In this article, we will see how to stack Multiple pandas dataframe. Stacking means appending the dataframe rows to the second dataframe and so on. If there are 4 dataframes, then after stacking the result will be a single dataframe with an order of dataframe1,dataframe2,dataframe3,dataframe4
Method 1: Using concat() method
This method will stack the rows of the pandas dataframes in the order they give.
Syntax: pandas.concat([first_dataframe,second_dataframe,third_dataframe,………….,last_dataframe], ignore_index=True,axis)
Parameters:
- dataframes are the input dataframes to be stacked
- ignore_index is used to ignore the index values of the input dataframes
- axis=0 specifies vertical stacking
- axis=1 specifies horizontal stacking
Note: If the ignore_index parameter is not set to true means then it will take the given indexes which lead to the wrong stacking of the dataframes
Example 1: Python program to stack two dataframes vertically
Python3
# import pandas moduleimport pandas as pd# create first dataframedata1 = pd.DataFrame({'name': ['sravan', 'bobby', 'ojaswi', 'rohith', 'gnanesh'], 'subjects': ['java', 'python', 'php', 'java', '.NET']})# create second dataframedata2 = pd.DataFrame({'name': ['gopi', 'harsha', 'ravi', 'uma', 'deepika'], 'subjects': ['c/c++', 'html/css', 'dbms', 'java', 'IOT']})# stack the two DataFramespd.concat([data1, data2], ignore_index=True, axis=0) |
Output:
Example 2: Python code to stack multiple dataframes vertically
Python3
# import pandas moduleimport pandas as pd# create first dataframedata1 = pd.DataFrame({'name': ['sravan', 'bobby', 'ojaswi', 'rohith', 'gnanesh'], 'subjects': ['java', 'python', 'php', 'java', '.NET']})# create second dataframedata2 = pd.DataFrame({'name': ['gopi', 'harsha', 'ravi', 'uma', 'deepika'], 'subjects': ['c/c++', 'html/css', 'dbms', 'java', 'IOT']})# create third dataframedata3 = pd.DataFrame( {'name': ['ragini', 'latha'], 'subjects': ['java', 'python']})# create fourth dataframedata4 = pd.DataFrame( {'name': ['gowri', 'jyothika'], 'subjects': ['java', 'IOT']})# stack the four DataFramespd.concat([data1, data2, data3, data4], ignore_index=True,axis=0) |
Output:
Example 3: Python program to stack multiple dataframes horizontally
Python3
# import pandas moduleimport pandas as pd# create first dataframedata1 = pd.DataFrame({'name': ['sravan', 'bobby', 'ojaswi', 'rohith', 'gnanesh'], 'subjects': ['java', 'python', 'php', 'java', '.NET']})# create second dataframedata2 = pd.DataFrame({'name': ['gopi', 'harsha', 'ravi', 'uma', 'deepika'], 'subjects': ['c/c++', 'html/css', 'dbms', 'java', 'IOT']})# create third dataframedata3 = pd.DataFrame( {'name': ['ragini', 'latha'], 'subjects': ['java', 'python']})# create fourth dataframedata4 = pd.DataFrame( {'name': ['gowri', 'jyothika'], 'subjects': ['java', 'IOT']})# stack the four DataFrames horizontallypd.concat([data1, data2, data3, data4], axis=1, ignore_index=True) |
Output:
Method 2: Using append() method
append() method is used to append the dataframes after the given dataframe.
Syntax: first_dataframe.append([second_dataframe,…,last_dataframe],ignore_index=True)
Example: Python program to stack multiple dataframes using append() method
Python3
# import pandas moduleimport pandas as pd# create first dataframedata1 = pd.DataFrame({'name': ['sravan', 'bobby', 'ojaswi', 'rohith', 'gnanesh'], 'subjects': ['java', 'python', 'php', 'java', '.NET']})# create second dataframedata2 = pd.DataFrame({'name': ['gopi', 'harsha', 'ravi', 'uma', 'deepika'], 'subjects': [ 'c/c++', 'html/css', 'dbms', 'java', 'IOT']})# create third dataframedata3 = pd.DataFrame( {'name': ['ragini', 'latha'], 'subjects': ['java', 'python']})# create fourth dataframedata4 = pd.DataFrame( {'name': ['gowri', 'jyothika'], 'subjects': ['java', 'IOT']})# stack the four DataFrames using append()data1.append([data2, data3, data4], ignore_index=True) |
Output:
