in this pandas tutorials, We’ll learn how to Concatenate two or more Data Frames. The concat() method help to combines Data Frames across rows or columns in pandas.
The Pandas DataFrame is a structure that contains two-dimensional data and its corresponding labels. DataFrames are widely used in data science, machine learning, scientific computing, and many other data-intensive fields.
As we know, The DataFrames are similar to tables or spreadsheets and part of the Python and NumPy ecosystems. The DataFrames are faster, easier to use, and more powerful than tables or spreadsheets.
Pandas concat two dataframes
Let’s concatenate two dataframe using concat() method.
import pandas as pd import numpy as np dataframe1 = pd.DataFrame(np.random.randint(100, size=(3, 3)), index=["1", "2", "3"], columns=["eng", "fr", "de"]) dataframe2 = pd.DataFrame(np.random.randint(100, size=(3, 3)), index=["1", "2", "3"], columns=["af", "hi", "ar"]) print(dataframe1); print(dataframe2); # concatenating dataframe1 and dataframe2 along columns horizontal_concat = pd.concat([dataframe1, dataframe2], axis=1) #Horizontall display(horizontal_concat) dataframe3 = pd.DataFrame(np.random.randint(100, size=(2, 2)), index=["1", "2"], columns=["eng", "fr"]) dataframe4 = pd.DataFrame(np.random.randint(100, size=(2, 2)), index=["1", "2"], columns=["eng", "fr"]) # concatenating dataframe3 and dataframe4 along rows vertical_concat = pd.concat([dataframe3, dataframe4], axis=0) #vertical display(vertical_concat)
Output:
eng fr de 1 3 91 44 2 95 86 26 3 43 40 60 af hi ar 1 91 9 21 2 3 44 14 3 10 48 52
Horizontal concatenate
eng fr de af hi ar 1 10 71 58 35 73 64 2 46 11 71 27 38 57 3 13 58 15 5 11 67
Vertical concatenate
eng fr 1 19 30 2 18 70 3 40 95 4 71 87
Step 1: import pandas and NumPy module.
Step 2: define dataframe 1 and dataframe 2.
Step 3: Merging two dataframe(dataframe1, dataframe2) using concat() method.
Step 4: Define dataframe3 and dataframe4.
Step 5: Merging two dataframe(dataframe3, dataframe4) using concat() method.
