
10 1
 
0.1%
4 1
 
0.1%
2 1
 
0.1%
1 7
0.9%

Unnamed: 60
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
810 
1
 
4
11
 
1
3
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.9718826
Min length1

Unique

Unique4 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 810
99.0%
1 4
 
0.5%
11 1
 
0.1%
3 1
 
0.1%
2 1
 
0.1%
4 1
 
0.1%

Length

2023-12-13T04:50:26.645260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:26.815003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 810
99.0%
1 4
 
0.5%
11 1
 
0.1%
3 1
 
0.1%
2 1
 
0.1%
4 1
 
0.1%

Unnamed: 61
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
815 
2
 
2
12
 
1

Length

Max length4
Median length4
Mean length3.99022
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 815
99.6%
2 2
 
0.2%
12 1
 
0.1%

Length

2023-12-13T04:50:26.969843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:27.123266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 815
99.6%
2 2
 
0.2%
12 1
 
0.1%

Unnamed: 62
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing736
Missing (%)90.0%
Memory size6.5 KiB

Unnamed: 63
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
814 
1
 
3
2016
 
1

Length

Max length4
Median length4
Mean length3.9889976
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 814
99.5%
1 3
 
0.4%
2016 1
 
0.1%

Length

2023-12-13T04:50:27.266062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:27.396192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 814
99.5%
1 3
 
0.4%
2016 1
 
0.1%

Unnamed: 64
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
815 
1
 
2
2
 
1

Length

Max length4
Median length4
Mean length3.9889976
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 815
99.6%
1 2
 
0.2%
2 1
 
0.1%

Length

2023-12-13T04:50:27.539524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:27.678516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 815
99.6%
1 2
 
0.2%
2 1
 
0.1%

Unnamed: 65
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
814 
3
 
2
1
 
1
4
 
1

Length

Max length4
Median length4
Mean length3.9853301
Min length1

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 814
99.5%
3 2
 
0.2%
1 1
 
0.1%
4 1
 
0.1%

Length

2023-12-13T04:50:27.799441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:27.929484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 814
99.5%
3 2
 
0.2%
1 1
 
0.1%
4 1
 
0.1%

Unnamed: 66
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)30.0%
Missing798
Missing (%)97.6%
Infinite0
Infinite (%)0.0%
Mean3.75
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:28.079514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile17.5
Maximum27
Range26
Interquartile range (IQR)2

Descriptive statistics

Standard deviation6.5363357
Coefficient of variation (CV)1.7430228
Kurtosis9.2727365
Mean3.75
Median Absolute Deviation (MAD)0
Skewness3.065394
Sum75
Variance42.723684
MonotonicityNot monotonic
2023-12-13T04:50:28.261911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 12
 
1.5%
3 3
 
0.4%
4 2
 
0.2%
17 1
 
0.1%
2 1
 
0.1%
27 1
 
0.1%
(Missing) 798
97.6%
ValueCountFrequency (%)
1 12
1.5%
2 1
 
0.1%
3 3
 
0.4%
4 2
 
0.2%
17 1
 
0.1%
27 1
 
0.1%
ValueCountFrequency (%)
27 1
 
0.1%
17 1
 
0.1%
4 2
 
0.2%
3 3
 
0.4%
2 1
 
0.1%
1 12
1.5%

Unnamed: 67
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)28.6%
Missing790
Missing (%)96.6%
Infinite0
Infinite (%)0.0%
Mean5.9285714
Minimum1
Maximum71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:28.379967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32.25
95-th percentile33.35
Maximum71
Range70
Interquartile range (IQR)1.25

Descriptive statistics

Standard deviation15.422275
Coefficient of variation (CV)2.6013476
Kurtosis13.635572
Mean5.9285714
Median Absolute Deviation (MAD)0
Skewness3.7240764
Sum166
Variance237.84656
MonotonicityNot monotonic
2023-12-13T04:50:28.501760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 17
 
2.1%
2 4
 
0.5%
3 2
 
0.2%
5 1
 
0.1%
4 1
 
0.1%
8 1
 
0.1%
47 1
 
0.1%
71 1
 
0.1%
(Missing) 790
96.6%
ValueCountFrequency (%)
1 17
2.1%
2 4
 
0.5%
3 2
 
0.2%
4 1
 
0.1%
5 1
 
0.1%
8 1
 
0.1%
47 1
 
0.1%
71 1
 
0.1%
ValueCountFrequency (%)
71 1
 
0.1%
47 1
 
0.1%
8 1
 
0.1%
5 1
 
0.1%
4 1
 
0.1%
3 2
 
0.2%
2 4
 
0.5%
1 17
2.1%

Unnamed: 68
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)27.0%
Missing781
Missing (%)95.5%
Infinite0
Infinite (%)0.0%
Mean8.7297297
Minimum1
Maximum136
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:28.634017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile31
Maximum136
Range135
Interquartile range (IQR)2

Descriptive statistics

Standard deviation25.843169
Coefficient of variation (CV)2.960363
Kurtosis18.805883
Mean8.7297297
Median Absolute Deviation (MAD)0
Skewness4.3041715
Sum323
Variance667.86937
MonotonicityNot monotonic
2023-12-13T04:50:28.781891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 21
 
2.6%
2 6
 
0.7%
6 2
 
0.2%
3 2
 
0.2%
15 1
 
0.1%
17 1
 
0.1%
87 1
 
0.1%
10 1
 
0.1%
7 1
 
0.1%
136 1
 
0.1%
(Missing) 781
95.5%
ValueCountFrequency (%)
1 21
2.6%
2 6
 
0.7%
3 2
 
0.2%
6 2
 
0.2%
7 1
 
0.1%
10 1
 
0.1%
15 1
 
0.1%
17 1
 
0.1%
87 1
 
0.1%
136 1
 
0.1%
ValueCountFrequency (%)
136 1
 
0.1%
87 1
 
0.1%
17 1
 
0.1%
15 1
 
0.1%
10 1
 
0.1%
7 1
 
0.1%
6 2
 
0.2%
3 2
 
0.2%
2 6
 
0.7%
1 21
2.6%

Unnamed: 69
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)27.5%
Missing778
Missing (%)95.1%
Infinite0
Infinite (%)0.0%
Mean8.725
Minimum1
Maximum152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:28.920344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33.25
95-th percentile27
Maximum152
Range151
Interquartile range (IQR)2.25

Descriptive statistics

Standard deviation26.882448
Coefficient of variation (CV)3.0810829
Kurtosis22.734282
Mean8.725
Median Absolute Deviation (MAD)0
Skewness4.6670442
Sum349
Variance722.66603
MonotonicityNot monotonic
2023-12-13T04:50:29.040542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 22
 
2.7%
3 5
 
0.6%
4 3
 
0.4%
2 3
 
0.4%
7 1
 
0.1%
24 1
 
0.1%
16 1
 
0.1%
5 1
 
0.1%
84 1
 
0.1%
6 1
 
0.1%
(Missing) 778
95.1%
ValueCountFrequency (%)
1 22
2.7%
2 3
 
0.4%
3 5
 
0.6%
4 3
 
0.4%
5 1
 
0.1%
6 1
 
0.1%
7 1
 
0.1%
16 1
 
0.1%
24 1
 
0.1%
84 1
 
0.1%
ValueCountFrequency (%)
152 1
 
0.1%
84 1
 
0.1%
24 1
 
0.1%
16 1
 
0.1%
7 1
 
0.1%
6 1
 
0.1%
5 1
 
0.1%
4 3
0.4%
3 5
0.6%
2 3
0.4%

Unnamed: 70
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)34.5%
Missing789
Missing (%)96.5%
Infinite0
Infinite (%)0.0%
Mean8.0344828
Minimum1
Maximum98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:29.177167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile41
Maximum98
Range97
Interquartile range (IQR)2

Descriptive statistics

Standard deviation20.340815
Coefficient of variation (CV)2.5316895
Kurtosis15.087078
Mean8.0344828
Median Absolute Deviation (MAD)0
Skewness3.8271447
Sum233
Variance413.74877
MonotonicityNot monotonic
2023-12-13T04:50:29.330662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 16
 
2.0%
2 3
 
0.4%
3 3
 
0.4%
8 1
 
0.1%
12 1
 
0.1%
17 1
 
0.1%
6 1
 
0.1%
4 1
 
0.1%
57 1
 
0.1%
98 1
 
0.1%
(Missing) 789
96.5%
ValueCountFrequency (%)
1 16
2.0%
2 3
 
0.4%
3 3
 
0.4%
4 1
 
0.1%
6 1
 
0.1%
8 1
 
0.1%
12 1
 
0.1%
17 1
 
0.1%
57 1
 
0.1%
98 1
 
0.1%
ValueCountFrequency (%)
98 1
 
0.1%
57 1
 
0.1%
17 1
 
0.1%
12 1
 
0.1%
8 1
 
0.1%
6 1
 
0.1%
4 1
 
0.1%
3 3
 
0.4%
2 3
 
0.4%
1 16
2.0%

Unnamed: 71
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)34.8%
Missing795
Missing (%)97.2%
Infinite0
Infinite (%)0.0%
Mean7.2608696
Minimum1
Maximum71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:29.468641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32.5
95-th percentile42.5
Maximum71
Range70
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation16.815084
Coefficient of variation (CV)2.3158498
Kurtosis10.577182
Mean7.2608696
Median Absolute Deviation (MAD)0
Skewness3.2805001
Sum167
Variance282.74704
MonotonicityNot monotonic
2023-12-13T04:50:29.637388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 13
 
1.6%
2 4
 
0.5%
9 1
 
0.1%
6 1
 
0.1%
11 1
 
0.1%
46 1
 
0.1%
3 1
 
0.1%
71 1
 
0.1%
(Missing) 795
97.2%
ValueCountFrequency (%)
1 13
1.6%
2 4
 
0.5%
3 1
 
0.1%
6 1
 
0.1%
9 1
 
0.1%
11 1
 
0.1%
46 1
 
0.1%
71 1
 
0.1%
ValueCountFrequency (%)
71 1
 
0.1%
46 1
 
0.1%
11 1
 
0.1%
9 1
 
0.1%
6 1
 
0.1%
3 1
 
0.1%
2 4
 
0.5%
1 13
1.6%

Unnamed: 72
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)43.8%
Missing802
Missing (%)98.0%
Infinite0
Infinite (%)0.0%
Mean5.25
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:29.771689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q36.5
95-th percentile18.75
Maximum30
Range29
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation7.7931594
Coefficient of variation (CV)1.4844113
Kurtosis6.7669918
Mean5.25
Median Absolute Deviation (MAD)0
Skewness2.495524
Sum84
Variance60.733333
MonotonicityNot monotonic
2023-12-13T04:50:29.907257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 9
 
1.1%
3 2
 
0.2%
10 1
 
0.1%
6 1
 
0.1%
8 1
 
0.1%
15 1
 
0.1%
30 1
 
0.1%
(Missing) 802
98.0%
ValueCountFrequency (%)
1 9
1.1%
3 2
 
0.2%
6 1
 
0.1%
8 1
 
0.1%
10 1
 
0.1%
15 1
 
0.1%
30 1
 
0.1%
ValueCountFrequency (%)
30 1
 
0.1%
15 1
 
0.1%
10 1
 
0.1%
8 1
 
0.1%
6 1
 
0.1%
3 2
 
0.2%
1 9
1.1%

Unnamed: 73
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
809 
1
 
5
11
 
1
3
 
1
4
 
1

Length

Max length4
Median length4
Mean length3.9682152
Min length1

Unique

Unique4 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 809
98.9%
1 5
 
0.6%
11 1
 
0.1%
3 1
 
0.1%
4 1
 
0.1%
9 1
 
0.1%

Length

2023-12-13T04:50:30.063964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:30.208859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 809
98.9%
1 5
 
0.6%
11 1
 
0.1%
3 1
 
0.1%
4 1
 
0.1%
9 1
 
0.1%

Unnamed: 74
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
815 
2
 
2
12
 
1

Length

Max length4
Median length4
Mean length3.99022
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 815
99.6%
2 2
 
0.2%
12 1
 
0.1%

Length

2023-12-13T04:50:30.348337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:30.466487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 815
99.6%
2 2
 
0.2%
12 1
 
0.1%

Unnamed: 75
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing725
Missing (%)88.6%
Memory size6.5 KiB

Unnamed: 76
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
814 
1
 
3
2017
 
1

Length

Max length4
Median length4
Mean length3.9889976
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 814
99.5%
1 3
 
0.4%
2017 1
 
0.1%

Length

2023-12-13T04:50:30.599563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:30.732650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 814
99.5%
1 3
 
0.4%
2017 1
 
0.1%

Unnamed: 77
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
812 
1
 
2
4
 
1
2
 
1
6
 
1

Length

Max length4
Median length4
Mean length3.9779951
Min length1

Unique

Unique4 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 812
99.3%
1 2
 
0.2%
4 1
 
0.1%
2 1
 
0.1%
6 1
 
0.1%
8 1
 
0.1%

Length

2023-12-13T04:50:30.885340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:31.047652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 812
99.3%
1 2
 
0.2%
4 1
 
0.1%
2 1
 
0.1%
6 1
 
0.1%
8 1
 
0.1%

Unnamed: 78
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
806 
1
 
7
5
 
2
4
 
1
20
 
1

Length

Max length4
Median length4
Mean length3.9584352
Min length1

Unique

Unique3 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 806
98.5%
1 7
 
0.9%
5 2
 
0.2%
4 1
 
0.1%
20 1
 
0.1%
30 1
 
0.1%

Length

2023-12-13T04:50:31.185902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:31.337245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 806
98.5%
1 7
 
0.9%
5 2
 
0.2%
4 1
 
0.1%
20 1
 
0.1%
30 1
 
0.1%

Unnamed: 79
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)25.8%
Missing787
Missing (%)96.2%
Infinite0
Infinite (%)0.0%
Mean6.1290323
Minimum1
Maximum79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:31.462799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile32.5
Maximum79
Range78
Interquartile range (IQR)1

Descriptive statistics

Standard deviation16.574563
Coefficient of variation (CV)2.7042708
Kurtosis14.732683
Mean6.1290323
Median Absolute Deviation (MAD)0
Skewness3.8634678
Sum190
Variance274.71613
MonotonicityNot monotonic
2023-12-13T04:50:31.601765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 21
 
2.6%
2 3
 
0.4%
5 2
 
0.2%
6 1
 
0.1%
11 1
 
0.1%
54 1
 
0.1%
3 1
 
0.1%
79 1
 
0.1%
(Missing) 787
96.2%
ValueCountFrequency (%)
1 21
2.6%
2 3
 
0.4%
3 1
 
0.1%
5 2
 
0.2%
6 1
 
0.1%
11 1
 
0.1%
54 1
 
0.1%
79 1
 
0.1%
ValueCountFrequency (%)
79 1
 
0.1%
54 1
 
0.1%
11 1
 
0.1%
6 1
 
0.1%
5 2
 
0.2%
3 1
 
0.1%
2 3
 
0.4%
1 21
2.6%

Unnamed: 80
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)32.4%
Missing784
Missing (%)95.8%
Infinite0
Infinite (%)0.0%
Mean8.3235294
Minimum1
Maximum122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:31.709986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33.75
95-th percentile36.55
Maximum122
Range121
Interquartile range (IQR)2.75

Descriptive statistics

Standard deviation23.558722
Coefficient of variation (CV)2.8303765
Kurtosis18.242866
Mean8.3235294
Median Absolute Deviation (MAD)0
Skewness4.202765
Sum283
Variance555.01337
MonotonicityNot monotonic
2023-12-13T04:50:31.842277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 22
 
2.7%
4 2
 
0.2%
2 2
 
0.2%
7 1
 
0.1%
14 1
 
0.1%
18 1
 
0.1%
9 1
 
0.1%
71 1
 
0.1%
5 1
 
0.1%
3 1
 
0.1%
(Missing) 784
95.8%
ValueCountFrequency (%)
1 22
2.7%
2 2
 
0.2%
3 1
 
0.1%
4 2
 
0.2%
5 1
 
0.1%
7 1
 
0.1%
9 1
 
0.1%
14 1
 
0.1%
18 1
 
0.1%
71 1
 
0.1%
ValueCountFrequency (%)
122 1
0.1%
71 1
0.1%
18 1
0.1%
14 1
0.1%
9 1
0.1%
7 1
0.1%
5 1
0.1%
4 2
0.2%
3 1
0.1%
2 2
0.2%

Unnamed: 81
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)32.0%
Missing793
Missing (%)96.9%
Infinite0
Infinite (%)0.0%
Mean9
Minimum1
Maximum97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:31.957166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile54.6
Maximum97
Range96
Interquartile range (IQR)2

Descriptive statistics

Standard deviation22.362543
Coefficient of variation (CV)2.484727
Kurtosis11.538934
Mean9
Median Absolute Deviation (MAD)0
Skewness3.4370223
Sum225
Variance500.08333
MonotonicityNot monotonic
2023-12-13T04:50:32.058955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 13
 
1.6%
2 4
 
0.5%
8 2
 
0.2%
3 2
 
0.2%
13 1
 
0.1%
7 1
 
0.1%
65 1
 
0.1%
97 1
 
0.1%
(Missing) 793
96.9%
ValueCountFrequency (%)
1 13
1.6%
2 4
 
0.5%
3 2
 
0.2%
7 1
 
0.1%
8 2
 
0.2%
13 1
 
0.1%
65 1
 
0.1%
97 1
 
0.1%
ValueCountFrequency (%)
97 1
 
0.1%
65 1
 
0.1%
13 1
 
0.1%
8 2
 
0.2%
7 1
 
0.1%
3 2
 
0.2%
2 4
 
0.5%
1 13
1.6%

Unnamed: 82
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)36.0%
Missing793
Missing (%)96.9%
Infinite0
Infinite (%)0.0%
Mean6.88
Minimum1
Maximum67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:32.168303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q35
95-th percentile32.8
Maximum67
Range66
Interquartile range (IQR)4

Descriptive statistics

Standard deviation14.675149
Coefficient of variation (CV)2.1330159
Kurtosis12.63965
Mean6.88
Median Absolute Deviation (MAD)0
Skewness3.4718116
Sum172
Variance215.36
MonotonicityNot monotonic
2023-12-13T04:50:32.271472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 13
 
1.6%
2 3
 
0.4%
5 2
 
0.2%
3 2
 
0.2%
9 1
 
0.1%
8 1
 
0.1%
16 1
 
0.1%
37 1
 
0.1%
67 1
 
0.1%
(Missing) 793
96.9%
ValueCountFrequency (%)
1 13
1.6%
2 3
 
0.4%
3 2
 
0.2%
5 2
 
0.2%
8 1
 
0.1%
9 1
 
0.1%
16 1
 
0.1%
37 1
 
0.1%
67 1
 
0.1%
ValueCountFrequency (%)
67 1
 
0.1%
37 1
 
0.1%
16 1
 
0.1%
9 1
 
0.1%
8 1
 
0.1%
5 2
 
0.2%
3 2
 
0.2%
2 3
 
0.4%
1 13
1.6%

Unnamed: 83
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)35.3%
Missing801
Missing (%)97.9%
Infinite0
Infinite (%)0.0%
Mean4.4117647
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-13T04:50:32.369365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile16
Maximum28
Range27
Interquartile range (IQR)1

Descriptive statistics

Standard deviation7.1068525
Coefficient of variation (CV)1.6108866
Kurtosis7.6821563
Mean4.4117647
Median Absolute Deviation (MAD)0
Skewness2.6718373
Sum75
Variance50.507353
MonotonicityNot monotonic
2023-12-13T04:50:32.473300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 10
 
1.2%
2 3
 
0.4%
10 1
 
0.1%
8 1
 
0.1%
13 1
 
0.1%
28 1
 
0.1%
(Missing) 801
97.9%
ValueCountFrequency (%)
1 10
1.2%
2 3
 
0.4%
8 1
 
0.1%
10 1
 
0.1%
13 1
 
0.1%
28 1
 
0.1%
ValueCountFrequency (%)
28 1
 
0.1%
13 1
 
0.1%
10 1
 
0.1%
8 1
 
0.1%
2 3
 
0.4%
1 10
1.2%

Unnamed: 84
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
815 
2
 
2
11
 
1

Length

Max length4
Median length4
Mean length3.99022
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 815
99.6%
2 2
 
0.2%
11 1
 
0.1%

Length

2023-12-13T04:50:32.588854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:32.681921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 815
99.6%
2 2
 
0.2%
11 1
 
0.1%

Unnamed: 85
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
815 
2
 
2
12
 
1

Length

Max length4
Median length4
Mean length3.99022
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 815
99.6%
2 2
 
0.2%
12 1
 
0.1%

Length

2023-12-13T04:50:32.790643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:50:32.905884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 815
99.6%
2 2
 
0.2%
12 1
 
0.1%

Unnamed: 86
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing754
Missing (%)92.2%
Memory size6.5 KiB

Unnamed: 87
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing649
Missing (%)79.3%
Memory size6.5 KiB

Sample

<말라리아 발생현황 공공데이터 제공>Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6감염병감시과, 2018.5.24Unnamed: 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: 79Unnamed: 80Unnamed: 81Unnamed: 82Unnamed: 83Unnamed: 84Unnamed: 85Unnamed: 86Unnamed: 87
0<NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<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>NaNNaN
1<NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<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>NaNNaN
2<NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<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>NaNNaN
32013~2017년 말라리아 국내발생 연령별/직업별 현황NaN<NA><NA><NA><NA>NaN<NA><NA><NA>2013~2017년 말라리아 국내발생 월별/직업별 현황NaN<NA><NA><NA><NA>NaN<NA><NA>2013~2017년 말라리아 국내발생 지역별/직업별 현황NaN<NA><NA><NA><NA>NaN<NA><NA>2013~2017년 말라리아 국내발생 지역별/연령별/월별/직업별 현황 (인천, 강원지역)NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<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>NaNNaN
4<NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<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>NaNNaN
5<NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<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>NaNNaN
6<NA>연도<NA><NA><NA><NA>NaN<NA><NA><NA><NA>연도<NA><NA><NA><NA>NaN<NA><NA><NA>연도<NA><NA><NA><NA>NaN<NA><NA><NA>연도/월<NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<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>NaNNaN
7연령별/직업별20132014201520162017총합계<NA><NA><NA>월별/직업별20132014201520162017총합계<NA><NA>지역별/직업별20132014201520162017총합계<NA><NA><NA>2013<NA><NA><NA><NA><NA><NA><NA><NA><NA>2013 요약2014<NA><NA><NA><NA><NA><NA><NA><NA><NA>2014 요약2015<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2015 요약2016<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2016 요약2017<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017 요약총합계
80-4세NaN<NA>2<NA>13<NA><NA><NA>01NaN<NA>3115<NA><NA>서울3776647543295<NA><NA>지역/연령/직업0234567891011NaN2456789101112NaN13456789101112NaN123456789101112NaN1456789101112NaNNaN
9기타NaN<NA><NA><NA>11<NA><NA><NA>군인NaN<NA>21<NA>3<NA><NA>중구NaN<NA><NA>213<NA><NA>서울1<NA>1579743<NA>37<NA>131221161552176<NA>147101412124<NA><NA>64<NA>1134152412663<NA>751<NA>5514882<NA><NA>43295
<말라리아 발생현황 공공데이터 제공>Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6감염병감시과, 2018.5.24Unnamed: 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: 79Unnamed: 80Unnamed: 81Unnamed: 82Unnamed: 83Unnamed: 84Unnamed: 85Unnamed: 86Unnamed: 87
808<NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA>무직NaN<NA><NA><NA>11<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<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>NaNNaN
809<NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA>제주시21<NA>2<NA>5<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<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>NaNNaN
810<NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA>군인NaN<NA><NA>1<NA>1<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<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>NaNNaN
811<NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA>기타1<NA><NA>1<NA>2<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<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>NaNNaN
812<NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA>농업 및 어업숙련 종사자NaN1<NA><NA><NA>1<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<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>NaNNaN
813<NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA>학생1<NA><NA><NA><NA>1<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<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>NaNNaN
814<NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA>세종NaN<NA><NA>1<NA>1<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<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>NaNNaN
815<NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA>NaN<NA><NA>1<NA>1<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<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>NaNNaN
816<NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA>군인NaN<NA><NA>1<NA>1<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<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>NaNNaN
817<NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>NaN<NA><NA>총합계3855586286024362609<NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<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>NaNNaN

Duplicate rows

Most frequently occurring

<말라리아 발생현황 공공데이터 제공>Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 10Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 19Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 28Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33Unnamed: 34Unnamed: 35Unnamed: 36Unnamed: 37Unnamed: 38Unnamed: 40Unnamed: 41Unnamed: 42Unnamed: 43Unnamed: 44Unnamed: 45Unnamed: 46Unnamed: 47Unnamed: 48Unnamed: 49Unnamed: 51Unnamed: 52Unnamed: 53Unnamed: 54Unnamed: 55Unnamed: 56Unnamed: 57Unnamed: 58Unnamed: 59Unnamed: 60Unnamed: 61Unnamed: 63Unnamed: 64Unnamed: 65Unnamed: 66Unnamed: 67Unnamed: 68Unnamed: 69Unnamed: 70Unnamed: 71Unnamed: 72Unnamed: 73Unnamed: 74Unnamed: 76Unnamed: 77Unnamed: 78Unnamed: 79Unnamed: 80Unnamed: 81Unnamed: 82Unnamed: 83Unnamed: 84Unnamed: 85# duplicates
7<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>군인<NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19
23<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>기타<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>16
64<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>학생1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>12
69<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>학생<NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>12
70<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>학생<NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>12
20<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>기타1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>11
25<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>기타<NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>11
67<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>학생<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>10
71<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>학생<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>10
6<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>군인<NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>9