numpy: process the data& array

pandas：data analysis and explore

matplotlib:show with mat &plot 

scipy: matrix integration

statsmodels: statistic

Gensim:tex mining

sklearn、keras:computing learning’

 

numpy:

import numpy as nn a=nn.array(["element1","element2","1","8a"]) a.sort() b=nn.array([["key1","key2"],["1","2","0"],["a","2","0b"]]) b.sort() print(a,b) a1=a[0:4] a2=a[:3] a3=a[1:] b1=b.max() print(a[0],a1,a2,a3) print(b[0][1],b1) pandas:

import pandas as p c=p.Series([2,2,3,4,5,3]) print(c) c1=p.Series([3,4,5,6,7],index=["one","two","three","four","five"]) print(c1) d=p.DataFrame([["a","b","c",2],[2,3,1,2,3,4,6]],columns=["one","two","three","four","five","six","seven"]) print(d) d1=p.DataFrame({
      "one":3,     "two":[3,4,5],     "three":list(str(233)) }) print(d1) d2=d.head()#first five lines d3=d.head(2) d4=d.tail()#last five lines d5=d.tail(3) d6=d.describe() d7=d.T# trans line to column print(d2,d3,d4,d5,d6,d7)

['1' '8a' 'element1' 'element2'] [list(['1', '2', '0']) list(['a', '2', '0b']) list(['key1', 'key2'])]

1 ['1' '8a' 'element1' 'element2'] ['1' '8a' 'element1'] ['8a' 'element1' 'element2']

2 ['key1', 'key2']

0 2

1 2

2 3

3 4

4 5

5 3

dtype: int64

one 3

two 4

three 5

four 6

five 7

dtype: int64

one two three four five six seven

0 a b c 2 NaN NaN NaN

1 2 3 1 2 3.0 4.0 6.0

one three two

0 3 2 3

1 3 3 4

2 3 3 5

one two three four five six seven

0 a b c 2 NaN NaN NaN

1 2 3 1 2 3.0 4.0 6.0 one two three four five six seven

0 a b c 2 NaN NaN NaN

1 2 3 1 2 3.0 4.0 6.0 one two three four five six seven

0 a b c 2 NaN NaN NaN

1 2 3 1 2 3.0 4.0 6.0 one two three four five six seven

0 a b c 2 NaN NaN NaN

1 2 3 1 2 3.0 4.0 6.0 four five six seven

count 2.0 1.0 1.0 1.0

mean 2.0 3.0 4.0 6.0

std 0.0 NaN NaN NaN

min 2.0 3.0 4.0 6.0

25% 2.0 3.0 4.0 6.0

50% 2.0 3.0 4.0 6.0

75% 2.0 3.0 4.0 6.0

max 2.0 3.0 4.0 6.0 0 1

one a 2

two b 3

three c 1

four 2 2

five NaN 3

six NaN 4

seven NaN 6