Question

Question #1 Please specify he output of the following code (2.4)
# import the pandas library and aliasing as pd
import pandas as pd
import numpy as np

df = pd.DataFrame(np.random.randn(8, 4),
index = ['a','b','c','d','e','f','g','h'], columns = ['A', 'B', 'C', 'D'])

# for getting values with a boolean array
print df.loc['a']>0

Question #2 Please specify the output of the following code (2.2)

import pandas as pd
import numpy as np

df = pd.DataFrame(np.random.randn(5, 3), index=['a', 'c', 'e', 'f',
'h'],columns=['one', 'two', 'three'])

df = df.reindex(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'])
print df.dropna(axis=1)

Question #3 Given the following temp.csv (2.1)

S.No,Name,Age,City,Salary
1,Tom,28,Toronto,20000
2,Lee,32,HongKong,3000
3,Steven,43,Bay Area,8300
4,Ram,38,Hyderabad,3900

Please specify what is the output of the following code:

import pandas as pd 

df=pd.read_csv("temp.csv",names=['a','b','c','d','e'],header=0)
print df

Question 4 Please describe what the following code is doing (2.3)

import pandas as pd
import numpy as np

df = pd.DataFrame(np.random.randn(10, 4),
      index = pd.date_range('1/1/2000', periods=10),
      columns = ['A', 'B', 'C', 'D'])
print df
r = df.rolling(window=3,min_periods=1)
print r['A'].aggregate(np.sum)

Answer 1

The Solution for 2.4 is: A,B,C,D with random True or False as follows:

=========================RUN-1================

A False
B False
C True
D True
Name: a, dtype: bool

==========================RUN-2=================
A False
B False
C False
D True
Name: a, dtype: bool

==================================================

solution for 2.2

Empty DataFrame
Columns: []
Index: [a, b, c, d, e, f, g, h]

solution for 2.1

header =0 will remove the header of the csv file

a,b,c,d,e column names are used.

SOLUTION FOR 2.3 is:

It will take the date and divide the date in range 1/1/2000 with columns A,B,C,D.

Finally, it sums the A column values and prints as shown in the image above.