Let’s understand how we can concatenate two or more Data Frames. A concatenation of two or more data frames can be done using pandas.concat() method. concat() in pandas works by combining Data Frames across rows or columns. We can concat two or more data frames either along rows (axis=0) or along columns (axis=1)
Step 1: Import numpy and pandas libraries.
Python3
import pandas as pd import numpy as np |
Step 2: Create two Data Frames which we will be concatenating now. For creating Data frames we will be using numpy and pandas.
Python3
df1 = pd.DataFrame(np.random.randint(25, size=(4, 4)), index=["1", "2", "3", "4"], columns=["A", "B", "C", "D"]) df2 = pd.DataFrame(np.random.randint(25, size=(6, 4)), index=["5", "6", "7", "8", "9", "10"], columns=["A", "B", "C", "D"]) df3 = pd.DataFrame(np.random.randint(25, size=(4, 4)), columns=["A", "B", "C", "D"]) df4 = pd.DataFrame(np.random.randint(25, size=(4, 4)), columns=["E", "F", "G", "H"]) display(df1, df2, df3, df4) |
Output:
Step 3: Now we need to pass the two data frames to the contact() method in the form of a list and mention in which axis you want to concat.
Python3
# concatenating df1 and df2 along rows vertical_concat = pd.concat([df1, df2], axis=0) # concatinating df3 and df4 along columns horizontal_concat = pd.concat([df3, df4], axis=1) display(vertical_concat, horizontal_concat) |
Output:
Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.
To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.
