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

Let’s discuss how to create an empty DataFrame and append rows & columns to it in Pandas n Python. There are multiple ways in which we can do this task. Here we will cover the following section:

• Creating an empty Dataframe in Pandas
• Append row to Dataframe in Pandas
• Append row to Dataframe in Pandas

Creating empty Dataframe

Python3

# import pandas library as pd
import pandas as pd

# create an Empty DataFrame object
df = pd.DataFrame()

print(df)

Output:

Empty DataFrame
Columns: []
Index: []

Append Column to Dataframe

Example 1:

Create a complete empty DataFrame without any column name or indices and then append columns in Pandas one by one to it. 

Python3

# 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:

Example 2:

This method will create a new Dataframe with a new column added to the old Dataframe using assign in Pandas.

Python3

# Import pandas package
import pandas as pd

# Define a dictionary containing Students data
data = {'Name': ['Jai', 'Princi', 'Gaurav', 'Anuj'],
    'Height': [5.1, 6.2, 5.1, 5.2],
    'Qualification': ['Msc', 'MA', 'Msc', 'Msc']}


# Convert the dictionary into DataFrame
df = pd.DataFrame(data)

# Using 'Address' as the column name and equating it to the list
df2 = df.assign(address=['Delhi', 'Bangalore', 'Chennai', 'Patna'])

# Observe the result
print(df2)

Output:

Append row to Dataframe

Example 1:

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

Python3

# 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:

Example 2:

Create an empty DataFrame with a column name and indices and then append rows one by one to it using the loc[] method. 

Python3

# 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: