Overview

Dataset statistics

Number of variables34
Number of observations1494
Missing cells1494
Missing cells (%)2.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory433.4 KiB
Average record size in memory297.1 B

Variable types

Numeric24
Categorical1
Text8
Unsupported1

Dataset

Description품목(AGCODE, HSCODE)별 전년도, 당해년도 우리 농식품 수출 실적(물량(천톤), 금액(백만불)) 및 전년 대비 당해년도 수출 실적(물량, 금액) 증감률(%)
Author농림축산식품부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20210930000000001603

Alerts

Unnamed: 33 has 1494 (100.0%) missing valuesMissing
3.0 is highly skewed (γ1 = 26.03298795)Skewed
111010100 has unique valuesUnique
1006100000 has unique valuesUnique
Unnamed: 33 is an unsupported type, check if it needs cleaning or further analysisUnsupported
92.0 has 270 (18.1%) zerosZeros
163.3 has 170 (11.4%) zerosZeros
92.0.1 has 270 (18.1%) zerosZeros
163.3.1 has 170 (11.4%) zerosZeros
0 has 675 (45.2%) zerosZeros
0.1 has 581 (38.9%) zerosZeros
1.0 has 681 (45.6%) zerosZeros
1.7 has 606 (40.6%) zerosZeros
92.0.2 has 287 (19.2%) zerosZeros
163.3.2 has 189 (12.7%) zerosZeros
51.9 has 270 (18.1%) zerosZeros
117.8 has 184 (12.3%) zerosZeros
51.9.1 has 270 (18.1%) zerosZeros
117.8.1 has 184 (12.3%) zerosZeros
1.5 has 717 (48.0%) zerosZeros
4.5 has 624 (41.8%) zerosZeros
0.2 has 681 (45.6%) zerosZeros
0.3 has 597 (40.0%) zerosZeros
50.4 has 283 (18.9%) zerosZeros
113.3 has 199 (13.3%) zerosZeros
3.0 has 635 (42.5%) zerosZeros
4.0 has 622 (41.6%) zerosZeros

Reproduction

Analysis started2023-12-11 03:52:44.558639
Analysis finished2023-12-11 03:52:45.169600
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

111010100
Real number (ℝ)

UNIQUE 

Distinct1494
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9331202 × 108
Minimum1.11011 × 108
Maximum3.7118107 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:45.247205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.11011 × 108
5-th percentile1.1203165 × 108
Q11.2226273 × 108
median1.5812 × 108
Q32.4302001 × 108
95-th percentile3.33077 × 108
Maximum3.7118107 × 108
Range2.6017007 × 108
Interquartile range (IQR)1.2075729 × 108

Descriptive statistics

Standard deviation79733728
Coefficient of variation (CV)0.4124613
Kurtosis-0.90531495
Mean1.9331202 × 108
Median Absolute Deviation (MAD)41659500
Skewness0.76555176
Sum2.8880816 × 1011
Variance6.3574674 × 1015
MonotonicityStrictly increasing
2023-12-11T12:52:45.401095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
111011001 1
 
0.1%
222010015 1
 
0.1%
222021029 1
 
0.1%
222021027 1
 
0.1%
222021021 1
 
0.1%
222015603 1
 
0.1%
222015602 1
 
0.1%
222015601 1
 
0.1%
222010019 1
 
0.1%
222010017 1
 
0.1%
Other values (1484) 1484
99.3%
ValueCountFrequency (%)
111011001 1
0.1%
111011002 1
0.1%
111011003 1
0.1%
111011004 1
0.1%
111011005 1
0.1%
111012001 1
0.1%
111012004 1
0.1%
111012005 1
0.1%
111012006 1
0.1%
111013000 1
0.1%
ValueCountFrequency (%)
371181070 1
0.1%
371181061 1
0.1%
371181060 1
0.1%
371181050 1
0.1%
371181040 1
0.1%
371181030 1
0.1%
371181020 1
0.1%
371171010 1
0.1%
371151010 1
0.1%
371141010 1
0.1%

1006100000
Real number (ℝ)

UNIQUE 

Distinct1494
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.191427 × 109
Minimum1.01291 × 108
Maximum9.602001 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:45.534060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.01291 × 108
5-th percentile4.0362445 × 108
Q19.0444 × 108
median1.901109 × 109
Q33.3012275 × 109
95-th percentile4.7013506 × 109
Maximum9.602001 × 109
Range9.50071 × 109
Interquartile range (IQR)2.3967875 × 109

Descriptive statistics

Standard deviation1.6284372 × 109
Coefficient of variation (CV)0.74309443
Kurtosis2.2847373
Mean2.191427 × 109
Median Absolute Deviation (MAD)1.035157 × 109
Skewness1.2939809
Sum3.273992 × 1012
Variance2.6518078 × 1018
MonotonicityNot monotonic
2023-12-11T12:52:45.661577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1006201000 1
 
0.1%
207141020 1
 
0.1%
207452090 1
 
0.1%
207451000 1
 
0.1%
207410000 1
 
0.1%
1602329000 1
 
0.1%
1602321090 1
 
0.1%
1602321010 1
 
0.1%
207142090 1
 
0.1%
207141090 1
 
0.1%
Other values (1484) 1484
99.3%
ValueCountFrequency (%)
101291000 1
0.1%
101299000 1
0.1%
102212000 1
0.1%
105111000 1
0.1%
105119000 1
0.1%
106110000 1
0.1%
106122000 1
0.1%
106149000 1
0.1%
106191000 1
0.1%
106199000 1
0.1%
ValueCountFrequency (%)
9602001000 1
0.1%
9406100000 1
0.1%
9403830000 1
0.1%
9403820000 1
0.1%
9403609090 1
0.1%
9403609030 1
0.1%
9403609020 1
0.1%
9403601090 1
0.1%
9403509000 1
0.1%
9403501000 1
0.1%

식품
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
식품
937 
비식품
557 

Length

Max length3
Median length2
Mean length2.3728246
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품 937
62.7%
비식품 557
37.3%

Length

2023-12-11T12:52:45.818800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:52:45.921010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품 937
62.7%
비식품 557
37.3%

92.0
Real number (ℝ)

ZEROS 

Distinct760
Distinct (%)50.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2712.6119
Minimum0
Maximum292600.4
Zeros270
Zeros (%)18.1%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:46.021052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.3
median10
Q3165.325
95-th percentile8766.7
Maximum292600.4
Range292600.4
Interquartile range (IQR)165.025

Descriptive statistics

Standard deviation16142.496
Coefficient of variation (CV)5.950905
Kurtosis168.77283
Mean2712.6119
Median Absolute Deviation (MAD)10
Skewness11.6336
Sum4052642.2
Variance2.6058017 × 108
MonotonicityNot monotonic
2023-12-11T12:52:46.158861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 270
 
18.1%
0.1 59
 
3.9%
0.2 25
 
1.7%
0.3 21
 
1.4%
0.4 18
 
1.2%
0.9 16
 
1.1%
0.6 15
 
1.0%
1.0 14
 
0.9%
0.8 12
 
0.8%
1.9 11
 
0.7%
Other values (750) 1033
69.1%
ValueCountFrequency (%)
0.0 270
18.1%
0.1 59
 
3.9%
0.2 25
 
1.7%
0.3 21
 
1.4%
0.4 18
 
1.2%
0.5 10
 
0.7%
0.6 15
 
1.0%
0.7 11
 
0.7%
0.8 12
 
0.8%
0.9 16
 
1.1%
ValueCountFrequency (%)
292600.4 1
0.1%
285631.0 1
0.1%
209623.5 1
0.1%
160723.5 1
0.1%
141040.0 1
0.1%
137284.6 1
0.1%
128636.0 1
0.1%
108523.4 1
0.1%
103849.4 1
0.1%
100704.0 1
0.1%

163.3
Real number (ℝ)

ZEROS 

Distinct1035
Distinct (%)69.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4702.5056
Minimum0
Maximum717303.5
Zeros170
Zeros (%)11.4%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:46.294647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.9
median65
Q3742.75
95-th percentile22162.62
Maximum717303.5
Range717303.5
Interquartile range (IQR)738.85

Descriptive statistics

Standard deviation28058.536
Coefficient of variation (CV)5.9667204
Kurtosis348.33348
Mean4702.5056
Median Absolute Deviation (MAD)65
Skewness16.393243
Sum7025543.3
Variance7.8728142 × 108
MonotonicityNot monotonic
2023-12-11T12:52:46.434325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 170
 
11.4%
0.1 28
 
1.9%
0.4 14
 
0.9%
0.2 13
 
0.9%
1.2 9
 
0.6%
0.3 9
 
0.6%
0.5 9
 
0.6%
0.9 8
 
0.5%
0.6 8
 
0.5%
0.8 7
 
0.5%
Other values (1025) 1219
81.6%
ValueCountFrequency (%)
0.0 170
11.4%
0.1 28
 
1.9%
0.2 13
 
0.9%
0.3 9
 
0.6%
0.4 14
 
0.9%
0.5 9
 
0.6%
0.6 8
 
0.5%
0.7 5
 
0.3%
0.8 7
 
0.5%
0.9 8
 
0.5%
ValueCountFrequency (%)
717303.5 1
0.1%
466996.0 1
0.1%
342361.1 1
0.1%
269563.7 1
0.1%
146229.1 1
0.1%
133057.0 1
0.1%
130191.6 1
0.1%
125275.8 1
0.1%
123272.8 1
0.1%
119381.8 1
0.1%

92.0.1
Real number (ℝ)

ZEROS 

Distinct760
Distinct (%)50.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2712.6119
Minimum0
Maximum292600.4
Zeros270
Zeros (%)18.1%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:46.576297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.3
median10
Q3165.325
95-th percentile8766.7
Maximum292600.4
Range292600.4
Interquartile range (IQR)165.025

Descriptive statistics

Standard deviation16142.496
Coefficient of variation (CV)5.950905
Kurtosis168.77283
Mean2712.6119
Median Absolute Deviation (MAD)10
Skewness11.6336
Sum4052642.2
Variance2.6058017 × 108
MonotonicityNot monotonic
2023-12-11T12:52:47.015305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 270
 
18.1%
0.1 59
 
3.9%
0.2 25
 
1.7%
0.3 21
 
1.4%
0.4 18
 
1.2%
0.9 16
 
1.1%
0.6 15
 
1.0%
1.0 14
 
0.9%
0.8 12
 
0.8%
1.9 11
 
0.7%
Other values (750) 1033
69.1%
ValueCountFrequency (%)
0.0 270
18.1%
0.1 59
 
3.9%
0.2 25
 
1.7%
0.3 21
 
1.4%
0.4 18
 
1.2%
0.5 10
 
0.7%
0.6 15
 
1.0%
0.7 11
 
0.7%
0.8 12
 
0.8%
0.9 16
 
1.1%
ValueCountFrequency (%)
292600.4 1
0.1%
285631.0 1
0.1%
209623.5 1
0.1%
160723.5 1
0.1%
141040.0 1
0.1%
137284.6 1
0.1%
128636.0 1
0.1%
108523.4 1
0.1%
103849.4 1
0.1%
100704.0 1
0.1%

163.3.1
Real number (ℝ)

ZEROS 

Distinct1035
Distinct (%)69.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4702.5056
Minimum0
Maximum717303.5
Zeros170
Zeros (%)11.4%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:47.188866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.9
median65
Q3742.75
95-th percentile22162.62
Maximum717303.5
Range717303.5
Interquartile range (IQR)738.85

Descriptive statistics

Standard deviation28058.536
Coefficient of variation (CV)5.9667204
Kurtosis348.33348
Mean4702.5056
Median Absolute Deviation (MAD)65
Skewness16.393243
Sum7025543.3
Variance7.8728142 × 108
MonotonicityNot monotonic
2023-12-11T12:52:47.373591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 170
 
11.4%
0.1 28
 
1.9%
0.4 14
 
0.9%
0.2 13
 
0.9%
1.2 9
 
0.6%
0.3 9
 
0.6%
0.5 9
 
0.6%
0.9 8
 
0.5%
0.6 8
 
0.5%
0.8 7
 
0.5%
Other values (1025) 1219
81.6%
ValueCountFrequency (%)
0.0 170
11.4%
0.1 28
 
1.9%
0.2 13
 
0.9%
0.3 9
 
0.6%
0.4 14
 
0.9%
0.5 9
 
0.6%
0.6 8
 
0.5%
0.7 5
 
0.3%
0.8 7
 
0.5%
0.9 8
 
0.5%
ValueCountFrequency (%)
717303.5 1
0.1%
466996.0 1
0.1%
342361.1 1
0.1%
269563.7 1
0.1%
146229.1 1
0.1%
133057.0 1
0.1%
130191.6 1
0.1%
125275.8 1
0.1%
123272.8 1
0.1%
119381.8 1
0.1%

0
Real number (ℝ)

ZEROS 

Distinct434
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean224.96479
Minimum0
Maximum28771
Zeros675
Zeros (%)45.2%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:47.534901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.2
Q312.075
95-th percentile716.285
Maximum28771
Range28771
Interquartile range (IQR)12.075

Descriptive statistics

Standard deviation1374.6266
Coefficient of variation (CV)6.1104079
Kurtosis199.98862
Mean224.96479
Median Absolute Deviation (MAD)0.2
Skewness12.454927
Sum336097.4
Variance1889598.4
MonotonicityNot monotonic
2023-12-11T12:52:47.705471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 675
45.2%
0.1 63
 
4.2%
0.2 34
 
2.3%
0.3 31
 
2.1%
0.4 26
 
1.7%
0.5 16
 
1.1%
0.7 15
 
1.0%
1.3 14
 
0.9%
0.6 11
 
0.7%
1.1 9
 
0.6%
Other values (424) 600
40.2%
ValueCountFrequency (%)
0.0 675
45.2%
0.1 63
 
4.2%
0.2 34
 
2.3%
0.3 31
 
2.1%
0.4 26
 
1.7%
0.5 16
 
1.1%
0.6 11
 
0.7%
0.7 15
 
1.0%
0.8 8
 
0.5%
0.9 8
 
0.5%
ValueCountFrequency (%)
28771.0 1
0.1%
22862.2 1
0.1%
16000.6 1
0.1%
12173.2 1
0.1%
11566.4 1
0.1%
11052.1 1
0.1%
10622.3 1
0.1%
9340.8 1
0.1%
9030.0 1
0.1%
8627.4 1
0.1%

0.1
Real number (ℝ)

ZEROS 

Distinct614
Distinct (%)41.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean414.35341
Minimum0
Maximum51358.2
Zeros581
Zeros (%)38.9%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:47.873884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.6
Q360.575
95-th percentile1940.4
Maximum51358.2
Range51358.2
Interquartile range (IQR)60.575

Descriptive statistics

Standard deviation2287.0037
Coefficient of variation (CV)5.5194518
Kurtosis250.02507
Mean414.35341
Median Absolute Deviation (MAD)1.6
Skewness13.88207
Sum619044
Variance5230385.8
MonotonicityNot monotonic
2023-12-11T12:52:48.035774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 581
38.9%
0.1 27
 
1.8%
0.5 18
 
1.2%
0.3 15
 
1.0%
0.2 12
 
0.8%
0.4 12
 
0.8%
1.0 11
 
0.7%
0.9 10
 
0.7%
0.7 10
 
0.7%
1.2 9
 
0.6%
Other values (604) 789
52.8%
ValueCountFrequency (%)
0.0 581
38.9%
0.1 27
 
1.8%
0.2 12
 
0.8%
0.3 15
 
1.0%
0.4 12
 
0.8%
0.5 18
 
1.2%
0.6 7
 
0.5%
0.7 10
 
0.7%
0.8 6
 
0.4%
0.9 10
 
0.7%
ValueCountFrequency (%)
51358.2 1
0.1%
38895.9 1
0.1%
31999.8 1
0.1%
21458.5 1
0.1%
14123.3 1
0.1%
12360.7 1
0.1%
11867.7 1
0.1%
11695.3 1
0.1%
10845.3 1
0.1%
10652.3 1
0.1%

1.0
Real number (ℝ)

ZEROS 

Distinct432
Distinct (%)28.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean227.83353
Minimum0
Maximum36351.2
Zeros681
Zeros (%)45.6%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:48.203667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.1
Q310.075
95-th percentile757.25
Maximum36351.2
Range36351.2
Interquartile range (IQR)10.075

Descriptive statistics

Standard deviation1445.5002
Coefficient of variation (CV)6.3445453
Kurtosis302.41368
Mean227.83353
Median Absolute Deviation (MAD)0.1
Skewness14.832412
Sum340383.3
Variance2089470.8
MonotonicityNot monotonic
2023-12-11T12:52:48.407351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 681
45.6%
0.1 72
 
4.8%
0.2 49
 
3.3%
0.3 32
 
2.1%
0.6 17
 
1.1%
0.4 17
 
1.1%
0.7 17
 
1.1%
0.5 15
 
1.0%
2.0 11
 
0.7%
1.1 11
 
0.7%
Other values (422) 572
38.3%
ValueCountFrequency (%)
0.0 681
45.6%
0.1 72
 
4.8%
0.2 49
 
3.3%
0.3 32
 
2.1%
0.4 17
 
1.1%
0.5 15
 
1.0%
0.6 17
 
1.1%
0.7 17
 
1.1%
0.8 11
 
0.7%
0.9 6
 
0.4%
ValueCountFrequency (%)
36351.2 1
0.1%
19934.7 1
0.1%
14620.7 1
0.1%
13754.6 1
0.1%
11751.3 1
0.1%
10172.2 1
0.1%
8522.0 1
0.1%
7839.8 1
0.1%
7764.3 1
0.1%
7237.1 1
0.1%

1.7
Real number (ℝ)

ZEROS 

Distinct602
Distinct (%)40.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean410.21633
Minimum0
Maximum45786.6
Zeros606
Zeros (%)40.6%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:48.594663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.5
Q357.2
95-th percentile1859.145
Maximum45786.6
Range45786.6
Interquartile range (IQR)57.2

Descriptive statistics

Standard deviation2263.6962
Coefficient of variation (CV)5.5182987
Kurtosis231.37084
Mean410.21633
Median Absolute Deviation (MAD)1.5
Skewness13.448404
Sum612863.2
Variance5124320.7
MonotonicityNot monotonic
2023-12-11T12:52:48.768558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 606
40.6%
0.1 18
 
1.2%
0.2 16
 
1.1%
0.6 13
 
0.9%
0.3 12
 
0.8%
0.8 11
 
0.7%
0.5 10
 
0.7%
0.7 10
 
0.7%
1.0 9
 
0.6%
0.9 9
 
0.6%
Other values (592) 780
52.2%
ValueCountFrequency (%)
0.0 606
40.6%
0.1 18
 
1.2%
0.2 16
 
1.1%
0.3 12
 
0.8%
0.4 7
 
0.5%
0.5 10
 
0.7%
0.6 13
 
0.9%
0.7 10
 
0.7%
0.8 11
 
0.7%
0.9 9
 
0.6%
ValueCountFrequency (%)
45786.6 1
0.1%
44333.6 1
0.1%
30751.5 1
0.1%
19056.2 1
0.1%
15004.6 1
0.1%
14759.5 1
0.1%
14366.3 1
0.1%
12465.3 1
0.1%
11785.5 1
0.1%
9769.0 1
0.1%

92.0.2
Real number (ℝ)

ZEROS 

Distinct755
Distinct (%)50.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2487.6474
Minimum0
Maximum269738.2
Zeros287
Zeros (%)19.2%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:49.012296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.2
median8.4
Q3147.1
95-th percentile8058.08
Maximum269738.2
Range269738.2
Interquartile range (IQR)146.9

Descriptive statistics

Standard deviation14814.635
Coefficient of variation (CV)5.9552795
Kurtosis166.44036
Mean2487.6474
Median Absolute Deviation (MAD)8.4
Skewness11.566797
Sum3716545.2
Variance2.1947342 × 108
MonotonicityNot monotonic
2023-12-11T12:52:49.190419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 287
 
19.2%
0.1 59
 
3.9%
0.2 29
 
1.9%
0.3 21
 
1.4%
0.4 20
 
1.3%
0.6 16
 
1.1%
0.9 15
 
1.0%
1.0 14
 
0.9%
0.7 13
 
0.9%
1.1 12
 
0.8%
Other values (745) 1008
67.5%
ValueCountFrequency (%)
0.0 287
19.2%
0.1 59
 
3.9%
0.2 29
 
1.9%
0.3 21
 
1.4%
0.4 20
 
1.3%
0.5 6
 
0.4%
0.6 16
 
1.1%
0.7 13
 
0.9%
0.8 12
 
0.8%
0.9 15
 
1.0%
ValueCountFrequency (%)
269738.2 1
0.1%
256860.0 1
0.1%
193622.8 1
0.1%
153527.2 1
0.1%
128866.8 1
0.1%
125718.2 1
0.1%
118013.7 1
0.1%
97471.3 1
0.1%
94508.5 1
0.1%
92076.7 1
0.1%

163.3.2
Real number (ℝ)

ZEROS 

Distinct990
Distinct (%)66.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4288.1531
Minimum0
Maximum665945.4
Zeros189
Zeros (%)12.7%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:49.431290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.1
median57.75
Q3680.125
95-th percentile19332.655
Maximum665945.4
Range665945.4
Interquartile range (IQR)677.025

Descriptive statistics

Standard deviation25813.367
Coefficient of variation (CV)6.0196933
Kurtosis357.31124
Mean4288.1531
Median Absolute Deviation (MAD)57.75
Skewness16.607027
Sum6406500.7
Variance6.6632989 × 108
MonotonicityNot monotonic
2023-12-11T12:52:49.606616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 189
 
12.7%
0.1 28
 
1.9%
0.4 14
 
0.9%
0.2 13
 
0.9%
0.5 10
 
0.7%
0.3 10
 
0.7%
0.8 8
 
0.5%
0.9 8
 
0.5%
0.6 7
 
0.5%
1.1 7
 
0.5%
Other values (980) 1200
80.3%
ValueCountFrequency (%)
0.0 189
12.7%
0.1 28
 
1.9%
0.2 13
 
0.9%
0.3 10
 
0.7%
0.4 14
 
0.9%
0.5 10
 
0.7%
0.6 7
 
0.5%
0.7 5
 
0.3%
0.8 8
 
0.5%
0.9 8
 
0.5%
ValueCountFrequency (%)
665945.4 1
0.1%
428100.0 1
0.1%
310361.3 1
0.1%
248105.2 1
0.1%
135913.4 1
0.1%
121028.2 1
0.1%
120696.3 1
0.1%
114430.6 1
0.1%
111405.1 1
0.1%
107686.6 1
0.1%

51.9
Real number (ℝ)

ZEROS 

Distinct735
Distinct (%)49.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2633.6567
Minimum0
Maximum313656.3
Zeros270
Zeros (%)18.1%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:49.778855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.3
median8
Q3146.4
95-th percentile7958.39
Maximum313656.3
Range313656.3
Interquartile range (IQR)146.1

Descriptive statistics

Standard deviation16405.69
Coefficient of variation (CV)6.229244
Kurtosis205.22592
Mean2633.6567
Median Absolute Deviation (MAD)8
Skewness12.962638
Sum3934683.1
Variance2.6914667 × 108
MonotonicityNot monotonic
2023-12-11T12:52:49.982834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 270
 
18.1%
0.1 72
 
4.8%
0.2 30
 
2.0%
0.3 22
 
1.5%
0.9 18
 
1.2%
0.8 18
 
1.2%
1.0 16
 
1.1%
0.5 15
 
1.0%
0.6 14
 
0.9%
0.4 13
 
0.9%
Other values (725) 1006
67.3%
ValueCountFrequency (%)
0.0 270
18.1%
0.1 72
 
4.8%
0.2 30
 
2.0%
0.3 22
 
1.5%
0.4 13
 
0.9%
0.5 15
 
1.0%
0.6 14
 
0.9%
0.7 13
 
0.9%
0.8 18
 
1.2%
0.9 18
 
1.2%
ValueCountFrequency (%)
313656.3 1
0.1%
282951.7 1
0.1%
270846.9 1
0.1%
177322.1 1
0.1%
132479.3 1
0.1%
109335.5 1
0.1%
105416.2 1
0.1%
91043.1 1
0.1%
88421.1 1
0.1%
86863.8 1
0.1%

117.8
Real number (ℝ)

ZEROS 

Distinct1007
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5063.0456
Minimum0
Maximum816620.2
Zeros184
Zeros (%)12.3%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:50.142310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.725
median61.65
Q3733.375
95-th percentile22402.91
Maximum816620.2
Range816620.2
Interquartile range (IQR)730.65

Descriptive statistics

Standard deviation32231.82
Coefficient of variation (CV)6.3660931
Kurtosis371.88399
Mean5063.0456
Median Absolute Deviation (MAD)61.65
Skewness17.360065
Sum7564190.2
Variance1.0388902 × 109
MonotonicityNot monotonic
2023-12-11T12:52:50.315508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 184
 
12.3%
0.2 19
 
1.3%
0.1 17
 
1.1%
1.0 16
 
1.1%
0.5 15
 
1.0%
0.7 11
 
0.7%
0.4 11
 
0.7%
0.8 10
 
0.7%
0.6 9
 
0.6%
0.3 9
 
0.6%
Other values (997) 1193
79.9%
ValueCountFrequency (%)
0.0 184
12.3%
0.1 17
 
1.1%
0.2 19
 
1.3%
0.3 9
 
0.6%
0.4 11
 
0.7%
0.5 15
 
1.0%
0.6 9
 
0.6%
0.7 11
 
0.7%
0.8 10
 
0.7%
0.9 7
 
0.5%
ValueCountFrequency (%)
816620.2 1
0.1%
603574.0 1
0.1%
428877.9 1
0.1%
264078.0 1
0.1%
167322.4 1
0.1%
144511.5 1
0.1%
137697.8 1
0.1%
136154.8 1
0.1%
125707.7 1
0.1%
119076.3 1
0.1%

51.9.1
Real number (ℝ)

ZEROS 

Distinct735
Distinct (%)49.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2633.6567
Minimum0
Maximum313656.3
Zeros270
Zeros (%)18.1%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:50.500736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.3
median8
Q3146.4
95-th percentile7958.39
Maximum313656.3
Range313656.3
Interquartile range (IQR)146.1

Descriptive statistics

Standard deviation16405.69
Coefficient of variation (CV)6.229244
Kurtosis205.22592
Mean2633.6567
Median Absolute Deviation (MAD)8
Skewness12.962638
Sum3934683.1
Variance2.6914667 × 108
MonotonicityNot monotonic
2023-12-11T12:52:50.672703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 270
 
18.1%
0.1 72
 
4.8%
0.2 30
 
2.0%
0.3 22
 
1.5%
0.9 18
 
1.2%
0.8 18
 
1.2%
1.0 16
 
1.1%
0.5 15
 
1.0%
0.6 14
 
0.9%
0.4 13
 
0.9%
Other values (725) 1006
67.3%
ValueCountFrequency (%)
0.0 270
18.1%
0.1 72
 
4.8%
0.2 30
 
2.0%
0.3 22
 
1.5%
0.4 13
 
0.9%
0.5 15
 
1.0%
0.6 14
 
0.9%
0.7 13
 
0.9%
0.8 18
 
1.2%
0.9 18
 
1.2%
ValueCountFrequency (%)
313656.3 1
0.1%
282951.7 1
0.1%
270846.9 1
0.1%
177322.1 1
0.1%
132479.3 1
0.1%
109335.5 1
0.1%
105416.2 1
0.1%
91043.1 1
0.1%
88421.1 1
0.1%
86863.8 1
0.1%

117.8.1
Real number (ℝ)

ZEROS 

Distinct1007
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5063.0456
Minimum0
Maximum816620.2
Zeros184
Zeros (%)12.3%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:50.864628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.725
median61.65
Q3733.375
95-th percentile22402.91
Maximum816620.2
Range816620.2
Interquartile range (IQR)730.65

Descriptive statistics

Standard deviation32231.82
Coefficient of variation (CV)6.3660931
Kurtosis371.88399
Mean5063.0456
Median Absolute Deviation (MAD)61.65
Skewness17.360065
Sum7564190.2
Variance1.0388902 × 109
MonotonicityNot monotonic
2023-12-11T12:52:51.019151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 184
 
12.3%
0.2 19
 
1.3%
0.1 17
 
1.1%
1.0 16
 
1.1%
0.5 15
 
1.0%
0.7 11
 
0.7%
0.4 11
 
0.7%
0.8 10
 
0.7%
0.6 9
 
0.6%
0.3 9
 
0.6%
Other values (997) 1193
79.9%
ValueCountFrequency (%)
0.0 184
12.3%
0.1 17
 
1.1%
0.2 19
 
1.3%
0.3 9
 
0.6%
0.4 11
 
0.7%
0.5 15
 
1.0%
0.6 9
 
0.6%
0.7 11
 
0.7%
0.8 10
 
0.7%
0.9 7
 
0.5%
ValueCountFrequency (%)
816620.2 1
0.1%
603574.0 1
0.1%
428877.9 1
0.1%
264078.0 1
0.1%
167322.4 1
0.1%
144511.5 1
0.1%
137697.8 1
0.1%
136154.8 1
0.1%
125707.7 1
0.1%
119076.3 1
0.1%

1.5
Real number (ℝ)

ZEROS 

Distinct429
Distinct (%)28.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean224.24043
Minimum0
Maximum32113.6
Zeros717
Zeros (%)48.0%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:51.565162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.1
Q310
95-th percentile719.325
Maximum32113.6
Range32113.6
Interquartile range (IQR)10

Descriptive statistics

Standard deviation1452.9018
Coefficient of variation (CV)6.4792145
Kurtosis267.16721
Mean224.24043
Median Absolute Deviation (MAD)0.1
Skewness14.61006
Sum335015.2
Variance2110923.7
MonotonicityNot monotonic
2023-12-11T12:52:51.766954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 717
48.0%
0.1 44
 
2.9%
0.2 35
 
2.3%
0.3 29
 
1.9%
0.4 20
 
1.3%
0.5 19
 
1.3%
0.6 17
 
1.1%
1.0 16
 
1.1%
1.1 11
 
0.7%
0.7 9
 
0.6%
Other values (419) 577
38.6%
ValueCountFrequency (%)
0.0 717
48.0%
0.1 44
 
2.9%
0.2 35
 
2.3%
0.3 29
 
1.9%
0.4 20
 
1.3%
0.5 19
 
1.3%
0.6 17
 
1.1%
0.7 9
 
0.6%
0.8 6
 
0.4%
0.9 7
 
0.5%
ValueCountFrequency (%)
32113.6 1
0.1%
27515.8 1
0.1%
19203.9 1
0.1%
14217.5 1
0.1%
11787.6 1
0.1%
7120.9 1
0.1%
6701.9 1
0.1%
6659.3 1
0.1%
6331.2 1
0.1%
6010.7 1
0.1%

4.5
Real number (ℝ)

ZEROS 

Distinct623
Distinct (%)41.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean483.51975
Minimum0
Maximum63350.4
Zeros624
Zeros (%)41.8%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:51.947225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.5
Q364.625
95-th percentile2012.385
Maximum63350.4
Range63350.4
Interquartile range (IQR)64.625

Descriptive statistics

Standard deviation2878.1135
Coefficient of variation (CV)5.9524219
Kurtosis279.78446
Mean483.51975
Median Absolute Deviation (MAD)1.5
Skewness15.062467
Sum722378.5
Variance8283537.5
MonotonicityNot monotonic
2023-12-11T12:52:52.104410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 624
41.8%
0.1 18
 
1.2%
0.3 14
 
0.9%
0.2 14
 
0.9%
0.4 12
 
0.8%
0.7 9
 
0.6%
0.9 9
 
0.6%
0.6 8
 
0.5%
4.9 7
 
0.5%
0.5 7
 
0.5%
Other values (613) 772
51.7%
ValueCountFrequency (%)
0.0 624
41.8%
0.1 18
 
1.2%
0.2 14
 
0.9%
0.3 14
 
0.9%
0.4 12
 
0.8%
0.5 7
 
0.5%
0.6 8
 
0.5%
0.7 9
 
0.6%
0.8 6
 
0.4%
0.9 9
 
0.6%
ValueCountFrequency (%)
63350.4 1
0.1%
53909.7 1
0.1%
46793.0 1
0.1%
20602.9 1
0.1%
17205.4 1
0.1%
16401.3 1
0.1%
14065.5 1
0.1%
13040.0 1
0.1%
12970.3 1
0.1%
11500.2 1
0.1%

0.2
Real number (ℝ)

ZEROS 

Distinct442
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean226.11386
Minimum0
Maximum34054.4
Zeros681
Zeros (%)45.6%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:52.277766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.2
Q310.45
95-th percentile727.625
Maximum34054.4
Range34054.4
Interquartile range (IQR)10.45

Descriptive statistics

Standard deviation1482.8387
Coefficient of variation (CV)6.5579295
Kurtosis274.28215
Mean226.11386
Median Absolute Deviation (MAD)0.2
Skewness14.736641
Sum337814.1
Variance2198810.7
MonotonicityNot monotonic
2023-12-11T12:52:52.457850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 681
45.6%
0.1 54
 
3.6%
0.2 40
 
2.7%
0.5 26
 
1.7%
0.4 23
 
1.5%
0.3 20
 
1.3%
1.0 16
 
1.1%
0.7 11
 
0.7%
1.5 11
 
0.7%
1.3 10
 
0.7%
Other values (432) 602
40.3%
ValueCountFrequency (%)
0.0 681
45.6%
0.1 54
 
3.6%
0.2 40
 
2.7%
0.3 20
 
1.3%
0.4 23
 
1.5%
0.5 26
 
1.7%
0.6 9
 
0.6%
0.7 11
 
0.7%
0.8 9
 
0.6%
0.9 5
 
0.3%
ValueCountFrequency (%)
34054.4 1
0.1%
26085.6 1
0.1%
20472.3 1
0.1%
13207.7 1
0.1%
11159.9 1
0.1%
10764.1 1
0.1%
7135.6 1
0.1%
6646.8 1
0.1%
6474.7 1
0.1%
6244.9 1
0.1%

0.3
Real number (ℝ)

ZEROS 

Distinct626
Distinct (%)41.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean455.08394
Minimum0
Maximum57080.5
Zeros597
Zeros (%)40.0%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:52.607558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.9
Q363.5
95-th percentile1865.3
Maximum57080.5
Range57080.5
Interquartile range (IQR)63.5

Descriptive statistics

Standard deviation2577.1289
Coefficient of variation (CV)5.6629749
Kurtosis255.66172
Mean455.08394
Median Absolute Deviation (MAD)1.9
Skewness14.160079
Sum679895.4
Variance6641593.3
MonotonicityNot monotonic
2023-12-11T12:52:52.760655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 597
40.0%
0.1 29
 
1.9%
0.2 20
 
1.3%
0.4 11
 
0.7%
0.9 9
 
0.6%
1.3 9
 
0.6%
1.9 9
 
0.6%
1.0 8
 
0.5%
1.8 8
 
0.5%
1.1 8
 
0.5%
Other values (616) 786
52.6%
ValueCountFrequency (%)
0.0 597
40.0%
0.1 29
 
1.9%
0.2 20
 
1.3%
0.3 6
 
0.4%
0.4 11
 
0.7%
0.5 6
 
0.4%
0.6 6
 
0.4%
0.7 3
 
0.2%
0.8 5
 
0.3%
0.9 9
 
0.6%
ValueCountFrequency (%)
57080.5 1
0.1%
45493.7 1
0.1%
38629.3 1
0.1%
20207.8 1
0.1%
15562.1 1
0.1%
15429.9 1
0.1%
15139.8 1
0.1%
14793.5 1
0.1%
12436.5 1
0.1%
11232.2 1
0.1%

50.4
Real number (ℝ)

ZEROS 

Distinct728
Distinct (%)48.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2409.4171
Minimum0
Maximum281542.7
Zeros283
Zeros (%)18.9%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:52.930128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.2
median6.6
Q3138.725
95-th percentile7364.995
Maximum281542.7
Range281542.7
Interquartile range (IQR)138.525

Descriptive statistics

Standard deviation14994.916
Coefficient of variation (CV)6.2234622
Kurtosis201.20457
Mean2409.4171
Median Absolute Deviation (MAD)6.6
Skewness12.839472
Sum3599669.2
Variance2.2484752 × 108
MonotonicityNot monotonic
2023-12-11T12:52:53.078098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 283
 
18.9%
0.1 76
 
5.1%
0.2 30
 
2.0%
0.3 19
 
1.3%
0.6 17
 
1.1%
0.8 16
 
1.1%
0.5 16
 
1.1%
0.7 15
 
1.0%
1.0 15
 
1.0%
3.0 13
 
0.9%
Other values (718) 994
66.5%
ValueCountFrequency (%)
0.0 283
18.9%
0.1 76
 
5.1%
0.2 30
 
2.0%
0.3 19
 
1.3%
0.4 13
 
0.9%
0.5 16
 
1.1%
0.6 17
 
1.1%
0.7 15
 
1.0%
0.8 16
 
1.1%
0.9 13
 
0.9%
ValueCountFrequency (%)
281542.7 1
0.1%
263747.8 1
0.1%
243331.1 1
0.1%
163104.6 1
0.1%
120691.7 1
0.1%
103324.9 1
0.1%
98295.3 1
0.1%
85861.3 1
0.1%
82089.8 1
0.1%
80161.9 1
0.1%

113.3
Real number (ℝ)

ZEROS 

Distinct974
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4579.5251
Minimum0
Maximum753269.8
Zeros199
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:52:53.204953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.125
median52.7
Q3676.175
95-th percentile21017.455
Maximum753269.8
Range753269.8
Interquartile range (IQR)674.05

Descriptive statistics

Standard deviation29432.391
Coefficient of variation (CV)6.4269527
Kurtosis380.50446
Mean4579.5251
Median Absolute Deviation (MAD)52.7
Skewness17.552761
Sum6841810.5
Variance8.6626564 × 108
MonotonicityNot monotonic
2023-12-11T12:52:53.351393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 199
 
13.3%
0.2 22
 
1.5%
0.5 17
 
1.1%
0.1 16
 
1.1%
0.9 13
 
0.9%
0.4 12
 
0.8%
1.0 12
 
0.8%
0.7 12
 
0.8%
0.3 9
 
0.6%
1.8 7
 
0.5%
Other values (964) 1175
78.6%
ValueCountFrequency (%)
0.0 199
13.3%
0.1 16
 
1.1%
0.2 22
 
1.5%
0.3 9
 
0.6%
0.4 12
 
0.8%
0.5 17
 
1.1%
0.6 5
 
0.3%
0.7 12
 
0.8%
0.8 7
 
0.5%
0.9 13
 
0.9%
ValueCountFrequency (%)
753269.8 1
0.1%
549664.3 1
0.1%
382084.9 1
0.1%
243475.1 1
0.1%
150117.0 1
0.1%
131541.1 1
0.1%
125021.6 1
0.1%
123632.3 1
0.1%
114207.5 1
0.1%
111108.5 1
0.1%
Distinct990
Distinct (%)66.3%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2023-12-11T12:52:53.694876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length4.7028112
Min length3

Characters and Unicode

Total characters7026
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique818 ?
Unique (%)54.8%

Sample

1st row44.3
2nd row146.2
3rd row1.1
4th row72.1
5th row△72.6
ValueCountFrequency (%)
△100.0 150
 
10.0%
0.0 133
 
8.9%
4.0 5
 
0.3%
△1.7 5
 
0.3%
1.1 5
 
0.3%
△95.4 4
 
0.3%
△98.2 4
 
0.3%
△15.0 4
 
0.3%
△18.6 4
 
0.3%
△50.0 4
 
0.3%
Other values (980) 1176
78.7%
2023-12-11T12:52:54.192933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1494
21.3%
0 1050
14.9%
756
10.8%
1 700
10.0%
2 408
 
5.8%
3 399
 
5.7%
9 382
 
5.4%
4 380
 
5.4%
5 351
 
5.0%
6 349
 
5.0%
Other values (3) 757
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4703
66.9%
Other Punctuation 1567
 
22.3%
Other Symbol 756
 
10.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1050
22.3%
1 700
14.9%
2 408
 
8.7%
3 399
 
8.5%
9 382
 
8.1%
4 380
 
8.1%
5 351
 
7.5%
6 349
 
7.4%
8 347
 
7.4%
7 337
 
7.2%
Other Punctuation
ValueCountFrequency (%)
. 1494
95.3%
, 73
 
4.7%
Other Symbol
ValueCountFrequency (%)
756
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7026
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1494
21.3%
0 1050
14.9%
756
10.8%
1 700
10.0%
2 408
 
5.8%
3 399
 
5.7%
9 382
 
5.4%
4 380
 
5.4%
5 351
 
5.0%
6 349
 
5.0%
Other values (3) 757
10.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6270
89.2%
Geometric Shapes 756
 
10.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1494
23.8%
0 1050
16.7%
1 700
11.2%
2 408
 
6.5%
3 399
 
6.4%
9 382
 
6.1%
4 380
 
6.1%
5 351
 
5.6%
6 349
 
5.6%
8 347
 
5.5%
Other values (2) 410
 
6.5%
Geometric Shapes
ValueCountFrequency (%)
756
100.0%
Distinct968
Distinct (%)64.8%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2023-12-11T12:52:54.567554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.6519411
Min length3

Characters and Unicode

Total characters6950
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique769 ?
Unique (%)51.5%

Sample

1st row104.3
2nd row126.5
3rd row△10.9
4th row71.2
5th row△72.2
ValueCountFrequency (%)
△100.0 145
 
9.7%
0.0 135
 
9.0%
△4.6 6
 
0.4%
19.8 4
 
0.3%
△2.0 4
 
0.3%
△37.9 4
 
0.3%
△24.4 4
 
0.3%
△10.3 4
 
0.3%
2.3 4
 
0.3%
△54.5 4
 
0.3%
Other values (958) 1180
79.0%
2023-12-11T12:52:55.095610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1494
21.5%
0 991
14.3%
730
10.5%
1 699
10.1%
2 434
 
6.2%
4 422
 
6.1%
3 408
 
5.9%
6 363
 
5.2%
8 344
 
4.9%
7 340
 
4.9%
Other values (3) 725
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4668
67.2%
Other Punctuation 1552
 
22.3%
Other Symbol 730
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 991
21.2%
1 699
15.0%
2 434
9.3%
4 422
9.0%
3 408
8.7%
6 363
 
7.8%
8 344
 
7.4%
7 340
 
7.3%
9 335
 
7.2%
5 332
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 1494
96.3%
, 58
 
3.7%
Other Symbol
ValueCountFrequency (%)
730
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6950
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1494
21.5%
0 991
14.3%
730
10.5%
1 699
10.1%
2 434
 
6.2%
4 422
 
6.1%
3 408
 
5.9%
6 363
 
5.2%
8 344
 
4.9%
7 340
 
4.9%
Other values (3) 725
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6220
89.5%
Geometric Shapes 730
 
10.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1494
24.0%
0 991
15.9%
1 699
11.2%
2 434
 
7.0%
4 422
 
6.8%
3 408
 
6.6%
6 363
 
5.8%
8 344
 
5.5%
7 340
 
5.5%
9 335
 
5.4%
Other values (2) 390
 
6.3%
Geometric Shapes
ValueCountFrequency (%)
730
100.0%
Distinct990
Distinct (%)66.3%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2023-12-11T12:52:55.437981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length4.7028112
Min length3

Characters and Unicode

Total characters7026
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique818 ?
Unique (%)54.8%

Sample

1st row44.3
2nd row146.2
3rd row1.1
4th row72.1
5th row△72.6
ValueCountFrequency (%)
△100.0 150
 
10.0%
0.0 133
 
8.9%
4.0 5
 
0.3%
△1.7 5
 
0.3%
1.1 5
 
0.3%
△95.4 4
 
0.3%
△98.2 4
 
0.3%
△15.0 4
 
0.3%
△18.6 4
 
0.3%
△50.0 4
 
0.3%
Other values (980) 1176
78.7%
2023-12-11T12:52:55.963159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1494
21.3%
0 1050
14.9%
756
10.8%
1 700
10.0%
2 408
 
5.8%
3 399
 
5.7%
9 382
 
5.4%
4 380
 
5.4%
5 351
 
5.0%
6 349
 
5.0%
Other values (3) 757
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4703
66.9%
Other Punctuation 1567
 
22.3%
Other Symbol 756
 
10.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1050
22.3%
1 700
14.9%
2 408
 
8.7%
3 399
 
8.5%
9 382
 
8.1%
4 380
 
8.1%
5 351
 
7.5%
6 349
 
7.4%
8 347
 
7.4%
7 337
 
7.2%
Other Punctuation
ValueCountFrequency (%)
. 1494
95.3%
, 73
 
4.7%
Other Symbol
ValueCountFrequency (%)
756
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7026
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1494
21.3%
0 1050
14.9%
756
10.8%
1 700
10.0%
2 408
 
5.8%
3 399
 
5.7%
9 382
 
5.4%
4 380
 
5.4%
5 351
 
5.0%
6 349
 
5.0%
Other values (3) 757
10.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6270
89.2%
Geometric Shapes 756
 
10.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1494
23.8%
0 1050
16.7%
1 700
11.2%
2 408
 
6.5%
3 399
 
6.4%
9 382
 
6.1%
4 380
 
6.1%
5 351
 
5.6%
6 349
 
5.6%
8 347
 
5.5%
Other values (2) 410
 
6.5%
Geometric Shapes
ValueCountFrequency (%)
756
100.0%
Distinct968
Distinct (%)64.8%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2023-12-11T12:52:56.353109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.6519411
Min length3

Characters and Unicode

Total characters6950
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique769 ?
Unique (%)51.5%

Sample

1st row104.3
2nd row126.5
3rd row△10.9
4th row71.2
5th row△72.2
ValueCountFrequency (%)
△100.0 145
 
9.7%
0.0 135
 
9.0%
△4.6 6
 
0.4%
19.8 4
 
0.3%
△2.0 4
 
0.3%
△37.9 4
 
0.3%
△24.4 4
 
0.3%
△10.3 4
 
0.3%
2.3 4
 
0.3%
△54.5 4
 
0.3%
Other values (958) 1180
79.0%
2023-12-11T12:52:56.867228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1494
21.5%
0 991
14.3%
730
10.5%
1 699
10.1%
2 434
 
6.2%
4 422
 
6.1%
3 408
 
5.9%
6 363
 
5.2%
8 344
 
4.9%
7 340
 
4.9%
Other values (3) 725
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4668
67.2%
Other Punctuation 1552
 
22.3%
Other Symbol 730
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 991
21.2%
1 699
15.0%
2 434
9.3%
4 422
9.0%
3 408
8.7%
6 363
 
7.8%
8 344
 
7.4%
7 340
 
7.3%
9 335
 
7.2%
5 332
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 1494
96.3%
, 58
 
3.7%
Other Symbol
ValueCountFrequency (%)
730
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6950
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1494
21.5%
0 991
14.3%
730
10.5%
1 699
10.1%
2 434
 
6.2%
4 422
 
6.1%
3 408
 
5.9%
6 363
 
5.2%
8 344
 
4.9%
7 340
 
4.9%
Other values (3) 725
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6220
89.5%
Geometric Shapes 730
 
10.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1494
24.0%
0 991
15.9%
1 699
11.2%
2 434
 
7.0%
4 422
 
6.8%
3 408
 
6.6%
6 363
 
5.8%
8 344
 
5.5%
7 340
 
5.5%
9 335
 
5.4%
Other values (2) 390
 
6.3%
Geometric Shapes
ValueCountFrequency (%)
730
100.0%

0.0
Text

Distinct659
Distinct (%)44.1%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2023-12-11T12:52:57.217233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.2135207
Min length3

Characters and Unicode

Total characters6295
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique575 ?
Unique (%)38.5%

Sample

1st row30.3
2nd row△23.1
3rd row△0.2
4th row△26.4
5th row△85.5
ValueCountFrequency (%)
0.0 573
38.4%
△100.0 166
 
11.1%
△99.9 4
 
0.3%
△99.5 4
 
0.3%
△99.8 4
 
0.3%
68.2 4
 
0.3%
100.0 3
 
0.2%
△24.8 3
 
0.2%
△98.7 3
 
0.2%
13.6 3
 
0.2%
Other values (649) 727
48.7%
2023-12-11T12:52:57.704776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1883
29.9%
. 1494
23.7%
509
 
8.1%
1 486
 
7.7%
2 296
 
4.7%
4 250
 
4.0%
3 246
 
3.9%
5 244
 
3.9%
9 236
 
3.7%
7 219
 
3.5%
Other values (2) 432
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4292
68.2%
Other Punctuation 1494
 
23.7%
Other Symbol 509
 
8.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1883
43.9%
1 486
 
11.3%
2 296
 
6.9%
4 250
 
5.8%
3 246
 
5.7%
5 244
 
5.7%
9 236
 
5.5%
7 219
 
5.1%
8 218
 
5.1%
6 214
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 1494
100.0%
Other Symbol
ValueCountFrequency (%)
509
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6295
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1883
29.9%
. 1494
23.7%
509
 
8.1%
1 486
 
7.7%
2 296
 
4.7%
4 250
 
4.0%
3 246
 
3.9%
5 244
 
3.9%
9 236
 
3.7%
7 219
 
3.5%
Other values (2) 432
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5786
91.9%
Geometric Shapes 509
 
8.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1883
32.5%
. 1494
25.8%
1 486
 
8.4%
2 296
 
5.1%
4 250
 
4.3%
3 246
 
4.3%
5 244
 
4.2%
9 236
 
4.1%
7 219
 
3.8%
8 218
 
3.8%
Geometric Shapes
ValueCountFrequency (%)
509
100.0%

0.0.1
Text

Distinct683
Distinct (%)45.7%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2023-12-11T12:52:58.103553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.1900937
Min length3

Characters and Unicode

Total characters6260
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique614 ?
Unique (%)41.1%

Sample

1st row162.7
2nd row5.9
3rd row31.6
4th row△3.0
5th row△81.0
ValueCountFrequency (%)
0.0 569
38.1%
△100.0 162
 
10.8%
△39.5 4
 
0.3%
△99.8 4
 
0.3%
5.9 4
 
0.3%
△99.6 4
 
0.3%
4.1 3
 
0.2%
△65.1 3
 
0.2%
11.3 3
 
0.2%
△44.9 3
 
0.2%
Other values (673) 735
49.2%
2023-12-11T12:52:58.742136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1806
28.8%
. 1494
23.9%
1 500
 
8.0%
487
 
7.8%
2 297
 
4.7%
3 274
 
4.4%
6 255
 
4.1%
5 254
 
4.1%
9 241
 
3.8%
8 223
 
3.6%
Other values (2) 429
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4279
68.4%
Other Punctuation 1494
 
23.9%
Other Symbol 487
 
7.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1806
42.2%
1 500
 
11.7%
2 297
 
6.9%
3 274
 
6.4%
6 255
 
6.0%
5 254
 
5.9%
9 241
 
5.6%
8 223
 
5.2%
4 218
 
5.1%
7 211
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 1494
100.0%
Other Symbol
ValueCountFrequency (%)
487
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6260
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1806
28.8%
. 1494
23.9%
1 500
 
8.0%
487
 
7.8%
2 297
 
4.7%
3 274
 
4.4%
6 255
 
4.1%
5 254
 
4.1%
9 241
 
3.8%
8 223
 
3.6%
Other values (2) 429
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5773
92.2%
Geometric Shapes 487
 
7.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1806
31.3%
. 1494
25.9%
1 500
 
8.7%
2 297
 
5.1%
3 274
 
4.7%
6 255
 
4.4%
5 254
 
4.4%
9 241
 
4.2%
8 223
 
3.9%
4 218
 
3.8%
Geometric Shapes
ValueCountFrequency (%)
487
100.0%

0.0.2
Text

Distinct667
Distinct (%)44.6%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2023-12-11T12:52:59.244907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.1720214
Min length3

Characters and Unicode

Total characters6233
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique570 ?
Unique (%)38.2%

Sample

1st row36.6
2nd row△44.6
3rd row△57.4
4th row△85.2
5th row104.4
ValueCountFrequency (%)
0.0 576
38.6%
△100.0 138
 
9.2%
100.0 8
 
0.5%
△50.0 4
 
0.3%
△0.2 4
 
0.3%
△60.0 4
 
0.3%
△2.0 3
 
0.2%
△89.3 3
 
0.2%
△73.3 3
 
0.2%
△84.4 3
 
0.2%
Other values (657) 748
50.1%
2023-12-11T12:52:59.908877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1846
29.6%
. 1494
24.0%
536
 
8.6%
1 438
 
7.0%
2 281
 
4.5%
3 263
 
4.2%
5 252
 
4.0%
8 251
 
4.0%
6 249
 
4.0%
9 226
 
3.6%
Other values (2) 397
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4203
67.4%
Other Punctuation 1494
 
24.0%
Other Symbol 536
 
8.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1846
43.9%
1 438
 
10.4%
2 281
 
6.7%
3 263
 
6.3%
5 252
 
6.0%
8 251
 
6.0%
6 249
 
5.9%
9 226
 
5.4%
4 213
 
5.1%
7 184
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 1494
100.0%
Other Symbol
ValueCountFrequency (%)
536
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6233
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1846
29.6%
. 1494
24.0%
536
 
8.6%
1 438
 
7.0%
2 281
 
4.5%
3 263
 
4.2%
5 252
 
4.0%
8 251
 
4.0%
6 249
 
4.0%
9 226
 
3.6%
Other values (2) 397
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5697
91.4%
Geometric Shapes 536
 
8.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1846
32.4%
. 1494
26.2%
1 438
 
7.7%
2 281
 
4.9%
3 263
 
4.6%
5 252
 
4.4%
8 251
 
4.4%
6 249
 
4.4%
9 226
 
4.0%
4 213
 
3.7%
Geometric Shapes
ValueCountFrequency (%)
536
100.0%

0.0.3
Text

Distinct689
Distinct (%)46.1%
Missing0
Missing (%)0.0%
Memory size11.8 KiB
2023-12-11T12:53:00.327478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.1405622
Min length3

Characters and Unicode

Total characters6186
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique607 ?
Unique (%)40.6%

Sample

1st row87.4
2nd row△40.5
3rd row△59.2
4th row△83.7
5th row154.7
ValueCountFrequency (%)
0.0 572
38.3%
△100.0 138
 
9.2%
△75.0 5
 
0.3%
△14.1 4
 
0.3%
△84.3 4
 
0.3%
△13.8 3
 
0.2%
△47.3 3
 
0.2%
22.4 3
 
0.2%
34.6 3
 
0.2%
16.9 3
 
0.2%
Other values (679) 756
50.6%
2023-12-11T12:53:00.921720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1782
28.8%
. 1494
24.2%
533
 
8.6%
1 488
 
7.9%
2 279
 
4.5%
4 274
 
4.4%
5 247
 
4.0%
3 245
 
4.0%
8 225
 
3.6%
6 212
 
3.4%
Other values (2) 407
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4159
67.2%
Other Punctuation 1494
 
24.2%
Other Symbol 533
 
8.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1782
42.8%
1 488
 
11.7%
2 279
 
6.7%
4 274
 
6.6%
5 247
 
5.9%
3 245
 
5.9%
8 225
 
5.4%
6 212
 
5.1%
9 204
 
4.9%
7 203
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 1494
100.0%
Other Symbol
ValueCountFrequency (%)
533
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6186
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1782
28.8%
. 1494
24.2%
533
 
8.6%
1 488
 
7.9%
2 279
 
4.5%
4 274
 
4.4%
5 247
 
4.0%
3 245
 
4.0%
8 225
 
3.6%
6 212
 
3.4%
Other values (2) 407
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5653
91.4%
Geometric Shapes 533
 
8.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1782
31.5%
. 1494
26.4%
1 488
 
8.6%
2 279
 
4.9%
4 274
 
4.8%
5 247
 
4.4%
3 245
 
4.3%
8 225
 
4.0%
6 212
 
3.8%
9 204
 
3.6%
Geometric Shapes
ValueCountFrequency (%)
533
100.0%

3.0
Real number (ℝ)

SKEWED  ZEROS 

Distinct325
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.656091
Minimum0
Maximum15625
Zeros635
Zeros (%)42.5%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:53:01.110126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.1
Q310.575
95-th percentile50.835
Maximum15625
Range15625
Interquartile range (IQR)10.575

Descriptive statistics

Standard deviation501.17856
Coefficient of variation (CV)14.055903
Kurtosis738.53895
Mean35.656091
Median Absolute Deviation (MAD)2.1
Skewness26.032988
Sum53270.2
Variance251179.95
MonotonicityNot monotonic
2023-12-11T12:53:01.299070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 635
42.5%
0.2 14
 
0.9%
0.1 12
 
0.8%
9.3 11
 
0.7%
0.5 10
 
0.7%
6.2 10
 
0.7%
9.7 9
 
0.6%
11.8 9
 
0.6%
11.4 8
 
0.5%
2.1 8
 
0.5%
Other values (315) 768
51.4%
ValueCountFrequency (%)
0.0 635
42.5%
0.1 12
 
0.8%
0.2 14
 
0.9%
0.3 1
 
0.1%
0.4 7
 
0.5%
0.5 10
 
0.7%
0.6 3
 
0.2%
0.7 2
 
0.1%
0.8 2
 
0.1%
0.9 2
 
0.1%
ValueCountFrequency (%)
15625.0 1
0.1%
10112.4 1
0.1%
2808.3 1
0.1%
2673.2 1
0.1%
2671.5 1
0.1%
2568.9 1
0.1%
450.0 1
0.1%
376.5 1
0.1%
350.3 1
0.1%
326.2 1
0.1%

4.0
Real number (ℝ)

ZEROS 

Distinct340
Distinct (%)22.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.916466
Minimum0
Maximum4100.4
Zeros622
Zeros (%)41.6%
Negative0
Negative (%)0.0%
Memory size13.3 KiB
2023-12-11T12:53:01.502625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.9
Q311.3
95-th percentile47.305
Maximum4100.4
Range4100.4
Interquartile range (IQR)11.3

Descriptive statistics

Standard deviation159.28819
Coefficient of variation (CV)7.9978138
Kurtosis390.47778
Mean19.916466
Median Absolute Deviation (MAD)2.9
Skewness18.672576
Sum29755.2
Variance25372.726
MonotonicityNot monotonic
2023-12-11T12:53:01.689348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 622
41.6%
0.5 11
 
0.7%
10.3 10
 
0.7%
8.0 10
 
0.7%
10.2 9
 
0.6%
9.5 9
 
0.6%
0.2 8
 
0.5%
8.7 8
 
0.5%
7.5 8
 
0.5%
4.2 7
 
0.5%
Other values (330) 792
53.0%
ValueCountFrequency (%)
0.0 622
41.6%
0.1 5
 
0.3%
0.2 8
 
0.5%
0.3 4
 
0.3%
0.4 7
 
0.5%
0.5 11
 
0.7%
0.6 5
 
0.3%
0.7 6
 
0.4%
0.8 6
 
0.4%
0.9 6
 
0.4%
ValueCountFrequency (%)
4100.4 1
0.1%
2434.7 1
0.1%
2209.9 1
0.1%
2174.4 1
0.1%
2155.9 1
0.1%
439.3 1
0.1%
437.7 1
0.1%
274.7 1
0.1%
273.7 1
0.1%
241.2 1
0.1%

Unnamed: 33
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1494
Missing (%)100.0%
Memory size13.3 KiB

Sample

1110101001006100000식품92.0163.392.0.1163.3.100.11.01.792.0.2163.3.251.9117.851.9.1117.8.11.54.50.20.350.4113.3△43.6△27.9△43.6.1△27.9.10.00.0.10.0.20.0.33.04.0Unnamed: 33
01110110011006201000식품61.7157.661.7157.65.623.04.28.656.1134.689.0322.089.0322.07.360.55.332.381.7261.544.3104.344.3104.330.3162.736.687.48.923.1<NA>
11110110021006202000식품46.0152.946.0152.93.69.23.46.542.5143.8113.4346.3113.4346.32.89.75.016.3110.6336.6146.2126.5146.2126.5△23.15.9△44.6△40.52.52.9<NA>
21110110031006301000식품51238.223063.951238.223063.9103.5230.6126.9299.751134.722833.351811.820549.351811.820549.3103.3303.4242.4744.451708.520245.91.1△10.91.1△10.9△0.231.6△57.4△59.20.21.5<NA>
31110110041006302000식품81.5251.181.5251.13.812.74.615.377.7238.5140.3430.0140.3430.02.812.318.975.2137.6417.772.171.272.171.2△26.4△3.0△85.2△83.72.02.9<NA>
41110110051006400000식품143.3446.8143.3446.823.770.91.88.5119.6375.939.3124.239.3124.23.413.41.75.335.9110.8△72.6△72.2△72.6△72.2△85.5△81.0104.4154.79.612.1<NA>
51110120011102902000식품87.5113.387.5113.32.46.521.219.785.2106.7296.7326.1296.7326.136.944.211.717.3259.9282.0239.0187.9239.0187.91459.4576.8214.6155.214.215.7<NA>
61110120041104191000식품37.2227.337.2227.35.821.94.224.731.4205.414.093.214.093.20.72.52.319.413.290.7△62.4△59.0△62.4△59.0△87.7△88.5△68.5△86.95.42.8<NA>
71110120051103193000식품35.1100.135.1100.11.13.617.058.334.096.529.9305.329.9305.35.662.60.537.324.2242.7△15.0205.0△15.0205.0410.51653.21030.868.023.225.8<NA>
81110120061103202000식품0.00.10.00.10.00.00.00.00.00.10.00.20.00.20.00.10.00.00.00.152.047.652.047.60.00.00.00.052.848.6<NA>
91110130001104301000식품0.613.00.613.00.10.90.03.20.512.10.56.80.56.80.01.90.00.00.45.0△24.6△47.4△24.6△47.4△60.3115.40.00.09.737.4<NA>
1110101001006100000식품92.0163.392.0.1163.3.100.11.01.792.0.2163.3.251.9117.851.9.1117.8.11.54.50.20.350.4113.3△43.6△27.9△43.6.1△27.9.10.00.0.10.0.20.0.33.04.0Unnamed: 33
14843711410109403401000비식품243.0627.3243.0627.35.320.813.049.0237.7606.5111.1347.6111.1347.61.914.110.134.0109.2333.4△54.3△44.6△54.3△44.6△63.7△32.0△81.0△58.51.84.2<NA>
14853711510109403609020비식품40.6251.740.6251.75.722.22.28.134.9229.546.7153.746.7153.71.76.13.414.545.0147.615.1△38.915.1△38.9△70.0△72.6△48.8△58.03.84.1<NA>
14863711710109403501000비식품490.11656.5490.11656.540.2140.663.7216.1449.91515.9516.91590.0516.91590.016.273.123.679.0500.71516.95.5△4.05.5△4.0△59.6△48.0△31.3△7.43.24.8<NA>
14873711810209403601090비식품47.4527.047.4527.04.228.45.575.443.2498.6121.81220.4121.81220.44.9478.36.3482.2116.9742.1156.7131.6156.7131.617.01586.3△22.6△0.84.264.4<NA>
14883711810309403509000비식품567.31401.9567.31401.9174.8217.2126.5251.1392.51184.7457.31338.1457.31338.120.9118.9196.0759.4436.41219.2△19.4△4.6△19.4△4.6△88.0△45.3△89.3△84.34.89.8<NA>
14893711810409403409000비식품4029.010576.14029.010576.1645.22163.7795.82422.63383.88412.46950.122081.26950.122081.2522.81762.6565.11726.86427.320318.672.5108.872.5108.8△19.0△18.5△7.52.18.18.7<NA>
14903711810509403609090비식품7722.723741.37722.723741.3697.21835.8847.42597.77025.521905.55674.919361.35674.919361.3335.2878.1367.51080.15339.718483.2△26.5△18.4△26.5△18.4△51.9△52.2△8.8△18.76.34.8<NA>
14913711810609403309000비식품2118.410030.72118.410030.7201.6812.8217.3772.11916.89217.91197.34744.51197.34744.541.8184.357.1218.81155.64560.2△43.5△52.7△43.5△52.7△79.3△77.3△26.9△15.83.64.0<NA>
14923711810619403820000비식품0.11.30.11.30.11.20.00.00.00.00.00.50.00.50.00.00.00.00.00.5△77.0△63.7△77.0△63.7△100.0△100.00.00.00.00.0<NA>
14933711810709403830000비식품16.19.016.19.00.81.30.60.315.47.62.31.82.31.80.00.00.00.12.31.8△86.0△80.0△86.0△80.0△100.0△100.0△100.0△100.00.00.0<NA>