How to Use the pandas Library in Python Programming (3 Examples)

This page illustrates how to apply the functions of the pandas library in the Python programming language.

Setting up the Examples

import pandas as pd                                # Load pandas library
my_df = pd.DataFrame({"A":range(3, 12),            # Construct pandas DataFrame in Python
                     "B":["a", "x", "b", "y", "y", "c", "y", "d", "x"],
                     "C":range(1, 10)})
print(my_df)
#     A  B  C
# 0   3  a  1
# 1   4  x  2
# 2   5  b  3
# 3   6  y  4
# 4   7  y  5
# 5   8  c  6
# 6   9  y  7
# 7  10  d  8
# 8  11  x  9

Example 1: Appending New Variable to pandas DataFrame in Python

D = ["d", "h", "h", "a", "h", "d", "a", "d", "d"]  # Constructing new column
print(D)
# ['d', 'h', 'h', 'a', 'h', 'd', 'a', 'd', 'd']
my_df1 = my_df.assign(D = D)                       # Adding new column to DataFrame
print(my_df1)
#     A  B  C  D
# 0   3  a  1  d
# 1   4  x  2  h
# 2   5  b  3  h
# 3   6  y  4  a
# 4   7  y  5  h
# 5   8  c  6  d
# 6   9  y  7  a
# 7  10  d  8  d
# 8  11  x  9  d

Example 2: Removing Rows of pandas DataFrame in Python

my_df2 = my_df[my_df.B != "y"]                     # Dropping rows of DataFrame
print(my_df2)
#     A  B  C
# 0   3  a  1
# 1   4  x  2
# 2   5  b  3
# 5   8  c  6
# 7  10  d  8
# 8  11  x  9

Example 3: Computing Mean of pandas DataFrame Variable in Python

my_df_mean = my_df["C"].mean()                     # Calculate mean of column
print(my_df_mean)
# 5.0

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