How to create an empty Pandas DataFrame and append rows & columns?



Let’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.

# 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:



python-pandas-empty-dataframe-1

Method #2: Create an empty DataFrame with columns name only then appending rows one by one to it using append() method.

# 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:

python-empty-dataframe


Method #3: Create an empty DataFrame with a column name and indices and then appending rows one by one to it using loc[] method.

# 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:

python-pandas-empty-dataframe

Last Updated on October 8, 2021 by admin

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