Pandas DataFrame is a 2-dimensional labeled data structure with columns of potentially different types. It is generally the most commonly used pandas object.
Pandas DataFrame can be created in multiple ways. Let’s discuss how to create a Pandas DataFrame from List of Dicts.
Code #1:
# Python code demonstrate how to create # Pandas DataFrame by lists of dicts. import pandas as pd # Initialise data to lists. data = [{ 'Geeks' : 'dataframe' , 'For' : 'using' , 'geeks' : 'list' }, { 'Geeks' : 10 , 'For' : 20 , 'geeks' : 30 }] # Creates DataFrame. df = pd.DataFrame(data) # Print the data df |
Output:
Code #2: With index
# Python code demonstrate how to create # Pandas DataFrame by lists of dicts. import pandas as pd # Initialise data to lists. data = [{ 'Geeks' : 'dataframe' , 'For' : 'using' , 'geeks' : 'list' }, { 'Geeks' : 10 , 'For' : 20 , 'geeks' : 30 }] # Creates DataFrame. df = pd.DataFrame(data, index = [ 'ind1' , 'ind2' ]) # Print the data df |
Output:
Code #3: With index
and columns
# Python code demonstrate how to create # Pandas DataFrame by lists of dicts. import pandas as pd # Initialise data to lists. data = [{ 'Geeks' : 'dataframe' , 'For' : 'using' , 'geeks' : 'list' }, { 'Geeks' : 10 , 'For' : 20 , 'geeks' : 30 }] # With two column indices, values same # as dictionary keys df1 = pd.DataFrame(data, index = [ 'ind1' , 'ind2' ], columns = [ 'Geeks' , 'For' ]) # With two column indices with # one index with other name df2 = pd.DataFrame(data, index = [ 'indx' , 'indy' ]) # print for first data frame print (df1, "\n" ) # Print for second DataFrame. print (df2) |
Output:
Last Updated on August 28, 2021 by admin