There are different ways of creating a pandas data frame:
Creating using list
Creating using dictionary
Using arrays
Using zip()
Creating using list without index:
# Import pandas library import pandas as pd # initialize list of lists data = [['A', 18, 'M'], ['B', 14, 'F'], ['C', 13, 'M']] df = pd.DataFrame(data, columns = ['Name', 'Age', 'Gender']) print(df)
Output:
Name Age Gender 0 A 18 M 1 B 14 F 2 C 13 M
Creating using list with index:
# Import pandas library import pandas as pd # initialize list of lists data = [['A', 18, 'M'], ['B', 14, 'F'], ['C', 13, 'M']] df = pd.DataFrame(data, columns = ['Name', 'Age', 'Gender'], index = ['row1', 'row2', 'row3']) print(df)
Output:
Name Age Gender row1 A 18 M row2 B 14 F row3 C 13 M
Creating using dictionary:
Creating the data frame using the dictionary, all the array must be of the same length.
import pandas as pd # intialise data of lists. data = {'Job':['sofware Eng', 'IT consultant', 'Teacher'], 'Age':[27, 29, 30]} # Create DataFrame df = pd.DataFrame(data) # Print the output. print(df)
Output:
Job Age 0 sofware Eng 27 1 IT consultant 29 2 Teacher 30
Using arrays:
import pandas as pd # initialise data of lists. data = {'Name':['A', 'B', 'C', 'D'], 'Grade':['A+','B+', 'A', 'C']} # Creates pandas DataFrame. df = pd.DataFrame(data, index =['1', '2', '3', '4']) print(df)
Output:
Name Grade 1 A A+ 2 B B+ 3 C A 4 D C
Using zip()
In this merge two lists using list(zip()) function and use.
#using dic import pandas as pd # List1 Name = ['A', 'B', 'C', 'D'] # List2 Age = [22, 18, 32, 27] Gender = ['M', 'F', 'M', 'M'] # and merge them by using zip(). list_tuple = list(zip(Name, Age, Gender)) # Assign data to tuples. list_tuple #convert list into the pandas df = pd.DataFrame(list_tuple, columns = ['Name', 'Age', 'Gender']) # Print data. print(df)
Output:
Name Age Gender 0 A 22 M 1 B 18 F 2 C 32 M 3 D 27 M
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