CS计算机代考程序代写 Data_Structures

Data_Structures

In [1]:

import pandas as pd
import numpy as np

myseries = pd.Series([4, 7, -5, 3])
myseries

Out[1]:

0 4
1 7
2 -5
3 3
dtype: int64

In [3]:

myseries2 = pd.Series([4, 7, -5, 3], index=[‘x’, ‘b’, ‘a’, ‘c’])
myseries2

Out[3]:

x 4
b 7
a -5
c 3
dtype: int64

In [4]:

myseries.values

Out[4]:

array([ 4, 7, -5, 3], dtype=int64)

In [6]:

myseries2.index

Out[6]:

Index([‘x’, ‘b’, ‘a’, ‘c’], dtype=’object’)

In [9]:

myseries2[‘b’]

Out[9]:

7

In [10]:

myseries2[‘a’]

frame= { ‘theseries’: myseries, ‘ultimate series’: myseries2 }

dd= pd.DataFrame(frame)
dd

Out[10]:

theseries ultimate series
0 4.0 NaN
1 7.0 NaN
2 -5.0 NaN
3 3.0 NaN
a NaN -5.0
b NaN 7.0
c NaN 3.0
x NaN 4.0

In [12]:

raw_data = {‘first_name’: [‘Jason’, ‘Molly’, ‘Tina’, ‘Jake’, ‘Amy’],
‘last_name’: [‘Miller’, ‘Jacobson’, “.”, ‘Milner’, ‘Cooze’],
‘age’: [42, 52, 36, 24, 73],
‘preTestScore’: [4, 24, 31, “.”, “.”],
‘postTestScore’: [“25,000”, “94,000”, 57, 62, 70]}
df = pd.DataFrame(raw_data, columns = [‘first_name’, ‘last_name’, ‘age’, ‘preTestScore’, ‘postTestScore’])
df

Out[12]:

first_name last_name age preTestScore postTestScore
0 Jason Miller 42 4 25,000
1 Molly Jacobson 52 24 94,000
2 Tina . 36 31 57
3 Jake Milner 24 . 62
4 Amy Cooze 73 . 70

In [13]:

df.to_csv(‘exampledf.csv’)

In [ ]: