Page 456 - AI Ver 3.0 class 10_Flipbook
P. 456
tail(n) Returns the last n
[1]: import pandas as pd
members of the series. friends = pd.Series(["Rohan","Susan","James",
If n is not specified then "Riya","Sumit","Abhinav", "vihaan"],
index=[11,22,33,44,55,66,77])
by default the last five
print(friends.tail())
members are displayed.
33 James
44 Riya
55 Sumit
66 Abhinav
77 vihaan
dtype: object
count() It counts the total non
[1]: import pandas as pd
NaN values in a series friends = pd.Series(["Rohan","Susan","James","Riya",
"Sumit","Abhinav","vihaan"],
index=[11,22,33,44,55,66,77])
print(friends.count())
7
DataFrames
A DataFrame is a two-dimensional labelled heterogeneous data structure that contains rows and columns. It has
both a row and column index. The data arranged in the form of a row and a column resembles the data arranged
in a tabular form in a table of a database.
Creating a DataFrame
Different ways to create a DataFrame are as follows:
• Creating an empty DataFrame
[1]: import pandas as pd
Emp = pd. DataFrame ()
print(Emp)
Empty DataFrame
Columns: []
Index: []
• Creating a DataFrame from Numpy Array
[1]: import numpy as np
import pandas as pd
a1 = np.array([10,20,30])
a2 = np.array([11,22,33])
f1=pd.DataFrame(a1)
f2=pd.DataFrame([a1,a2])
print(f1)
print(f2)
0
0 10
1 20
2 30
0 1 2
0 10 20 30
1 11 22 33
454 Touchpad Artificial Intelligence (Ver. 3.0)-X

