Overview

Dataset statistics

Number of variables24
Number of observations93
Missing cells93
Missing cells (%)4.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.5 KiB
Average record size in memory214.4 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=20210930000000001604

Alerts

Unnamed: 23 has 93 (100.0%) missing valuesMissing
총계 has unique valuesUnique
Unnamed: 23 is an unsupported type, check if it needs cleaning or further analysisUnsupported
604.3 has 29 (31.2%) zerosZeros
1,553.7 has 25 (26.9%) zerosZeros
656.0 has 31 (33.3%) zerosZeros
1,595.8 has 27 (29.0%) zerosZeros
727.7 has 29 (31.2%) zerosZeros
1,793.4 has 25 (26.9%) zerosZeros
627.1 has 26 (28.0%) zerosZeros
1,736.0 has 23 (24.7%) zerosZeros
691.9 has 25 (26.9%) zerosZeros
1,932.3 has 23 (24.7%) zerosZeros
749.6 has 26 (28.0%) zerosZeros
2,178.8 has 23 (24.7%) zerosZeros
846.4 has 28 (30.1%) zerosZeros
2,209.4 has 24 (25.8%) zerosZeros
890.1 has 23 (24.7%) zerosZeros
2,282.5 has 21 (22.6%) zerosZeros
880.7 has 26 (28.0%) zerosZeros
2,596.4 has 24 (25.8%) zerosZeros
902.3 has 27 (29.0%) zerosZeros
3,023.0 has 24 (25.8%) zerosZeros

Reproduction

Analysis started2023-12-11 03:06:30.066917
Analysis finished2023-12-11 03:06:30.358166
Duration0.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

총계
Text

UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size876.0 B
2023-12-11T12:06:30.583329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length4.3548387
Min length1

Characters and Unicode

Total characters405
Distinct characters129
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)100.0%

Sample

1st row가이아나
2nd row과들루프
3rd row과테말라
4th row괌
5th row그리스
ValueCountFrequency (%)
버진아일랜드 2
 
1.9%
제도 2
 
1.9%
가이아나 1
 
1.0%
지브롤터 1
 
1.0%
저지 1
 
1.0%
자메이카 1
 
1.0%
이탈리아 1
 
1.0%
우크라이나 1
 
1.0%
우루과이 1
 
1.0%
온두라스 1
 
1.0%
Other values (92) 92
88.5%
2023-12-11T12:06:31.020609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 29
 
7.2%
스 16
 
4.0%
리 13
 
3.2%
니 12
 
3.0%
라 12
 
3.0%
11
 
2.7%
바 11
 
2.7%
이 11
 
2.7%
도 10
 
2.5%
르 10
 
2.5%
Other values (119) 270
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 393
97.0%
Space Separator 11
 
2.7%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 29
 
7.4%
스 16
 
4.1%
리 13
 
3.3%
니 12
 
3.1%
라 12
 
3.1%
바 11
 
2.8%
이 11
 
2.8%
도 10
 
2.5%
르 10
 
2.5%
드 10
 
2.5%
Other values (117) 259
65.9%
Space Separator
ValueCountFrequency (%)
11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 393
97.0%
Common 12
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 29
 
7.4%
스 16
 
4.1%
리 13
 
3.3%
니 12
 
3.1%
라 12
 
3.1%
바 11
 
2.8%
이 11
 
2.8%
도 10
 
2.5%
르 10
 
2.5%
드 10
 
2.5%
Other values (117) 259
65.9%
Common
ValueCountFrequency (%)
11
91.7%
- 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 393
97.0%
ASCII 12
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 29
 
7.4%
스 16
 
4.1%
리 13
 
3.3%
니 12
 
3.1%
라 12
 
3.1%
바 11
 
2.8%
이 11
 
2.8%
도 10
 
2.5%
르 10
 
2.5%
드 10
 
2.5%
Other values (117) 259
65.9%
ASCII
ValueCountFrequency (%)
11
91.7%
- 1
 
8.3%

604.3
Real number (ℝ)

ZEROS 

Distinct40
Distinct (%)43.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4978495
Minimum0
Maximum218
Zeros29
Zeros (%)31.2%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:31.178766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.5
Q32.3
95-th percentile19.88
Maximum218
Range218
Interquartile range (IQR)2.3

Descriptive statistics

Standard deviation26.936479
Coefficient of variation (CV)4.1454452
Kurtosis46.993502
Mean6.4978495
Median Absolute Deviation (MAD)0.5
Skewness6.6153784
Sum604.3
Variance725.57391
MonotonicityNot monotonic
2023-12-11T12:06:31.369004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0.0 29
31.2%
0.2 6
 
6.5%
0.1 6
 
6.5%
0.3 5
 
5.4%
1.6 3
 
3.2%
1.8 3
 
3.2%
0.5 3
 
3.2%
0.6 3
 
3.2%
1.4 2
 
2.2%
1.1 2
 
2.2%
Other values (30) 31
33.3%
ValueCountFrequency (%)
0.0 29
31.2%
0.1 6
 
6.5%
0.2 6
 
6.5%
0.3 5
 
5.4%
0.5 3
 
3.2%
0.6 3
 
3.2%
0.7 2
 
2.2%
0.8 1
 
1.1%
1.1 2
 
2.2%
1.2 1
 
1.1%
ValueCountFrequency (%)
218.0 1
1.1%
134.5 1
1.1%
47.1 1
1.1%
31.7 1
1.1%
30.2 1
1.1%
13.0 1
1.1%
12.3 1
1.1%
11.8 1
1.1%
10.5 1
1.1%
7.7 1
1.1%

1,553.7
Real number (ℝ)

ZEROS 

Distinct48
Distinct (%)51.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.705376
Minimum0
Maximum664
Zeros25
Zeros (%)26.9%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:31.551428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.2
Q34.6
95-th percentile55.94
Maximum664
Range664
Interquartile range (IQR)4.6

Descriptive statistics

Standard deviation74.605627
Coefficient of variation (CV)4.4659651
Kurtosis63.964088
Mean16.705376
Median Absolute Deviation (MAD)1.2
Skewness7.6556119
Sum1553.6
Variance5565.9996
MonotonicityNot monotonic
2023-12-11T12:06:31.693271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0.0 25
26.9%
0.1 8
 
8.6%
1.4 4
 
4.3%
0.3 3
 
3.2%
1.8 3
 
3.2%
2.7 3
 
3.2%
0.5 2
 
2.2%
0.6 2
 
2.2%
1.5 2
 
2.2%
0.2 2
 
2.2%
Other values (38) 39
41.9%
ValueCountFrequency (%)
0.0 25
26.9%
0.1 8
 
8.6%
0.2 2
 
2.2%
0.3 3
 
3.2%
0.4 1
 
1.1%
0.5 2
 
2.2%
0.6 2
 
2.2%
0.9 1
 
1.1%
1.0 1
 
1.1%
1.1 1
 
1.1%
ValueCountFrequency (%)
664.0 1
1.1%
259.0 1
1.1%
99.5 1
1.1%
83.1 1
1.1%
60.8 1
1.1%
52.7 1
1.1%
47.9 1
1.1%
35.7 1
1.1%
32.0 1
1.1%
21.8 1
1.1%

656.0
Real number (ℝ)

ZEROS 

Distinct41
Distinct (%)44.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0505376
Minimum0
Maximum231.8
Zeros31
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:31.865552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.6
Q32.5
95-th percentile21.76
Maximum231.8
Range231.8
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation28.115107
Coefficient of variation (CV)3.9876544
Kurtosis49.046976
Mean7.0505376
Median Absolute Deviation (MAD)0.6
Skewness6.7199958
Sum655.7
Variance790.45927
MonotonicityNot monotonic
2023-12-11T12:06:32.000201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0.0 31
33.3%
0.2 5
 
5.4%
0.5 3
 
3.2%
1.0 3
 
3.2%
0.1 3
 
3.2%
2.3 3
 
3.2%
0.6 3
 
3.2%
3.3 3
 
3.2%
1.2 2
 
2.2%
1.9 2
 
2.2%
Other values (31) 35
37.6%
ValueCountFrequency (%)
0.0 31
33.3%
0.1 3
 
3.2%
0.2 5
 
5.4%
0.3 1
 
1.1%
0.4 2
 
2.2%
0.5 3
 
3.2%
0.6 3
 
3.2%
0.7 1
 
1.1%
0.8 1
 
1.1%
1.0 3
 
3.2%
ValueCountFrequency (%)
231.8 1
1.1%
133.1 1
1.1%
51.5 1
1.1%
27.9 1
1.1%
26.5 1
1.1%
18.6 1
1.1%
17.9 1
1.1%
16.7 1
1.1%
16.4 1
1.1%
12.2 1
1.1%

1,595.8
Real number (ℝ)

ZEROS 

Distinct52
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.162366
Minimum0
Maximum740.2
Zeros27
Zeros (%)29.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:32.133142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.5
Q35.8
95-th percentile47.02
Maximum740.2
Range740.2
Interquartile range (IQR)5.8

Descriptive statistics

Standard deviation81.563119
Coefficient of variation (CV)4.7524404
Kurtosis69.404771
Mean17.162366
Median Absolute Deviation (MAD)1.5
Skewness8.0261739
Sum1596.1
Variance6652.5424
MonotonicityNot monotonic
2023-12-11T12:06:32.271300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 27
29.0%
0.1 4
 
4.3%
0.2 4
 
4.3%
1.7 3
 
3.2%
1.6 3
 
3.2%
0.4 2
 
2.2%
0.3 2
 
2.2%
3.3 2
 
2.2%
5.4 2
 
2.2%
2.1 2
 
2.2%
Other values (42) 42
45.2%
ValueCountFrequency (%)
0.0 27
29.0%
0.1 4
 
4.3%
0.2 4
 
4.3%
0.3 2
 
2.2%
0.4 2
 
2.2%
0.5 1
 
1.1%
0.7 1
 
1.1%
0.9 1
 
1.1%
1.0 1
 
1.1%
1.1 1
 
1.1%
ValueCountFrequency (%)
740.2 1
1.1%
254.9 1
1.1%
100.7 1
1.1%
81.8 1
1.1%
49.9 1
1.1%
45.1 1
1.1%
35.3 1
1.1%
32.2 1
1.1%
29.0 1
1.1%
20.4 1
1.1%

727.7
Real number (ℝ)

ZEROS 

Distinct47
Distinct (%)50.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.8215054
Minimum0
Maximum255.6
Zeros29
Zeros (%)31.2%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:32.426190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.8
Q33.4
95-th percentile29.86
Maximum255.6
Range255.6
Interquartile range (IQR)3.4

Descriptive statistics

Standard deviation29.961787
Coefficient of variation (CV)3.8306931
Kurtosis53.873586
Mean7.8215054
Median Absolute Deviation (MAD)0.8
Skewness6.9764201
Sum727.4
Variance897.70866
MonotonicityNot monotonic
2023-12-11T12:06:32.558044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0.0 29
31.2%
0.1 6
 
6.5%
0.2 6
 
6.5%
0.9 3
 
3.2%
0.8 2
 
2.2%
11.8 2
 
2.2%
0.7 2
 
2.2%
0.6 2
 
2.2%
1.9 2
 
2.2%
3.4 2
 
2.2%
Other values (37) 37
39.8%
ValueCountFrequency (%)
0.0 29
31.2%
0.1 6
 
6.5%
0.2 6
 
6.5%
0.6 2
 
2.2%
0.7 2
 
2.2%
0.8 2
 
2.2%
0.9 3
 
3.2%
1.0 1
 
1.1%
1.1 1
 
1.1%
1.2 1
 
1.1%
ValueCountFrequency (%)
255.6 1
1.1%
124.1 1
1.1%
53.1 1
1.1%
32.8 1
1.1%
30.7 1
1.1%
29.3 1
1.1%
22.5 1
1.1%
16.6 1
1.1%
11.8 2
2.2%
11.2 1
1.1%

1,793.4
Real number (ℝ)

ZEROS 

Distinct51
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.27957
Minimum0
Maximum811.3
Zeros25
Zeros (%)26.9%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:32.695536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.4
Q36.6
95-th percentile51.3
Maximum811.3
Range811.3
Interquartile range (IQR)6.6

Descriptive statistics

Standard deviation88.139147
Coefficient of variation (CV)4.5716345
Kurtosis73.008167
Mean19.27957
Median Absolute Deviation (MAD)1.4
Skewness8.2411128
Sum1793
Variance7768.5093
MonotonicityNot monotonic
2023-12-11T12:06:32.839855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 25
26.9%
0.1 8
 
8.6%
0.3 3
 
3.2%
0.7 2
 
2.2%
1.4 2
 
2.2%
2.9 2
 
2.2%
1.5 2
 
2.2%
1.0 2
 
2.2%
0.2 2
 
2.2%
1.6 2
 
2.2%
Other values (41) 43
46.2%
ValueCountFrequency (%)
0.0 25
26.9%
0.1 8
 
8.6%
0.2 2
 
2.2%
0.3 3
 
3.2%
0.6 1
 
1.1%
0.7 2
 
2.2%
0.8 1
 
1.1%
0.9 1
 
1.1%
1.0 2
 
2.2%
1.2 1
 
1.1%
ValueCountFrequency (%)
811.3 1
1.1%
238.1 1
1.1%
109.2 1
1.1%
81.7 1
1.1%
59.4 1
1.1%
45.9 1
1.1%
42.8 1
1.1%
38.8 1
1.1%
36.8 1
1.1%
35.0 1
1.1%

627.1
Real number (ℝ)

ZEROS 

Distinct43
Distinct (%)46.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.744086
Minimum0
Maximum271.4
Zeros26
Zeros (%)28.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:33.016752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.7
Q33.6
95-th percentile16.52
Maximum271.4
Range271.4
Interquartile range (IQR)3.6

Descriptive statistics

Standard deviation29.3429
Coefficient of variation (CV)4.3509083
Kurtosis73.932056
Mean6.744086
Median Absolute Deviation (MAD)0.7
Skewness8.2793107
Sum627.2
Variance861.00575
MonotonicityNot monotonic
2023-12-11T12:06:33.148849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0.0 26
28.0%
0.1 9
 
9.7%
0.3 4
 
4.3%
0.2 3
 
3.2%
1.5 3
 
3.2%
1.4 3
 
3.2%
1.2 3
 
3.2%
1.0 2
 
2.2%
1.6 2
 
2.2%
4.2 2
 
2.2%
Other values (33) 36
38.7%
ValueCountFrequency (%)
0.0 26
28.0%
0.1 9
 
9.7%
0.2 3
 
3.2%
0.3 4
 
4.3%
0.4 1
 
1.1%
0.5 1
 
1.1%
0.6 2
 
2.2%
0.7 1
 
1.1%
0.8 1
 
1.1%
0.9 1
 
1.1%
ValueCountFrequency (%)
271.4 1
1.1%
63.8 1
1.1%
53.9 1
1.1%
31.7 1
1.1%
18.2 1
1.1%
15.4 1
1.1%
15.1 1
1.1%
13.6 1
1.1%
13.3 1
1.1%
10.5 1
1.1%

1,736.0
Real number (ℝ)

ZEROS 

Distinct48
Distinct (%)51.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.666667
Minimum0
Maximum859
Zeros23
Zeros (%)24.7%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:33.288002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1
median1
Q36.9
95-th percentile53.82
Maximum859
Range859
Interquartile range (IQR)6.8

Descriptive statistics

Standard deviation91.258401
Coefficient of variation (CV)4.8888429
Kurtosis80.393319
Mean18.666667
Median Absolute Deviation (MAD)1
Skewness8.7256539
Sum1736
Variance8328.0957
MonotonicityNot monotonic
2023-12-11T12:06:33.442029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0.0 23
24.7%
0.2 8
 
8.6%
0.1 5
 
5.4%
1.0 5
 
5.4%
0.3 4
 
4.3%
1.3 2
 
2.2%
2.9 2
 
2.2%
5.1 2
 
2.2%
1.5 2
 
2.2%
3.3 2
 
2.2%
Other values (38) 38
40.9%
ValueCountFrequency (%)
0.0 23
24.7%
0.1 5
 
5.4%
0.2 8
 
8.6%
0.3 4
 
4.3%
0.7 1
 
1.1%
0.8 1
 
1.1%
1.0 5
 
5.4%
1.3 2
 
2.2%
1.4 1
 
1.1%
1.5 2
 
2.2%
ValueCountFrequency (%)
859.0 1
1.1%
140.9 1
1.1%
138.1 1
1.1%
86.5 1
1.1%
60.0 1
1.1%
49.7 1
1.1%
37.7 1
1.1%
37.3 1
1.1%
36.6 1
1.1%
32.4 1
1.1%

691.9
Real number (ℝ)

ZEROS 

Distinct45
Distinct (%)48.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4430108
Minimum0
Maximum309.4
Zeros25
Zeros (%)26.9%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:33.594971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.6
Q33.9
95-th percentile22.14
Maximum309.4
Range309.4
Interquartile range (IQR)3.9

Descriptive statistics

Standard deviation33.039934
Coefficient of variation (CV)4.439055
Kurtosis77.96679
Mean7.4430108
Median Absolute Deviation (MAD)0.6
Skewness8.5529586
Sum692.2
Variance1091.6373
MonotonicityNot monotonic
2023-12-11T12:06:33.785276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0.0 25
26.9%
0.1 10
 
10.8%
0.3 5
 
5.4%
1.8 3
 
3.2%
0.6 3
 
3.2%
0.2 3
 
3.2%
1.4 2
 
2.2%
0.4 2
 
2.2%
0.8 2
 
2.2%
1.6 2
 
2.2%
Other values (35) 36
38.7%
ValueCountFrequency (%)
0.0 25
26.9%
0.1 10
 
10.8%
0.2 3
 
3.2%
0.3 5
 
5.4%
0.4 2
 
2.2%
0.5 1
 
1.1%
0.6 3
 
3.2%
0.8 2
 
2.2%
1.2 1
 
1.1%
1.4 2
 
2.2%
ValueCountFrequency (%)
309.4 1
1.1%
64.3 1
1.1%
44.5 1
1.1%
32.1 1
1.1%
27.9 1
1.1%
18.3 1
1.1%
16.6 1
1.1%
15.6 1
1.1%
13.4 1
1.1%
13.0 1
1.1%

1,932.3
Real number (ℝ)

ZEROS 

Distinct52
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.775269
Minimum0
Maximum957.2
Zeros23
Zeros (%)24.7%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:33.938431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1
median1
Q37.7
95-th percentile74.84
Maximum957.2
Range957.2
Interquartile range (IQR)7.6

Descriptive statistics

Standard deviation100.98577
Coefficient of variation (CV)4.8608645
Kurtosis82.708866
Mean20.775269
Median Absolute Deviation (MAD)1
Skewness8.880608
Sum1932.1
Variance10198.125
MonotonicityNot monotonic
2023-12-11T12:06:34.077327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 23
24.7%
0.1 6
 
6.5%
0.2 5
 
5.4%
0.4 4
 
4.3%
0.3 4
 
4.3%
1.2 2
 
2.2%
0.8 2
 
2.2%
3.5 2
 
2.2%
1.1 2
 
2.2%
90.5 1
 
1.1%
Other values (42) 42
45.2%
ValueCountFrequency (%)
0.0 23
24.7%
0.1 6
 
6.5%
0.2 5
 
5.4%
0.3 4
 
4.3%
0.4 4
 
4.3%
0.5 1
 
1.1%
0.8 2
 
2.2%
0.9 1
 
1.1%
1.0 1
 
1.1%
1.1 2
 
2.2%
ValueCountFrequency (%)
957.2 1
1.1%
132.5 1
1.1%
98.5 1
1.1%
90.5 1
1.1%
88.7 1
1.1%
65.6 1
1.1%
54.2 1
1.1%
51.9 1
1.1%
51.0 1
1.1%
43.2 1
1.1%

749.6
Real number (ℝ)

ZEROS 

Distinct46
Distinct (%)49.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.0645161
Minimum0
Maximum301.8
Zeros26
Zeros (%)28.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:34.223296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.5
Q34.5
95-th percentile28.62
Maximum301.8
Range301.8
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation32.740699
Coefficient of variation (CV)4.0598467
Kurtosis72.308109
Mean8.0645161
Median Absolute Deviation (MAD)0.5
Skewness8.1440508
Sum750
Variance1071.9534
MonotonicityNot monotonic
2023-12-11T12:06:34.394704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0.0 26
28.0%
0.1 10
 
10.8%
0.5 5
 
5.4%
0.4 3
 
3.2%
2.0 3
 
3.2%
1.1 2
 
2.2%
1.5 2
 
2.2%
5.8 2
 
2.2%
0.3 2
 
2.2%
3.3 2
 
2.2%
Other values (36) 36
38.7%
ValueCountFrequency (%)
0.0 26
28.0%
0.1 10
 
10.8%
0.2 1
 
1.1%
0.3 2
 
2.2%
0.4 3
 
3.2%
0.5 5
 
5.4%
0.6 1
 
1.1%
0.9 1
 
1.1%
1.0 1
 
1.1%
1.1 2
 
2.2%
ValueCountFrequency (%)
301.8 1
1.1%
75.4 1
1.1%
45.4 1
1.1%
37.8 1
1.1%
33.3 1
1.1%
25.5 1
1.1%
23.8 1
1.1%
23.5 1
1.1%
21.9 1
1.1%
16.4 1
1.1%

2,178.8
Real number (ℝ)

ZEROS 

Distinct52
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.424731
Minimum0
Maximum1025.3
Zeros23
Zeros (%)24.7%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:34.792675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1
median1.2
Q37.8
95-th percentile90.72
Maximum1025.3
Range1025.3
Interquartile range (IQR)7.7

Descriptive statistics

Standard deviation109.00494
Coefficient of variation (CV)4.6534128
Kurtosis79.754513
Mean23.424731
Median Absolute Deviation (MAD)1.2
Skewness8.6677492
Sum2178.5
Variance11882.078
MonotonicityNot monotonic
2023-12-11T12:06:34.918455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 23
24.7%
0.1 7
 
7.5%
0.3 3
 
3.2%
5.0 3
 
3.2%
1.3 3
 
3.2%
0.2 3
 
3.2%
3.2 2
 
2.2%
1.2 2
 
2.2%
0.5 2
 
2.2%
4.3 2
 
2.2%
Other values (42) 43
46.2%
ValueCountFrequency (%)
0.0 23
24.7%
0.1 7
 
7.5%
0.2 3
 
3.2%
0.3 3
 
3.2%
0.4 1
 
1.1%
0.5 2
 
2.2%
0.6 1
 
1.1%
0.7 1
 
1.1%
0.8 1
 
1.1%
0.9 2
 
2.2%
ValueCountFrequency (%)
1025.3 1
1.1%
173.1 1
1.1%
122.9 1
1.1%
105.1 1
1.1%
100.2 1
1.1%
84.4 1
1.1%
67.1 1
1.1%
61.7 1
1.1%
52.5 1
1.1%
51.8 1
1.1%

846.4
Real number (ℝ)

ZEROS 

Distinct49
Distinct (%)52.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.0978495
Minimum0
Maximum333.3
Zeros28
Zeros (%)30.1%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:35.044545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.9
Q34.6
95-th percentile29.44
Maximum333.3
Range333.3
Interquartile range (IQR)4.6

Descriptive statistics

Standard deviation36.738817
Coefficient of variation (CV)4.0381869
Kurtosis67.925656
Mean9.0978495
Median Absolute Deviation (MAD)0.9
Skewness7.8774023
Sum846.1
Variance1349.7406
MonotonicityNot monotonic
2023-12-11T12:06:35.181300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
0.0 28
30.1%
0.2 4
 
4.3%
0.1 4
 
4.3%
0.3 3
 
3.2%
0.5 2
 
2.2%
1.4 2
 
2.2%
0.7 2
 
2.2%
0.8 2
 
2.2%
5.0 2
 
2.2%
3.4 2
 
2.2%
Other values (39) 42
45.2%
ValueCountFrequency (%)
0.0 28
30.1%
0.1 4
 
4.3%
0.2 4
 
4.3%
0.3 3
 
3.2%
0.5 2
 
2.2%
0.6 1
 
1.1%
0.7 2
 
2.2%
0.8 2
 
2.2%
0.9 1
 
1.1%
1.0 1
 
1.1%
ValueCountFrequency (%)
333.3 1
1.1%
109.2 1
1.1%
51.7 1
1.1%
37.0 1
1.1%
32.2 1
1.1%
27.6 1
1.1%
24.4 1
1.1%
22.8 1
1.1%
22.1 1
1.1%
15.6 1
1.1%

2,209.4
Real number (ℝ)

ZEROS 

Distinct53
Distinct (%)57.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.752688
Minimum0
Maximum1080
Zeros24
Zeros (%)25.8%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:35.323551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.9
Q36.9
95-th percentile72.12
Maximum1080
Range1080
Interquartile range (IQR)6.9

Descriptive statistics

Standard deviation114.79462
Coefficient of variation (CV)4.8329108
Kurtosis80.1612
Mean23.752688
Median Absolute Deviation (MAD)1.9
Skewness8.7122667
Sum2209
Variance13177.806
MonotonicityNot monotonic
2023-12-11T12:06:35.470963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 24
25.8%
0.1 6
 
6.5%
0.2 3
 
3.2%
0.4 3
 
3.2%
0.7 2
 
2.2%
5.0 2
 
2.2%
0.6 2
 
2.2%
2.6 2
 
2.2%
6.3 2
 
2.2%
0.9 2
 
2.2%
Other values (43) 45
48.4%
ValueCountFrequency (%)
0.0 24
25.8%
0.1 6
 
6.5%
0.2 3
 
3.2%
0.3 1
 
1.1%
0.4 3
 
3.2%
0.5 1
 
1.1%
0.6 2
 
2.2%
0.7 2
 
2.2%
0.8 1
 
1.1%
0.9 2
 
2.2%
ValueCountFrequency (%)
1080.0 1
1.1%
215.8 1
1.1%
122.3 1
1.1%
96.1 1
1.1%
79.2 1
1.1%
67.4 1
1.1%
64.3 1
1.1%
59.6 1
1.1%
48.4 1
1.1%
42.8 1
1.1%

890.1
Real number (ℝ)

ZEROS 

Distinct49
Distinct (%)52.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.5698925
Minimum0
Maximum359.1
Zeros23
Zeros (%)24.7%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:35.623724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1
median0.9
Q35.9
95-th percentile28.16
Maximum359.1
Range359.1
Interquartile range (IQR)5.8

Descriptive statistics

Standard deviation39.418948
Coefficient of variation (CV)4.1190586
Kurtosis69.352431
Mean9.5698925
Median Absolute Deviation (MAD)0.9
Skewness7.995628
Sum890
Variance1553.8534
MonotonicityNot monotonic
2023-12-11T12:06:35.760376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
0.0 23
24.7%
0.1 10
 
10.8%
0.3 4
 
4.3%
1.0 3
 
3.2%
0.5 3
 
3.2%
0.2 2
 
2.2%
7.7 2
 
2.2%
1.7 2
 
2.2%
1.4 2
 
2.2%
5.8 2
 
2.2%
Other values (39) 40
43.0%
ValueCountFrequency (%)
0.0 23
24.7%
0.1 10
10.8%
0.2 2
 
2.2%
0.3 4
 
4.3%
0.4 1
 
1.1%
0.5 3
 
3.2%
0.6 2
 
2.2%
0.7 1
 
1.1%
0.9 1
 
1.1%
1.0 3
 
3.2%
ValueCountFrequency (%)
359.1 1
1.1%
120.1 1
1.1%
41.2 1
1.1%
39.7 1
1.1%
31.1 1
1.1%
26.2 1
1.1%
25.3 1
1.1%
24.0 1
1.1%
18.0 1
1.1%
17.0 1
1.1%

2,282.5
Real number (ℝ)

ZEROS 

Distinct55
Distinct (%)59.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.541935
Minimum0
Maximum1171.3
Zeros21
Zeros (%)22.6%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:35.893752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1
median1.4
Q37.1
95-th percentile74.46
Maximum1171.3
Range1171.3
Interquartile range (IQR)7

Descriptive statistics

Standard deviation123.90446
Coefficient of variation (CV)5.0486834
Kurtosis82.091041
Mean24.541935
Median Absolute Deviation (MAD)1.4
Skewness8.8478405
Sum2282.4
Variance15352.316
MonotonicityNot monotonic
2023-12-11T12:06:36.026755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 21
22.6%
0.1 10
 
10.8%
0.5 4
 
4.3%
0.2 3
 
3.2%
4.3 2
 
2.2%
6.1 2
 
2.2%
1.0 2
 
2.2%
0.8 2
 
2.2%
16.2 1
 
1.1%
3.5 1
 
1.1%
Other values (45) 45
48.4%
ValueCountFrequency (%)
0.0 21
22.6%
0.1 10
10.8%
0.2 3
 
3.2%
0.3 1
 
1.1%
0.5 4
 
4.3%
0.6 1
 
1.1%
0.7 1
 
1.1%
0.8 2
 
2.2%
1.0 2
 
2.2%
1.2 1
 
1.1%
ValueCountFrequency (%)
1171.3 1
1.1%
204.7 1
1.1%
133.3 1
1.1%
99.7 1
1.1%
75.9 1
1.1%
73.5 1
1.1%
68.6 1
1.1%
58.6 1
1.1%
42.9 1
1.1%
42.3 1
1.1%

880.7
Real number (ℝ)

ZEROS 

Distinct47
Distinct (%)50.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.4698925
Minimum0
Maximum429.3
Zeros26
Zeros (%)28.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:36.165803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.6
Q35.1
95-th percentile26.96
Maximum429.3
Range429.3
Interquartile range (IQR)5.1

Descriptive statistics

Standard deviation45.695392
Coefficient of variation (CV)4.8253338
Kurtosis79.687619
Mean9.4698925
Median Absolute Deviation (MAD)0.6
Skewness8.6839842
Sum880.7
Variance2088.0689
MonotonicityNot monotonic
2023-12-11T12:06:36.329998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0.0 26
28.0%
0.1 9
 
9.7%
0.2 4
 
4.3%
1.1 3
 
3.2%
0.4 3
 
3.2%
0.5 2
 
2.2%
1.7 2
 
2.2%
0.6 2
 
2.2%
5.7 2
 
2.2%
6.0 2
 
2.2%
Other values (37) 38
40.9%
ValueCountFrequency (%)
0.0 26
28.0%
0.1 9
 
9.7%
0.2 4
 
4.3%
0.3 1
 
1.1%
0.4 3
 
3.2%
0.5 2
 
2.2%
0.6 2
 
2.2%
1.1 3
 
3.2%
1.2 1
 
1.1%
1.3 1
 
1.1%
ValueCountFrequency (%)
429.3 1
1.1%
88.0 1
1.1%
53.9 1
1.1%
46.4 1
1.1%
34.4 1
1.1%
22.0 1
1.1%
16.7 1
1.1%
15.2 1
1.1%
13.4 1
1.1%
11.2 1
1.1%

2,596.4
Real number (ℝ)

ZEROS 

Distinct52
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.91828
Minimum0
Maximum1519.8
Zeros24
Zeros (%)25.8%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:36.500438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.6
Q36
95-th percentile73.06
Maximum1519.8
Range1519.8
Interquartile range (IQR)6

Descriptive statistics

Standard deviation159.23217
Coefficient of variation (CV)5.7035095
Kurtosis86.319621
Mean27.91828
Median Absolute Deviation (MAD)1.6
Skewness9.1506938
Sum2596.4
Variance25354.885
MonotonicityNot monotonic
2023-12-11T12:06:36.658105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 24
25.8%
0.1 8
 
8.6%
4.0 3
 
3.2%
0.5 3
 
3.2%
0.2 3
 
3.2%
0.4 2
 
2.2%
4.1 2
 
2.2%
0.3 2
 
2.2%
11.1 2
 
2.2%
1.7 2
 
2.2%
Other values (42) 42
45.2%
ValueCountFrequency (%)
0.0 24
25.8%
0.1 8
 
8.6%
0.2 3
 
3.2%
0.3 2
 
2.2%
0.4 2
 
2.2%
0.5 3
 
3.2%
0.7 1
 
1.1%
0.8 1
 
1.1%
1.0 1
 
1.1%
1.2 1
 
1.1%
ValueCountFrequency (%)
1519.8 1
1.1%
180.8 1
1.1%
156.3 1
1.1%
116.4 1
1.1%
75.4 1
1.1%
71.5 1
1.1%
60.4 1
1.1%
58.7 1
1.1%
53.2 1
1.1%
31.2 1
1.1%

902.3
Real number (ℝ)

ZEROS 

Distinct46
Distinct (%)49.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.6989247
Minimum0
Maximum418.3
Zeros27
Zeros (%)29.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:36.842698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.8
Q34.5
95-th percentile25.48
Maximum418.3
Range418.3
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation44.871368
Coefficient of variation (CV)4.6264271
Kurtosis76.877879
Mean9.6989247
Median Absolute Deviation (MAD)0.8
Skewness8.4902174
Sum902
Variance2013.4397
MonotonicityNot monotonic
2023-12-11T12:06:36.985155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0.0 27
29.0%
0.2 6
 
6.5%
0.3 4
 
4.3%
0.1 4
 
4.3%
6.6 3
 
3.2%
0.8 3
 
3.2%
2.3 3
 
3.2%
0.9 2
 
2.2%
4.5 2
 
2.2%
1.8 2
 
2.2%
Other values (36) 37
39.8%
ValueCountFrequency (%)
0.0 27
29.0%
0.1 4
 
4.3%
0.2 6
 
6.5%
0.3 4
 
4.3%
0.4 1
 
1.1%
0.6 2
 
2.2%
0.7 1
 
1.1%
0.8 3
 
3.2%
0.9 2
 
2.2%
1.0 1
 
1.1%
ValueCountFrequency (%)
418.3 1
1.1%
99.0 1
1.1%
58.2 1
1.1%
45.6 1
1.1%
26.8 1
1.1%
24.6 1
1.1%
24.0 1
1.1%
20.4 1
1.1%
17.0 1
1.1%
15.8 1
1.1%

3,023.0
Real number (ℝ)

ZEROS 

Distinct53
Distinct (%)57.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.503226
Minimum0
Maximum1656.6
Zeros24
Zeros (%)25.8%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T12:06:37.176723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.4
Q310.5
95-th percentile99.92
Maximum1656.6
Range1656.6
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation174.42621
Coefficient of variation (CV)5.3664276
Kurtosis84.137087
Mean32.503226
Median Absolute Deviation (MAD)1.4
Skewness8.9926795
Sum3022.8
Variance30424.502
MonotonicityNot monotonic
2023-12-11T12:06:37.324613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 24
25.8%
0.1 4
 
4.3%
0.2 3
 
3.2%
0.8 3
 
3.2%
0.3 3
 
3.2%
0.4 3
 
3.2%
0.5 3
 
3.2%
2.6 2
 
2.2%
1.7 2
 
2.2%
5.0 2
 
2.2%
Other values (43) 44
47.3%
ValueCountFrequency (%)
0.0 24
25.8%
0.1 4
 
4.3%
0.2 3
 
3.2%
0.3 3
 
3.2%
0.4 3
 
3.2%
0.5 3
 
3.2%
0.7 1
 
1.1%
0.8 3
 
3.2%
0.9 1
 
1.1%
1.2 1
 
1.1%
ValueCountFrequency (%)
1656.6 1
1.1%
242.4 1
1.1%
169.6 1
1.1%
152.0 1
1.1%
100.1 1
1.1%
99.8 1
1.1%
81.9 1
1.1%
74.1 1
1.1%
56.1 1
1.1%
43.6 1
1.1%

2.5
Text

Distinct78
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Memory size876.0 B
2023-12-11T12:06:37.553123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.7526882
Min length1

Characters and Unicode

Total characters349
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

Unique74 ?
Unique (%)79.6%

Sample

1st row45.6
2nd row△19.5
3rd row△9.7
4th row17.3
5th row△4.2
ValueCountFrequency (%)
0 13
 
14.0%
△25 2
 
2.2%
△100 2
 
2.2%
△58.7 2
 
2.2%
1429.3 1
 
1.1%
9.9 1
 
1.1%
36.5 1
 
1.1%
△2.1 1
 
1.1%
7.1 1
 
1.1%
1.8 1
 
1.1%
Other values (68) 68
73.1%
2023-12-11T12:06:37.934656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 71
20.3%
1 44
12.6%
2 38
10.9%
△ 37
10.6%
5 29
8.3%
0 24
 
6.9%
7 21
 
6.0%
9 19
 
5.4%
8 18
 
5.2%
4 17
 
4.9%
Other values (2) 31
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 241
69.1%
Other Punctuation 71
 
20.3%
Other Symbol 37
 
10.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 44
18.3%
2 38
15.8%
5 29
12.0%
0 24
10.0%
7 21
8.7%
9 19
7.9%
8 18
7.5%
4 17
 
7.1%
3 16
 
6.6%
6 15
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 71
100.0%
Other Symbol
ValueCountFrequency (%)
△ 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 349
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 71
20.3%
1 44
12.6%
2 38
10.9%
△ 37
10.6%
5 29
8.3%
0 24
 
6.9%
7 21
 
6.0%
9 19
 
5.4%
8 18
 
5.2%
4 17
 
4.9%
Other values (2) 31
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 312
89.4%
Geometric Shapes 37
 
10.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 71
22.8%
1 44
14.1%
2 38
12.2%
5 29
9.3%
0 24
 
7.7%
7 21
 
6.7%
9 19
 
6.1%
8 18
 
5.8%
4 17
 
5.4%
3 16
 
5.1%
Geometric Shapes
ValueCountFrequency (%)
△ 37
100.0%

16.4
Text

Distinct77
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Memory size876.0 B
2023-12-11T12:06:38.183552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.5591398
Min length1

Characters and Unicode

Total characters331
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

Unique72 ?
Unique (%)77.4%

Sample

1st row50.7
2nd row△17.8
3rd row1.8
4th row4.4
5th row15.7
ValueCountFrequency (%)
0 13
 
14.0%
7.6 2
 
2.2%
39.5 2
 
2.2%
△100 2
 
2.2%
115.7 2
 
2.2%
46.9 1
 
1.1%
68.6 1
 
1.1%
6.2 1
 
1.1%
△7.3 1
 
1.1%
40.7 1
 
1.1%
Other values (67) 67
72.0%
2023-12-11T12:06:38.578097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 72
21.8%
1 39
11.8%
5 30
9.1%
7 26
 
7.9%
0 23
 
6.9%
△ 23
 
6.9%
6 22
 
6.6%
3 22
 
6.6%
4 21
 
6.3%
8 19
 
5.7%
Other values (2) 34
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 236
71.3%
Other Punctuation 72
 
21.8%
Other Symbol 23
 
6.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 39
16.5%
5 30
12.7%
7 26
11.0%
0 23
9.7%
6 22
9.3%
3 22
9.3%
4 21
8.9%
8 19
8.1%
9 17
7.2%
2 17
7.2%
Other Punctuation
ValueCountFrequency (%)
. 72
100.0%
Other Symbol
ValueCountFrequency (%)
△ 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 331
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 72
21.8%
1 39
11.8%
5 30
9.1%
7 26
 
7.9%
0 23
 
6.9%
△ 23
 
6.9%
6 22
 
6.6%
3 22
 
6.6%
4 21
 
6.3%
8 19
 
5.7%
Other values (2) 34
10.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 308
93.1%
Geometric Shapes 23
 
6.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 72
23.4%
1 39
12.7%
5 30
9.7%
7 26
 
8.4%
0 23
 
7.5%
6 22
 
7.1%
3 22
 
7.1%
4 21
 
6.8%
8 19
 
6.2%
9 17
 
5.5%
Geometric Shapes
ValueCountFrequency (%)
△ 23
100.0%

Unnamed: 23
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing93
Missing (%)100.0%
Memory size969.0 B

Sample

총계604.31,553.7656.01,595.8727.71,793.4627.11,736.0691.91,932.3749.62,178.8846.42,209.4890.12,282.5880.72,596.4902.33,023.02.516.4Unnamed: 23
0가이아나0.30.30.50.40.10.10.20.10.30.30.10.10.30.10.20.10.20.10.30.245.650.7<NA>
1과들루프0.20.10.40.30.20.20.30.20.20.20.40.30.30.20.30.20.40.30.30.3△19.5△17.8<NA>
2과테말라1.42.92.03.83.45.34.86.96.36.97.37.88.19.312.413.110.212.59.212.7△9.71.8<NA>
3괌3.67.93.38.84.012.74.29.04.59.45.210.05.311.46.316.06.013.47.014.017.34.4<NA>
4그리스1.14.82.06.33.217.14.732.46.134.84.012.73.16.23.24.52.44.12.34.7△4.215.7<NA>
5그린란드0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.000<NA>
6네덜란드47.199.551.5100.753.181.753.986.544.588.745.4100.251.796.141.299.753.9116.458.2152.0830.6<NA>
7네덜란드령 안틸레스0.00.10.00.00.10.20.10.20.10.20.20.10.10.10.10.10.10.10.20.182.6115.7<NA>
8노르웨이3.78.22.67.13.17.54.89.23.78.72.05.02.16.21.95.01.34.00.93.7△25△6.9<NA>
9니카라과0.20.51.21.20.81.01.21.01.21.11.51.31.00.91.00.81.11.01.31.210.824.5<NA>
총계604.31,553.7656.01,595.8727.71,793.4627.11,736.0691.91,932.3749.62,178.8846.42,209.4890.12,282.5880.72,596.4902.33,023.02.516.4Unnamed: 23
83파라과이0.61.81.03.31.73.82.03.71.83.52.35.02.45.12.24.21.43.01.12.6△21.5△15.9<NA>
84페로 제도0.60.60.00.00.00.00.00.00.00.00.00.00.10.10.00.00.00.00.00.000<NA>
85페루0.51.40.72.01.13.61.54.62.15.92.03.23.44.84.87.11.74.94.010.5129.2112.8<NA>
86포르투갈1.22.72.35.42.88.33.611.24.411.35.614.28.315.65.88.85.711.14.312.4△25.711.2<NA>
87폴란드6.714.17.611.511.813.213.317.418.324.425.531.324.433.518.028.28.920.410.725.220.323.6<NA>
88푸에르토리코1.61.21.20.91.51.21.61.31.51.21.51.22.51.91.81.52.21.70.90.8△57.5△56<NA>
89프랑스10.532.018.629.011.242.815.460.013.065.623.884.422.179.225.373.513.458.720.4100.152.270.7<NA>
90프랑스령 기아나0.00.00.00.00.00.00.00.00.10.00.10.10.10.10.10.10.10.10.20.252.847.1<NA>
91핀란드0.31.50.81.50.10.30.10.30.10.30.00.20.30.50.30.50.10.50.20.775.559.5<NA>
92헝가리3.48.74.98.33.64.63.75.13.95.05.86.54.15.04.13.92.52.92.22.6△12.1△11.6<NA>