The Pandas library in Python provides all sorts of great tools for data analysis needs. There are often situations where you need to add an empty column to an existing DataFrame. In this article, we will discuss some easy methods to add an empty column to a Pandas Dataframe.
5 Methods to Add Empty Column to DataFrame
Adding an empty column in a Pandas DataFrame is useful when you want to populate the column with values later on or initialize it with specific criteria. You might add an empty column to hold values that will be filled based on certain conditions later in your analysis, or if you want to concatenate DataFrames, this can ensure proper alignment during the merging process.
Following are some of the best methods to add an empty column to a DataFrame:
1) Using the Assignment Operator
The most used method to add an empty column to a DataFrame is by using the assignment operator. This method allows you to assign empty values, such as empty strings, to newly created columns.
Let the example below:
import pandas as pd
# Create a sample DataFrame
df = pd.DataFrame({'Column1': [1, 2, 3],
'Column2': ['A', 'B', 'C']})
# Display the original DataFrame
print('Original DataFrame:\n', df)
# Add an empty column named 'Column3'
df['Column3'] = ''
# Display the new DataFrame
print('New DataFrame:\n', df)Output:
Original DataFrame:
Column1 Column2
0 1 A
1 2 B
2 3 C
New DataFrame:
Column1 Column2 Column3
0 1 A
1 2 B
2 3 C
2) Using np.nan Values
Another technique that we can use to add an empty column is by using np.nan values of the NumPy library. The np.nan represents a missing or undefined value in a DataFrame.
The following code shows how to do it:
import pandas as pd
import numpy as np
# Create a sample DataFrame
df = pd.DataFrame({'Column1': [1, 2, 3],
'Column2': ['A', 'B', 'C']})
# Display the original DataFrame
print('Original DataFrame:\n', df)
# Add an empty column named 'Column3' with np.nan values
df['Column3'] = np.nan
# Display the new DataFrame
print('New DataFrame:\n', df)Output:
Original DataFrame:
Column1 Column2
0 1 A
1 2 B
2 3 C
New DataFrame:
Column1 Column2 Column3
0 1 A NaN
1 2 B NaN
2 3 C NaN
3) Using None Values
You can also add an empty column to a DataFrame by using None values. None represents a missing or undefined value in Python.
Here is an example for this method:
import pandas as pd
# Create a sample DataFrame
df = pd.DataFrame({'Column1': [1, 2, 3],
'Column2': ['A', 'B', 'C']})
# Display the original DataFrame
print('Original DataFrame:\n', df)
# Add an empty column named 'Column3' with None values
df['Column3'] = None
# Display the new DataFrame
print('New DataFrame:\n', df)Output:
Original DataFrame:
Column1 Column2
0 1 A
1 2 B
2 3 C
New DataFrame:
Column1 Column2 Column3
0 1 A None
1 2 B None
2 3 C None
4) Using .reindex()
We can also use the reindex() method provided by Pandas library as well. This method allows you to modify the column index of a DataFrame and add new columns with NaN values.
Let’s see an example:
import pandas as pd
# Create a sample DataFrame
df = pd.DataFrame({'Column1': [1, 2, 3],
'Column2': ['A', 'B', 'C']})
# Display the original DataFrame
print('Original DataFrame:\n', df)
# Add empty columns 'Column3' and 'Column4' using reindex()
df = df.reindex(columns=df.columns.tolist() + ['Column3', 'Column4'])
# Display the new DataFrame
print('New DataFrame:\n', df)Output:
Original DataFrame:
Column1 Column2
0 1 A
1 2 B
2 3 C
New DataFrame:
Column1 Column2 Column3 Column4
0 1 A NaN NaN
1 2 B NaN NaN
2 3 C NaN NaN
5) Using .insert()
Finally, you can also use insert() method to do the job. It allows you to insert a new column at a specific position in the DataFrame.
The following code shows how to do it:
import pandas as pd
# Create a sample DataFrame
df = pd.DataFrame({'Column1': [1, 2, 3],
'Column2': ['A', 'B', 'C']})
# Display the original DataFrame
print('Original DataFrame:\n', df)
# Insert an empty column named 'Column3' at index 1
df.insert(1, 'Column3', '')
# Display the new DataFrame
print('New DataFrame:\n', df)Output:
Original DataFrame:
Column1 Column2
0 1 A
1 2 B
2 3 C
New DataFrame:
Column1 Column3 Column2
0 1 A
1 2 B
2 3 C
The next thing that should be based on your journey is how to rename a column in Pandas.
Conclusion
In this article, we learned the various methods to add an empty column to a DataFrame in Pandas. We learned about using the assignment operator, np.nan values, None values, Dataframe.reindex(), and Dataframe.insert() for this purpose. By understanding these methods, we added some more skills for data analysis.
