Pandas is a package in Python that is popular for its comprehensive data manipulation capabilities. It is fittingly named after panel data, which is referenced as a multidimensional dataset.
Pandas provides functionality to efficiently and effectively manipulate complex data structures, such as pandas dataframes. It is essential that data analysts and data scientists learn how to perform common tasks on a pandas DataFrame, such as moving columns to the front.
In this article, we will guide you through two methods to move one or multiple columns to the front of a pandas DataFrame. Method 1: Move One Column to the Front
Moving a single column to the front of a pandas DataFrame requires the use of the pandas insert function.
This function takes three arguments: the index location where the new column should be inserted, the new columns name, and the values of the new column. In this case, we want to insert the column in the first position, so we specify the index location as 0.
We also want to move the assists column to the front, so we specify its name as the column we want to move. The values in the column do not matter as they will be automatically populated from the other columns in the DataFrame.
“`python
import pandas as pd
# Create DataFrame
basketball_df = pd.DataFrame({
‘players’: [‘Kobe Bryant’, ‘LeBron James’, ‘Michael Jordan’, ‘Magic Johnson’],
‘points’: [33, 28, 30, 19],
‘rebounds’: [7, 8, 6, 11],
‘assists’: [8, 11, 5, 14]
})
# Move ‘assists’ column to front
basketball_df.insert(0, ‘assists’, basketball_df.pop(‘assists’))
# Print DataFrame
print(basketball_df)
“`
Output:
“`
assists players points rebounds
0 8 Kobe Bryant 33 7
1 11 LeBron James 28 8
2 5 Michael Jordan 30 6
3 14 Magic Johnson 19 11
“`
We can see that the assists column has been successfully moved to the front with the help of the insert function. Method 2: Move Multiple Columns to the Front
To move multiple columns to the front of a pandas DataFrame, we can use the pandas reindex function.
This function allows us to either move individual columns or blocks of columns within the DataFrame. We want to move both the points and rebounds columns to the front, so we create a list of all the column names in the desired order.
We then use this list to reindex the pandas DataFrame. “`python
import pandas as pd
# Create DataFrame
basketball_df = pd.DataFrame({
‘players’: [‘Kobe Bryant’, ‘LeBron James’, ‘Michael Jordan’, ‘Magic Johnson’],
‘points’: [33, 28, 30, 19],
‘rebounds’: [7, 8, 6, 11],
‘assists’: [8, 11, 5, 14]
})
# Move ‘points’ and ‘rebounds’ columns to front
basketball_df = basketball_df.reindex(columns=[‘points’, ‘rebounds’, ‘players’, ‘assists’])
# Print DataFrame
print(basketball_df)
“`
Output:
“`
points rebounds players assists
0 33 7 Kobe Bryant 8
1 28 8 LeBron James 11
2 30 6 Michael Jordan 5
3 19 11 Magic Johnson 14
“`
We can see that the points and rebounds columns have been successfully moved to the front of the DataFrame.
Additional Resources
Now that we have covered two methods of moving columns to the front of a pandas DataFrame, it is important to note that there are countless other common tasks that pandas can help with. Pandas is a vast library and learning it does require a certain level of familiarity with Python.
Although we have provided a brief overview of how to move columns in this article, it is essential that data analysts and data scientists learn other fundamental Pandas functions and methods. Tutorials and documentation found online can prove to be helpful in increasing your Pandas knowledge and providing you with the necessary toolbox to make confident and efficient decisions while working with data using Pandas.
Conclusion
In conclusion, pandas is a package in Python that is popular for its ability to manipulate complex data structures, such as pandas dataframes. In this article, we shared two methods on how to move columns to the front of a pandas dataframe.
The insert() function helps to move one column to the front, whereas the reindex() function assists with moving multiple columns in the desired order to the front of the DataFrame. With the numerous functions and methods offered by Pandas, it is essential to continually learn and expand your knowledge to comfortably and effectively proceed with your data analysis journey.
Pandas is a popular Python package that offers comprehensive data manipulation capabilities, especially with pandas dataframes. In this article, we have discussed two methods of moving columns to the front of a pandas dataframe: move one column using the insert() function, and move multiple columns using the reindex() function.
It is important for data analysts and scientists to learn about these common tasks and other fundamental functions and methods offered by Pandas. We recommend utilizing tutorials and documentation available online to explore and expand your Pandas knowledge and toolbox.
By mastering these skills, you can confidently and efficiently manipulate complex data structures, such as pandas dataframes.