Preview:
Data Analysis using numpy and pandas:

Program:
import numpy as np
x1 = np.array([[1,2,3],[4,5,6]]) 
print(x1.shape)
x2 = np.array([[1,2,3],[4,5,6]])
x2.shape = (3,2)
print(x2.size)
x11 = np.zeros((5,2), dtype = np.int)
print(x11)
x13 = np.ones([2,2], dtype=int)
x14 = np.arange(10, 20, 2)
x15 = np.arange(10, 20, 0.5)
i1 = np.array([[21,12,43],[54,25,6],[27,8,99]])
print(np.amin(i1,1))  #across rows
print(np.amin(i1,0))  #across cols
i2 = np.array([[20,50,80],[30,60,90],[40,70,100]])
print(np.percentile(i2,100))
print(np.median(i2))
i3 = np.array([[1,2,3],[3,4,5],[4,5,6]])
print(np.mean(i3))
i4 = np.array([1,2,3,4])
print(i4)
print(np.average(i4))
i5 = np.array([1,2,3,4])
print(np.var(i5))
print(np.std(i5))


O/P:
(2, 3)
6
[[0 0]
 [0 0]
 [0 0]
 [0 0]
 [0 0]]
[12  6  8]
[21  8  6]
100.0
60.0
3.6666666666666665
[1 2 3 4]
2.5
1.25
1.118033988749895



import pandas as pd   
 dict1 ={'a':1, 'b':2, 'c':3, 'd':4}   # Program to Create Data Frame with two dictionaries
dict2 ={'a':5, 'b':6, 'c':7, 'd':8, 'e':9} 
Data = {'first':dict1, 'second':dict2}
a = pd.DataFrame(Data)  
print(a)
s1 = pd.Series([1, 3, 4, 5, 6, 2, 9])   # Define series 1
s2 = pd.Series([1.1, 3.5, 4.7, 5.8, 2.9, 9.3])   # Define series 2       
s3 = pd.Series(['a', 'b', 'c', 'd', 'e'])     # Define series 3
Data1 ={'first':s1, 'second':s2, 'third':s3}  # Define Data
dfseries = pd.DataFrame(Data1)  # Create DataFrame
print(dfseries)
d1 =[[2, 3, 4], [5, 6, 7]] # Define 2d array 1
d2 =[[2, 4, 8], [1, 3, 9]] # Define 2d array 2
Data ={'first': d1, 'second': d2}  # Define Data
df2d = pd.DataFrame(Data)  # Create DataFrame
print(df2d)

O/P:
   first  second
a    1.0       5
b    2.0       6
c    3.0       7
d    4.0       8
e    NaN       9
   first  second third
0      1     1.1     a
1      3     3.5     b
2      4     4.7     c
3      5     5.8     d
4      6     2.9     e
5      2     9.3   NaN
6      9     NaN   NaN
       first     second
0  [2, 3, 4]  [2, 4, 8]
1  [5, 6, 7]  [1, 3, 9]


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