How to create an empty DataFrame and append rows & columns to it in Pandas?...
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How to create an empty DataFrame and append rows & columns to it in Pandas?
Last Updated: 02-07-2020Let’s discuss how to create an empty DataFrame and append rows & columns to it in Pandas. There are multiple ways in which we can do this task.
Method #1: Create a complete empty DataFrame without any column name or indices and then appending columns one by one to it.
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# import pandas library as pd import pandas as pd # create an Empty DataFrame object df = pd.DataFrame() print(df) # append columns to an empty DataFrame df['Name'] = ['Ankit', 'Ankita', 'Yashvardhan'] df['Articles'] = [97, 600, 200] df['Improved'] = [2200, 75, 100] df Output:
Method #2: Create an empty DataFrame with columns name only then appending rows one by one to it using append() method.
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# import pandas library as pd import pandas as pd # create an Empty DataFrame # object With column names only df = pd.DataFrame(columns = ['Name', 'Articles', 'Improved']) print(df) # append rows to an empty DataFrame df = df.append({'Name' : 'Ankit', 'Articles' : 97, 'Improved' : 2200}, ignore_index = True) df = df.append({'Name' : 'Aishwary', 'Articles' : 30, 'Improved' : 50}, ignore_index = True) df = df.append({'Name' : 'yash', 'Articles' : 17, 'Improved' : 220}, ignore_index = True) df Output:
Method #3: Create an empty DataFrame with a column name and indices and then appending rows one by one to it using loc[] method.
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# import pandas library as pd import pandas as pd # create an Empty DataFrame object With # column names and indices df = pd.DataFrame(columns = ['Name', 'Articles', 'Improved'], index = ['a', 'b', 'c']) print("Empty DataFrame With NaN values : \n\n", df) # adding rows to an empty # dataframe at existing index df.loc['a'] = ['Ankita', 50, 100] df.loc['b'] = ['Ankit', 60, 120] df.loc['c'] = ['Harsh', 30, 60] df Output:
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first_page Loop or Iterate over all or certain columns of a dataframe in Python-Pandas last_page Get the number of rows and number of columns in Pandas Dataframe
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