Overview

Dataset statistics

Number of variables24
Number of observations32
Missing cells32
Missing cells (%)4.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 KiB
Average record size in memory217.1 B

Variable types

Text3
Numeric20
Unsupported1

Dataset

Description해당 지역에 10개년(2021년 자료의 경우 2012~2021) 매 연간 우리 농식품 수출실적(물량(천톤), 금액(백만불)) 및 전년 대비 당해년도 수출실적(물량, 금액) 증감률(%) 등
Author농림축산식품부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20210930000000001606

Alerts

Unnamed: 23 has 32 (100.0%) missing valuesMissing
총계 has unique valuesUnique
1.9 has unique valuesUnique
Unnamed: 23 is an unsupported type, check if it needs cleaning or further analysisUnsupported
210.9 has 2 (6.2%) zerosZeros
662.3 has 2 (6.2%) zerosZeros
164.8 has 3 (9.4%) zerosZeros
527.6 has 3 (9.4%) zerosZeros
227.2 has 3 (9.4%) zerosZeros
715.6 has 2 (6.2%) zerosZeros
214.8 has 3 (9.4%) zerosZeros
701.5 has 2 (6.2%) zerosZeros
239.6 has 3 (9.4%) zerosZeros
776.8 has 2 (6.2%) zerosZeros
238.3 has 2 (6.2%) zerosZeros
804.3 has 1 (3.1%) zerosZeros
260.5 has 4 (12.5%) zerosZeros
592.1 has 1 (3.1%) zerosZeros
263.9 has 2 (6.2%) zerosZeros
504.0 has 1 (3.1%) zerosZeros
260.3 has 1 (3.1%) zerosZeros
642.8 has 1 (3.1%) zerosZeros
265.2 has 1 (3.1%) zerosZeros
676.3 has 1 (3.1%) zerosZeros

Reproduction

Analysis started2023-12-11 03:30:21.315033
Analysis finished2023-12-11 03:30:21.565160
Duration0.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

총계
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T12:30:21.703606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5.5
Mean length3.875
Min length2

Characters and Unicode

Total characters124
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row네팔
2nd row동티모르
3rd row레바논
4th row리비아
5th row몰디브
ValueCountFrequency (%)
네팔 1
 
3.1%
동티모르 1
 
3.1%
파키스탄 1
 
3.1%
투르크메니스탄 1
 
3.1%
터키 1
 
3.1%
타지키스탄 1
 
3.1%
키르기스스탄 1
 
3.1%
쿠웨이트 1
 
3.1%
카타르 1
 
3.1%
카자흐스탄 1
 
3.1%
Other values (22) 22
68.8%
2023-12-11T12:30:22.063035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 11
 
8.9%
탄 8
 
6.5%
아 7
 
5.6%
르 6
 
4.8%
키 5
 
4.0%
이 5
 
4.0%
리 4
 
3.2%
라 4
 
3.2%
인 3
 
2.4%
바 3
 
2.4%
Other values (54) 68
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 124
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 11
 
8.9%
탄 8
 
6.5%
아 7
 
5.6%
르 6
 
4.8%
키 5
 
4.0%
이 5
 
4.0%
리 4
 
3.2%
라 4
 
3.2%
인 3
 
2.4%
바 3
 
2.4%
Other values (54) 68
54.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 124
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 11
 
8.9%
탄 8
 
6.5%
아 7
 
5.6%
르 6
 
4.8%
키 5
 
4.0%
이 5
 
4.0%
리 4
 
3.2%
라 4
 
3.2%
인 3
 
2.4%
바 3
 
2.4%
Other values (54) 68
54.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 124
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 11
 
8.9%
탄 8
 
6.5%
아 7
 
5.6%
르 6
 
4.8%
키 5
 
4.0%
이 5
 
4.0%
리 4
 
3.2%
라 4
 
3.2%
인 3
 
2.4%
바 3
 
2.4%
Other values (54) 68
54.8%

210.9
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.590625
Minimum0
Maximum35.4
Zeros2
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:22.226324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.055
Q10.675
median1.95
Q36.85
95-th percentile29.28
Maximum35.4
Range35.4
Interquartile range (IQR)6.175

Descriptive statistics

Standard deviation9.672954
Coefficient of variation (CV)1.4676839
Kurtosis2.7683182
Mean6.590625
Median Absolute Deviation (MAD)1.8
Skewness1.9050361
Sum210.9
Variance93.566038
MonotonicityNot monotonic
2023-12-11T12:30:22.360848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.4 2
 
6.2%
0.7 2
 
6.2%
0.0 2
 
6.2%
6.8 1
 
3.1%
1.3 1
 
3.1%
4.8 1
 
3.1%
0.3 1
 
3.1%
1.6 1
 
3.1%
5.9 1
 
3.1%
13.0 1
 
3.1%
Other values (19) 19
59.4%
ValueCountFrequency (%)
0.0 2
6.2%
0.1 1
3.1%
0.2 1
3.1%
0.3 1
3.1%
0.4 2
6.2%
0.6 1
3.1%
0.7 2
6.2%
0.9 1
3.1%
1.1 1
3.1%
1.3 1
3.1%
ValueCountFrequency (%)
35.4 1
3.1%
31.7 1
3.1%
27.3 1
3.1%
21.7 1
3.1%
17.6 1
3.1%
13.0 1
3.1%
8.7 1
3.1%
7.0 1
3.1%
6.8 1
3.1%
6.4 1
3.1%

662.3
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.69375
Minimum0
Maximum224.5
Zeros2
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:22.496198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.165
Q11.475
median5.55
Q323.675
95-th percentile71.955
Maximum224.5
Range224.5
Interquartile range (IQR)22.2

Descriptive statistics

Standard deviation42.572708
Coefficient of variation (CV)2.0572737
Kurtosis17.623637
Mean20.69375
Median Absolute Deviation (MAD)4.65
Skewness3.9157315
Sum662.2
Variance1812.4354
MonotonicityNot monotonic
2023-12-11T12:30:22.615291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
6.7 2
 
6.2%
0.3 2
 
6.2%
1.5 2
 
6.2%
0.0 2
 
6.2%
0.8 2
 
6.2%
1.4 1
 
3.1%
6.2 1
 
3.1%
8.5 1
 
3.1%
13.7 1
 
3.1%
7.1 1
 
3.1%
Other values (17) 17
53.1%
ValueCountFrequency (%)
0.0 2
6.2%
0.3 2
6.2%
0.8 2
6.2%
1.0 1
3.1%
1.4 1
3.1%
1.5 2
6.2%
2.6 1
3.1%
2.7 1
3.1%
2.8 1
3.1%
3.0 1
3.1%
ValueCountFrequency (%)
224.5 1
3.1%
92.8 1
3.1%
54.9 1
3.1%
42.5 1
3.1%
41.3 1
3.1%
36.5 1
3.1%
35.0 1
3.1%
25.4 1
3.1%
23.1 1
3.1%
13.7 1
3.1%

164.8
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.14375
Minimum0
Maximum25.7
Zeros3
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:22.739546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.5
median1.95
Q36.975
95-th percentile18.565
Maximum25.7
Range25.7
Interquartile range (IQR)6.475

Descriptive statistics

Standard deviation6.761749
Coefficient of variation (CV)1.3145563
Kurtosis2.0266431
Mean5.14375
Median Absolute Deviation (MAD)1.75
Skewness1.6451368
Sum164.6
Variance45.72125
MonotonicityNot monotonic
2023-12-11T12:30:22.892901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.0 3
 
9.4%
0.5 3
 
9.4%
0.6 2
 
6.2%
6.9 2
 
6.2%
1.9 2
 
6.2%
0.4 1
 
3.1%
0.8 1
 
3.1%
9.7 1
 
3.1%
1.4 1
 
3.1%
3.9 1
 
3.1%
Other values (15) 15
46.9%
ValueCountFrequency (%)
0.0 3
9.4%
0.1 1
 
3.1%
0.3 1
 
3.1%
0.4 1
 
3.1%
0.5 3
9.4%
0.6 2
6.2%
0.8 1
 
3.1%
1.2 1
 
3.1%
1.4 1
 
3.1%
1.9 2
6.2%
ValueCountFrequency (%)
25.7 1
3.1%
20.6 1
3.1%
16.9 1
3.1%
15.7 1
3.1%
15.1 1
3.1%
9.7 1
3.1%
9.6 1
3.1%
7.2 1
3.1%
6.9 2
6.2%
5.6 1
3.1%

527.6
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.484375
Minimum0
Maximum191.7
Zeros3
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:23.060618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.3
median3.65
Q317.25
95-th percentile44.95
Maximum191.7
Range191.7
Interquartile range (IQR)15.95

Descriptive statistics

Standard deviation34.723109
Coefficient of variation (CV)2.1064255
Kurtosis22.140589
Mean16.484375
Median Absolute Deviation (MAD)3.65
Skewness4.4233739
Sum527.5
Variance1205.6943
MonotonicityNot monotonic
2023-12-11T12:30:23.227019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1.3 3
 
9.4%
0.0 3
 
9.4%
3.2 2
 
6.2%
1.8 2
 
6.2%
5.9 1
 
3.1%
8.1 1
 
3.1%
14.3 1
 
3.1%
0.8 1
 
3.1%
7.7 1
 
3.1%
3.4 1
 
3.1%
Other values (16) 16
50.0%
ValueCountFrequency (%)
0.0 3
9.4%
0.3 1
 
3.1%
0.6 1
 
3.1%
0.8 1
 
3.1%
1.3 3
9.4%
1.8 2
6.2%
2.7 1
 
3.1%
2.9 1
 
3.1%
3.2 2
6.2%
3.4 1
 
3.1%
ValueCountFrequency (%)
191.7 1
3.1%
47.7 1
3.1%
42.7 1
3.1%
33.9 1
3.1%
33.4 1
3.1%
30.9 1
3.1%
24.1 1
3.1%
23.4 1
3.1%
15.2 1
3.1%
14.3 1
3.1%

227.2
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.09375
Minimum0
Maximum46.3
Zeros3
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:23.389813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.7
median2
Q39.2
95-th percentile27.05
Maximum46.3
Range46.3
Interquartile range (IQR)8.5

Descriptive statistics

Standard deviation10.597502
Coefficient of variation (CV)1.493921
Kurtosis5.780484
Mean7.09375
Median Absolute Deviation (MAD)1.85
Skewness2.3029796
Sum227
Variance112.30706
MonotonicityNot monotonic
2023-12-11T12:30:23.541305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0.7 3
 
9.4%
0.0 3
 
9.4%
1.7 2
 
6.2%
0.9 2
 
6.2%
14.4 1
 
3.1%
1.0 1
 
3.1%
6.5 1
 
3.1%
2.1 1
 
3.1%
12.8 1
 
3.1%
22.1 1
 
3.1%
Other values (16) 16
50.0%
ValueCountFrequency (%)
0.0 3
9.4%
0.1 1
 
3.1%
0.2 1
 
3.1%
0.5 1
 
3.1%
0.7 3
9.4%
0.9 2
6.2%
1.0 1
 
3.1%
1.5 1
 
3.1%
1.7 2
6.2%
1.9 1
 
3.1%
ValueCountFrequency (%)
46.3 1
3.1%
33.1 1
3.1%
22.1 1
3.1%
19.4 1
3.1%
14.4 1
3.1%
13.5 1
3.1%
13.3 1
3.1%
12.8 1
3.1%
8.0 1
3.1%
7.4 1
3.1%

715.6
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.359375
Minimum0
Maximum304.5
Zeros2
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:23.666487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.055
Q11.45
median4.55
Q320.375
95-th percentile63.145
Maximum304.5
Range304.5
Interquartile range (IQR)18.925

Descriptive statistics

Standard deviation54.657685
Coefficient of variation (CV)2.4445086
Kurtosis24.542735
Mean22.359375
Median Absolute Deviation (MAD)4.45
Skewness4.7415822
Sum715.5
Variance2987.4625
MonotonicityNot monotonic
2023-12-11T12:30:23.813495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.1 2
 
6.2%
0.0 2
 
6.2%
4.5 2
 
6.2%
1.5 2
 
6.2%
1.6 1
 
3.1%
76.4 1
 
3.1%
12.1 1
 
3.1%
1.3 1
 
3.1%
18.5 1
 
3.1%
1.2 1
 
3.1%
Other values (18) 18
56.2%
ValueCountFrequency (%)
0.0 2
6.2%
0.1 2
6.2%
0.8 1
3.1%
1.0 1
3.1%
1.2 1
3.1%
1.3 1
3.1%
1.5 2
6.2%
1.6 1
3.1%
2.8 1
3.1%
3.9 1
3.1%
ValueCountFrequency (%)
304.5 1
3.1%
76.4 1
3.1%
52.3 1
3.1%
43.1 1
3.1%
41.5 1
3.1%
36.3 1
3.1%
26.8 1
3.1%
26.0 1
3.1%
18.5 1
3.1%
12.5 1
3.1%

214.8
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.709375
Minimum0
Maximum36.6
Zeros3
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:23.955736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.55
median1.55
Q310.425
95-th percentile27.27
Maximum36.6
Range36.6
Interquartile range (IQR)9.875

Descriptive statistics

Standard deviation9.7627785
Coefficient of variation (CV)1.4550951
Kurtosis2.543738
Mean6.709375
Median Absolute Deviation (MAD)1.5
Skewness1.7998203
Sum214.7
Variance95.311845
MonotonicityNot monotonic
2023-12-11T12:30:24.208596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0.4 3
 
9.4%
0.0 3
 
9.4%
1.2 2
 
6.2%
0.6 2
 
6.2%
1.5 1
 
3.1%
24.3 1
 
3.1%
3.6 1
 
3.1%
1.6 1
 
3.1%
1.1 1
 
3.1%
10.4 1
 
3.1%
Other values (16) 16
50.0%
ValueCountFrequency (%)
0.0 3
9.4%
0.1 1
 
3.1%
0.3 1
 
3.1%
0.4 3
9.4%
0.6 2
6.2%
0.8 1
 
3.1%
0.9 1
 
3.1%
1.1 1
 
3.1%
1.2 2
6.2%
1.5 1
 
3.1%
ValueCountFrequency (%)
36.6 1
3.1%
30.9 1
3.1%
24.3 1
3.1%
23.8 1
3.1%
16.8 1
3.1%
12.9 1
3.1%
11.0 1
3.1%
10.5 1
3.1%
10.4 1
3.1%
8.3 1
3.1%

701.5
Real number (ℝ)

ZEROS 

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.9125
Minimum0
Maximum335.4
Zeros2
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:24.563099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.055
Q11.375
median3.65
Q317.975
95-th percentile48.4
Maximum335.4
Range335.4
Interquartile range (IQR)16.6

Descriptive statistics

Standard deviation59.213734
Coefficient of variation (CV)2.7022811
Kurtosis27.459685
Mean21.9125
Median Absolute Deviation (MAD)3.6
Skewness5.0888581
Sum701.2
Variance3506.2663
MonotonicityNot monotonic
2023-12-11T12:30:25.002224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0.0 2
 
6.2%
2.3 2
 
6.2%
1.3 1
 
3.1%
2.9 1
 
3.1%
15.1 1
 
3.1%
12.6 1
 
3.1%
0.5 1
 
3.1%
7.6 1
 
3.1%
6.2 1
 
3.1%
3.6 1
 
3.1%
Other values (20) 20
62.5%
ValueCountFrequency (%)
0.0 2
6.2%
0.1 1
3.1%
0.2 1
3.1%
0.5 1
3.1%
0.6 1
3.1%
1.2 1
3.1%
1.3 1
3.1%
1.4 1
3.1%
1.6 1
3.1%
2.1 1
3.1%
ValueCountFrequency (%)
335.4 1
3.1%
49.5 1
3.1%
47.5 1
3.1%
45.3 1
3.1%
35.0 1
3.1%
34.8 1
3.1%
28.4 1
3.1%
26.6 1
3.1%
15.1 1
3.1%
12.6 1
3.1%

239.6
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4875
Minimum0
Maximum48.4
Zeros3
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:25.343276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.6
median2.1
Q37.7
95-th percentile33.065
Maximum48.4
Range48.4
Interquartile range (IQR)7.1

Descriptive statistics

Standard deviation11.926056
Coefficient of variation (CV)1.5927954
Kurtosis4.2728091
Mean7.4875
Median Absolute Deviation (MAD)1.95
Skewness2.1654465
Sum239.6
Variance142.23081
MonotonicityNot monotonic
2023-12-11T12:30:25.547119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0.0 3
 
9.4%
1.0 2
 
6.2%
0.3 2
 
6.2%
0.2 2
 
6.2%
1.7 2
 
6.2%
1.5 1
 
3.1%
31.4 1
 
3.1%
4.0 1
 
3.1%
0.9 1
 
3.1%
0.7 1
 
3.1%
Other values (16) 16
50.0%
ValueCountFrequency (%)
0.0 3
9.4%
0.1 1
 
3.1%
0.2 2
6.2%
0.3 2
6.2%
0.7 1
 
3.1%
0.8 1
 
3.1%
0.9 1
 
3.1%
1.0 2
6.2%
1.5 1
 
3.1%
1.7 2
6.2%
ValueCountFrequency (%)
48.4 1
3.1%
35.1 1
3.1%
31.4 1
3.1%
27.6 1
3.1%
15.7 1
3.1%
14.5 1
3.1%
12.8 1
3.1%
8.0 1
3.1%
7.6 1
3.1%
6.9 1
3.1%

776.8
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.275
Minimum0
Maximum415.7
Zeros2
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:25.678999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.055
Q11.5
median4.65
Q315.8
95-th percentile49.105
Maximum415.7
Range415.7
Interquartile range (IQR)14.3

Descriptive statistics

Standard deviation72.943469
Coefficient of variation (CV)3.0048803
Kurtosis29.160205
Mean24.275
Median Absolute Deviation (MAD)4.5
Skewness5.3010494
Sum776.8
Variance5320.7497
MonotonicityNot monotonic
2023-12-11T12:30:25.837355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
3.1 2
 
6.2%
10.7 2
 
6.2%
0.0 2
 
6.2%
34.3 2
 
6.2%
2.1 1
 
3.1%
4.4 1
 
3.1%
15.7 1
 
3.1%
0.7 1
 
3.1%
0.3 1
 
3.1%
4.9 1
 
3.1%
Other values (18) 18
56.2%
ValueCountFrequency (%)
0.0 2
6.2%
0.1 1
3.1%
0.2 1
3.1%
0.3 1
3.1%
0.7 1
3.1%
0.8 1
3.1%
1.2 1
3.1%
1.6 1
3.1%
2.1 1
3.1%
2.4 1
3.1%
ValueCountFrequency (%)
415.7 1
3.1%
51.8 1
3.1%
46.9 1
3.1%
36.4 1
3.1%
34.4 1
3.1%
34.3 2
6.2%
16.1 1
3.1%
15.7 1
3.1%
14.3 1
3.1%
11.5 1
3.1%

238.3
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.446875
Minimum0
Maximum49.3
Zeros2
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:25.974631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.055
Q10.6
median1.7
Q310.35
95-th percentile27.08
Maximum49.3
Range49.3
Interquartile range (IQR)9.75

Descriptive statistics

Standard deviation11.142681
Coefficient of variation (CV)1.4962895
Kurtosis6.2028638
Mean7.446875
Median Absolute Deviation (MAD)1.6
Skewness2.3393008
Sum238.3
Variance124.15934
MonotonicityNot monotonic
2023-12-11T12:30:26.125011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.1 3
 
9.4%
0.7 2
 
6.2%
0.0 2
 
6.2%
0.2 2
 
6.2%
0.8 1
 
3.1%
1.3 1
 
3.1%
35.0 1
 
3.1%
8.8 1
 
3.1%
1.1 1
 
3.1%
1.5 1
 
3.1%
Other values (17) 17
53.1%
ValueCountFrequency (%)
0.0 2
6.2%
0.1 3
9.4%
0.2 2
6.2%
0.3 1
 
3.1%
0.7 2
6.2%
0.8 1
 
3.1%
1.0 1
 
3.1%
1.1 1
 
3.1%
1.3 1
 
3.1%
1.4 1
 
3.1%
ValueCountFrequency (%)
49.3 1
3.1%
35.0 1
3.1%
20.6 1
3.1%
19.9 1
3.1%
16.2 1
3.1%
15.0 1
3.1%
11.7 1
3.1%
10.5 1
3.1%
10.3 1
3.1%
9.5 1
3.1%

804.3
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.140625
Minimum0
Maximum448.3
Zeros1
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:26.628433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q11.8
median4.5
Q318.95
95-th percentile42.72
Maximum448.3
Range448.3
Interquartile range (IQR)17.15

Descriptive statistics

Standard deviation78.338051
Coefficient of variation (CV)3.1159946
Kurtosis30.027545
Mean25.140625
Median Absolute Deviation (MAD)4.4
Skewness5.4075678
Sum804.5
Variance6136.8502
MonotonicityNot monotonic
2023-12-11T12:30:26.765853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.1 3
 
9.4%
3.9 2
 
6.2%
0.4 2
 
6.2%
2.5 2
 
6.2%
1.9 1
 
3.1%
35.2 1
 
3.1%
0.0 1
 
3.1%
18.8 1
 
3.1%
18.6 1
 
3.1%
0.5 1
 
3.1%
Other values (17) 17
53.1%
ValueCountFrequency (%)
0.0 1
 
3.1%
0.1 3
9.4%
0.4 2
6.2%
0.5 1
 
3.1%
1.5 1
 
3.1%
1.9 1
 
3.1%
2.0 1
 
3.1%
2.5 2
6.2%
3.0 1
 
3.1%
3.7 1
 
3.1%
ValueCountFrequency (%)
448.3 1
3.1%
43.6 1
3.1%
42.0 1
3.1%
35.2 1
3.1%
33.7 1
3.1%
30.9 1
3.1%
25.7 1
3.1%
19.4 1
3.1%
18.8 1
3.1%
18.6 1
3.1%

260.5
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.14375
Minimum0
Maximum48.5
Zeros4
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:26.925209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.6
median3.65
Q310.675
95-th percentile25.925
Maximum48.5
Range48.5
Interquartile range (IQR)10.075

Descriptive statistics

Standard deviation10.961044
Coefficient of variation (CV)1.3459455
Kurtosis4.8925282
Mean8.14375
Median Absolute Deviation (MAD)3.5
Skewness2.0338472
Sum260.6
Variance120.14448
MonotonicityNot monotonic
2023-12-11T12:30:27.071617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.0 4
 
12.5%
0.6 2
 
6.2%
0.9 2
 
6.2%
1.6 1
 
3.1%
48.5 1
 
3.1%
7.7 1
 
3.1%
0.3 1
 
3.1%
0.8 1
 
3.1%
1.4 1
 
3.1%
4.3 1
 
3.1%
Other values (17) 17
53.1%
ValueCountFrequency (%)
0.0 4
12.5%
0.3 1
 
3.1%
0.4 1
 
3.1%
0.5 1
 
3.1%
0.6 2
6.2%
0.8 1
 
3.1%
0.9 2
6.2%
1.4 1
 
3.1%
1.6 1
 
3.1%
2.1 1
 
3.1%
ValueCountFrequency (%)
48.5 1
3.1%
29.5 1
3.1%
23.0 1
3.1%
22.1 1
3.1%
18.8 1
3.1%
17.5 1
3.1%
17.3 1
3.1%
13.9 1
3.1%
9.6 1
3.1%
9.2 1
3.1%

592.1
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.50625
Minimum0
Maximum196.3
Zeros1
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:27.219075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q11.8
median6.85
Q322.6
95-th percentile49.485
Maximum196.3
Range196.3
Interquartile range (IQR)20.8

Descriptive statistics

Standard deviation35.426844
Coefficient of variation (CV)1.9143178
Kurtosis21.606456
Mean18.50625
Median Absolute Deviation (MAD)6.75
Skewness4.3424106
Sum592.2
Variance1255.0613
MonotonicityNot monotonic
2023-12-11T12:30:27.405582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.1 3
 
9.4%
1.9 2
 
6.2%
3.3 1
 
3.1%
0.0 1
 
3.1%
21.3 1
 
3.1%
18.5 1
 
3.1%
0.5 1
 
3.1%
2.6 1
 
3.1%
17.8 1
 
3.1%
6.8 1
 
3.1%
Other values (19) 19
59.4%
ValueCountFrequency (%)
0.0 1
 
3.1%
0.1 3
9.4%
0.5 1
 
3.1%
0.8 1
 
3.1%
1.4 1
 
3.1%
1.5 1
 
3.1%
1.9 2
6.2%
2.6 1
 
3.1%
3.1 1
 
3.1%
3.3 1
 
3.1%
ValueCountFrequency (%)
196.3 1
3.1%
50.2 1
3.1%
48.9 1
3.1%
35.8 1
3.1%
32.4 1
3.1%
27.3 1
3.1%
24.0 1
3.1%
23.8 1
3.1%
22.2 1
3.1%
21.3 1
3.1%

263.9
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.25
Minimum0
Maximum54.1
Zeros2
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:27.547736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.055
Q10.575
median3.05
Q312.175
95-th percentile32.2
Maximum54.1
Range54.1
Interquartile range (IQR)11.6

Descriptive statistics

Standard deviation12.345588
Coefficient of variation (CV)1.4964349
Kurtosis5.4568934
Mean8.25
Median Absolute Deviation (MAD)2.85
Skewness2.2261238
Sum264
Variance152.41355
MonotonicityNot monotonic
2023-12-11T12:30:27.687118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.1 3
 
9.4%
0.8 2
 
6.2%
0.3 2
 
6.2%
0.0 2
 
6.2%
3.1 2
 
6.2%
15.3 2
 
6.2%
1.1 1
 
3.1%
54.1 1
 
3.1%
1.7 1
 
3.1%
3.0 1
 
3.1%
Other values (15) 15
46.9%
ValueCountFrequency (%)
0.0 2
6.2%
0.1 3
9.4%
0.3 2
6.2%
0.5 1
 
3.1%
0.6 1
 
3.1%
0.8 2
6.2%
1.1 1
 
3.1%
1.3 1
 
3.1%
1.7 1
 
3.1%
1.9 1
 
3.1%
ValueCountFrequency (%)
54.1 1
3.1%
33.3 1
3.1%
31.3 1
3.1%
21.1 1
3.1%
19.9 1
3.1%
15.3 2
6.2%
15.1 1
3.1%
11.2 1
3.1%
9.2 1
3.1%
6.3 1
3.1%

504.0
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.75625
Minimum0
Maximum137.6
Zeros1
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:27.819921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q11.55
median5.85
Q323.35
95-th percentile55.325
Maximum137.6
Range137.6
Interquartile range (IQR)21.8

Descriptive statistics

Standard deviation26.832178
Coefficient of variation (CV)1.7029546
Kurtosis13.773107
Mean15.75625
Median Absolute Deviation (MAD)5.55
Skewness3.372302
Sum504.2
Variance719.96577
MonotonicityNot monotonic
2023-12-11T12:30:27.956683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1.8 2
 
6.2%
0.3 2
 
6.2%
0.1 2
 
6.2%
6.0 2
 
6.2%
3.3 1
 
3.1%
0.0 1
 
3.1%
22.4 1
 
3.1%
27.0 1
 
3.1%
0.4 1
 
3.1%
6.1 1
 
3.1%
Other values (18) 18
56.2%
ValueCountFrequency (%)
0.0 1
3.1%
0.1 2
6.2%
0.3 2
6.2%
0.4 1
3.1%
1.3 1
3.1%
1.4 1
3.1%
1.6 1
3.1%
1.7 1
3.1%
1.8 2
6.2%
2.6 1
3.1%
ValueCountFrequency (%)
137.6 1
3.1%
56.7 1
3.1%
54.2 1
3.1%
29.9 1
3.1%
27.5 1
3.1%
27.0 1
3.1%
26.9 1
3.1%
26.2 1
3.1%
22.4 1
3.1%
16.9 1
3.1%

260.3
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.1375
Minimum0
Maximum46.4
Zeros1
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:28.099371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q10.725
median2.65
Q310.425
95-th percentile35.905
Maximum46.4
Range46.4
Interquartile range (IQR)9.7

Descriptive statistics

Standard deviation12.219465
Coefficient of variation (CV)1.501624
Kurtosis3.6752459
Mean8.1375
Median Absolute Deviation (MAD)2.4
Skewness2.0386858
Sum260.4
Variance149.31532
MonotonicityNot monotonic
2023-12-11T12:30:28.257195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.8 2
 
6.2%
0.1 2
 
6.2%
3.7 2
 
6.2%
0.5 2
 
6.2%
2.4 1
 
3.1%
0.0 1
 
3.1%
46.4 1
 
3.1%
19.5 1
 
3.1%
1.1 1
 
3.1%
1.3 1
 
3.1%
Other values (18) 18
56.2%
ValueCountFrequency (%)
0.0 1
3.1%
0.1 2
6.2%
0.2 1
3.1%
0.3 1
3.1%
0.4 1
3.1%
0.5 2
6.2%
0.8 2
6.2%
1.0 1
3.1%
1.1 1
3.1%
1.2 1
3.1%
ValueCountFrequency (%)
46.4 1
3.1%
43.0 1
3.1%
30.1 1
3.1%
21.7 1
3.1%
20.7 1
3.1%
19.5 1
3.1%
11.9 1
3.1%
11.4 1
3.1%
10.1 1
3.1%
7.1 1
3.1%

642.8
Real number (ℝ)

ZEROS 

Distinct31
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.090625
Minimum0
Maximum262.6
Zeros1
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:28.431596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.265
Q12.1
median5.35
Q319.6
95-th percentile68.225
Maximum262.6
Range262.6
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation47.45243
Coefficient of variation (CV)2.3619191
Kurtosis23.495978
Mean20.090625
Median Absolute Deviation (MAD)4.6
Skewness4.6322071
Sum642.9
Variance2251.7331
MonotonicityNot monotonic
2023-12-11T12:30:28.587452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1.5 2
 
6.2%
2.3 1
 
3.1%
5.5 1
 
3.1%
0.0 1
 
3.1%
20.2 1
 
3.1%
0.1 1
 
3.1%
30.9 1
 
3.1%
0.8 1
 
3.1%
2.7 1
 
3.1%
5.4 1
 
3.1%
Other values (21) 21
65.6%
ValueCountFrequency (%)
0.0 1
3.1%
0.1 1
3.1%
0.4 1
3.1%
0.7 1
3.1%
0.8 1
3.1%
1.5 2
6.2%
1.8 1
3.1%
2.2 1
3.1%
2.3 1
3.1%
2.4 1
3.1%
ValueCountFrequency (%)
262.6 1
3.1%
70.7 1
3.1%
66.2 1
3.1%
30.9 1
3.1%
27.2 1
3.1%
24.3 1
3.1%
20.7 1
3.1%
20.2 1
3.1%
19.4 1
3.1%
18.1 1
3.1%

265.2
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.290625
Minimum0
Maximum44.6
Zeros1
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:28.746697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q10.725
median1.8
Q39.45
95-th percentile35.575
Maximum44.6
Range44.6
Interquartile range (IQR)8.725

Descriptive statistics

Standard deviation12.148314
Coefficient of variation (CV)1.4653073
Kurtosis2.5427262
Mean8.290625
Median Absolute Deviation (MAD)1.7
Skewness1.8268178
Sum265.3
Variance147.58152
MonotonicityNot monotonic
2023-12-11T12:30:28.911646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0.1 3
 
9.4%
1.0 3
 
9.4%
0.8 2
 
6.2%
1.7 2
 
6.2%
0.4 2
 
6.2%
0.5 2
 
6.2%
11.9 1
 
3.1%
0.0 1
 
3.1%
39.7 1
 
3.1%
24.3 1
 
3.1%
Other values (14) 14
43.8%
ValueCountFrequency (%)
0.0 1
 
3.1%
0.1 3
9.4%
0.4 2
6.2%
0.5 2
6.2%
0.8 2
6.2%
1.0 3
9.4%
1.4 1
 
3.1%
1.7 2
6.2%
1.9 1
 
3.1%
2.8 1
 
3.1%
ValueCountFrequency (%)
44.6 1
3.1%
39.7 1
3.1%
32.2 1
3.1%
25.3 1
3.1%
24.3 1
3.1%
18.9 1
3.1%
11.9 1
3.1%
9.9 1
3.1%
9.3 1
3.1%
8.8 1
3.1%

676.3
Real number (ℝ)

ZEROS 

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.128125
Minimum0
Maximum202.2
Zeros1
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-11T12:30:29.057816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q11.9
median6.35
Q319.6
95-th percentile97.495
Maximum202.2
Range202.2
Interquartile range (IQR)17.7

Descriptive statistics

Standard deviation41.368838
Coefficient of variation (CV)1.9579986
Kurtosis12.126754
Mean21.128125
Median Absolute Deviation (MAD)5.1
Skewness3.307229
Sum676.1
Variance1711.3808
MonotonicityNot monotonic
2023-12-11T12:30:29.207289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1.9 2
 
6.2%
0.1 2
 
6.2%
2.8 1
 
3.1%
6.3 1
 
3.1%
0.0 1
 
3.1%
23.2 1
 
3.1%
54.4 1
 
3.1%
0.8 1
 
3.1%
2.2 1
 
3.1%
6.2 1
 
3.1%
Other values (20) 20
62.5%
ValueCountFrequency (%)
0.0 1
3.1%
0.1 2
6.2%
0.5 1
3.1%
0.8 1
3.1%
1.0 1
3.1%
1.7 1
3.1%
1.9 2
6.2%
2.2 1
3.1%
2.5 1
3.1%
2.7 1
3.1%
ValueCountFrequency (%)
202.2 1
3.1%
106.9 1
3.1%
89.8 1
3.1%
54.4 1
3.1%
34.3 1
3.1%
25.6 1
3.1%
23.6 1
3.1%
23.2 1
3.1%
18.4 1
3.1%
12.5 1
3.1%

1.9
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T12:30:29.455782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4
Min length1

Characters and Unicode

Total characters128
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

Unique32 ?
Unique (%)100.0%

Sample

1st row△3.4
2nd row△49.5
3rd row△0.7
4th row△40.7
5th row26.9
ValueCountFrequency (%)
△3.4 1
 
3.1%
△49.5 1
 
3.1%
△14.4 1
 
3.1%
3.8 1
 
3.1%
24.4 1
 
3.1%
△9.6 1
 
3.1%
△6.9 1
 
3.1%
6.5 1
 
3.1%
61.5 1
 
3.1%
5 1
 
3.1%
Other values (22) 22
68.8%
2023-12-11T12:30:29.851355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 29
22.7%
△ 16
12.5%
1 16
12.5%
8 12
9.4%
4 11
 
8.6%
5 9
 
7.0%
6 9
 
7.0%
9 8
 
6.2%
7 7
 
5.5%
2 5
 
3.9%
Other values (2) 6
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 83
64.8%
Other Punctuation 29
 
22.7%
Other Symbol 16
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
19.3%
8 12
14.5%
4 11
13.3%
5 9
10.8%
6 9
10.8%
9 8
9.6%
7 7
8.4%
2 5
 
6.0%
3 4
 
4.8%
0 2
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 29
100.0%
Other Symbol
ValueCountFrequency (%)
△ 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 128
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 29
22.7%
△ 16
12.5%
1 16
12.5%
8 12
9.4%
4 11
 
8.6%
5 9
 
7.0%
6 9
 
7.0%
9 8
 
6.2%
7 7
 
5.5%
2 5
 
3.9%
Other values (2) 6
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 112
87.5%
Geometric Shapes 16
 
12.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 29
25.9%
1 16
14.3%
8 12
10.7%
4 11
 
9.8%
5 9
 
8.0%
6 9
 
8.0%
9 8
 
7.1%
7 7
 
6.2%
2 5
 
4.5%
3 4
 
3.6%
Geometric Shapes
ValueCountFrequency (%)
△ 16
100.0%

5.2
Text

Distinct31
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-11T12:30:30.031372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.9375
Min length2

Characters and Unicode

Total characters126
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

Unique30 ?
Unique (%)93.8%

Sample

1st row19.7
2nd row△40.8
3rd row158.5
4th row△42
5th row30.5
ValueCountFrequency (%)
14.4 2
 
6.2%
19.7 1
 
3.1%
△36.7 1
 
3.1%
15.2 1
 
3.1%
7.9 1
 
3.1%
75.8 1
 
3.1%
1.8 1
 
3.1%
△16.2 1
 
3.1%
45.3 1
 
3.1%
51.3 1
 
3.1%
Other values (21) 21
65.6%
2023-12-11T12:30:30.380449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 27
21.4%
1 16
12.7%
4 12
9.5%
△ 12
9.5%
2 11
8.7%
5 10
 
7.9%
3 9
 
7.1%
7 9
 
7.1%
8 6
 
4.8%
9 5
 
4.0%
Other values (2) 9
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 87
69.0%
Other Punctuation 27
 
21.4%
Other Symbol 12
 
9.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
18.4%
4 12
13.8%
2 11
12.6%
5 10
11.5%
3 9
10.3%
7 9
10.3%
8 6
 
6.9%
9 5
 
5.7%
6 5
 
5.7%
0 4
 
4.6%
Other Punctuation
ValueCountFrequency (%)
. 27
100.0%
Other Symbol
ValueCountFrequency (%)
△ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 126
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 27
21.4%
1 16
12.7%
4 12
9.5%
△ 12
9.5%
2 11
8.7%
5 10
 
7.9%
3 9
 
7.1%
7 9
 
7.1%
8 6
 
4.8%
9 5
 
4.0%
Other values (2) 9
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 114
90.5%
Geometric Shapes 12
 
9.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 27
23.7%
1 16
14.0%
4 12
10.5%
2 11
9.6%
5 10
 
8.8%
3 9
 
7.9%
7 9
 
7.9%
8 6
 
5.3%
9 5
 
4.4%
6 5
 
4.4%
Geometric Shapes
ValueCountFrequency (%)
△ 12
100.0%

Unnamed: 23
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing32
Missing (%)100.0%
Memory size420.0 B

Sample

총계210.9662.3164.8527.6227.2715.6214.8701.5239.6776.8238.3804.3260.5592.1263.9504.0260.3642.8265.2676.31.95.2Unnamed: 23
0네팔0.41.40.41.30.71.60.41.31.02.10.81.90.61.90.81.80.82.30.82.8△3.419.7<NA>
1동티모르1.11.01.91.81.51.52.62.32.72.42.82.52.11.91.91.71.91.81.01.0△49.5△40.8<NA>
2레바논1.42.82.33.20.52.80.82.11.03.10.72.00.93.50.51.40.83.20.88.4△0.7158.5<NA>
3리비아7.06.77.215.213.326.08.326.64.716.11.99.55.423.84.026.22.919.41.711.2△40.7△42<NA>
4몰디브0.20.30.00.00.10.10.10.20.10.20.10.10.00.10.10.30.10.40.10.526.930.5<NA>
5몽골27.342.525.742.719.441.516.835.014.536.415.042.018.850.219.956.721.766.232.289.848.135.5<NA>
6바레인0.41.50.31.30.21.00.31.20.31.20.31.50.41.50.31.30.31.50.41.719.112.9<NA>
7방글라데시6.49.95.68.38.010.16.39.78.010.716.219.49.614.711.216.911.418.19.318.4△18.21.7<NA>
8부탄0.00.00.00.00.00.00.00.00.00.00.00.10.00.10.00.10.41.50.51.918.624.7<NA>
9사우디아라비아35.441.39.633.47.136.310.534.86.934.36.130.96.027.36.326.96.224.36.725.68.85.3<NA>
총계210.9662.3164.8527.6227.2715.6214.8701.5239.6776.8238.3804.3260.5592.1263.9504.0260.3642.8265.2676.31.95.2Unnamed: 23
22인도8.723.116.933.922.143.123.845.327.646.920.643.623.048.933.354.243.070.744.6106.93.651.3<NA>
23카자흐스탄13.035.015.147.712.852.310.449.57.634.48.633.79.235.89.229.97.120.77.423.6514.4<NA>
24카타르0.72.60.63.21.73.91.23.60.73.10.73.74.36.83.05.75.48.68.812.561.545.3<NA>
25쿠웨이트5.96.70.63.40.95.81.16.21.77.01.513.81.417.81.76.11.35.41.46.26.514.4<NA>
26키르기스스탄1.67.12.07.72.16.91.67.60.94.91.15.10.82.60.81.81.12.71.02.2△6.9△16.2<NA>
27타지키스탄0.30.80.50.80.91.20.40.50.20.30.20.50.30.50.30.40.50.80.50.8△9.61.8<NA>
28터키4.813.73.914.36.518.53.612.64.010.78.818.67.718.515.327.019.530.924.354.424.475.8<NA>
29투르크메니스탄1.31.51.41.81.01.31.22.30.30.70.10.40.00.10.10.10.10.10.10.13.87.9<NA>
30파키스탄6.88.59.78.114.412.124.315.131.415.735.018.848.521.354.122.446.420.239.723.2△14.415.2<NA>
31팔레스타인0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0△65.4△29<NA>