How to drop unnamed column in pandas

How to drop unnamed column in pandas ? 5 Steps Only

An unnamed column in pandas comes when you are reading CSV file using it. Sometimes we require to drop columns in the dataset that we not required. It not only saves memory but also helpful in analyzing the data efficiently. One approach is removing the NaN value or some other value. The second approach is to drop unnamed columns in pandas. In this entire tutorial, I will discuss how to easily remove unnamed column error while reading a CSV file.

Steps by Step to drop unnamed column in pandas

Step1: Import all the necessary libraries.

The first and basic step is to import python libraries. Here in our example, We are using only pandas. So let’s import them. However, if you have not installed pandas in your system, you can read How to install pandas in the dedicated tutorial.

import pandas as pd

Step 2: Create a DataFrame.

Now let’s create a Dataframe for demonstrating purpose.  You can do it by using pandas.Dataframe() method.

df = pd.DataFrame('x', index=range(5), columns=list('abc'))

The following argument I am passing. It is done only for creation purposes.

x: It allows us to put value in the entire row as “x”.

index: It will create an index column. In our example rows from 0 to 4.

columns: Name of the columns.

Output

Sample DataFrame Creation for Unnamed Column Example
Sample DataFrame Creation for Unnamed Column Example

Step 3: Export or Save it as CSV File.

The next step is to save this dataframe as CSV. Some readers might have asked, Why I am doing so? The answer is simple. I want to read the CSV file that outputs the dataframe with the unnamed column.  You can export any dataframe using the to_csv() method.

df.to_csv('demo_file.csv')

It will save dataframe with the filename “demo_file.csv

Step 4: Read the Exported CSV File

After exporting the dataframe as a CSV file, let’s now read it. You can read the CSV file using the read_csv() method.

Execute the following code to read the dataframe.

df2= pd.read_csv("demo_file.csv")

If you output the dataframe you will also get the unnamed column error like below.

Unnamed Column Error
Unnamed Column Error

And if you also print the columns using df2.columns you will see the unnamed columns also.

Index(['Unnamed: 0', 'a', 'b', 'c'], dtype='object')

Step 5: Follow the following method to drop unnamed column in pandas

Method 1: Use the index = False argument

In this method, you have to not directly output the dataframe to the CSV file. But you should also include index = False argument. It will automatically drop the unnamed column in pandas. You will get the output as below.

Exporting the Dataframe to CSV with index set as False
Exporting the Dataframe to CSV with index set as False

Method 2: Filtering the Unnamed Column

The second method to drop unnamed column is filtering the dataframe using str.match. It can be also known as continual filtering.

Execute the code below to drop the column.

df2.columns.str.match("Unnamed")
df2.loc[:,~df2.columns.str.match("Unnamed")]

You will get the following output.

Dropping the Unnamed Column by Filtering the Unamed Column
Dropping the Unnamed Column by Filtering the Unamed Column

Method 3: Drop the Unnamed Column in Pandas using drop() method

In this example, you will use the drop() method. You have to pass the “Unnamed: 0” as its argument.  Execute the code below.

df2.drop("Unnamed: 0",axis=1)

You will get the following output.

Drop the Unnamed Column in Pandas using drop() method
Drop the Unnamed Column in Pandas using drop() method

Conclusion

These are the method to remove the issue of the drop unnamed column. You should note that while exporting the dataset in form of CSV you should always include index = False. It will remove the error automatically. However, if you have already had dataframe that output this column then you can try other methods.

Hope this tutorial has solved your issue. If you have any queries then you can contact us for more information.

Source:

Pandas Read CSV Method

Pandas Drop Method

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