Course Content
Unveiling the Power of Data Manipulation with Pandas
Unveiling the Power of Data Manipulation with Pandas
Import and Export Files
You may be wondering: Yes, working with DataFrames is engaging, but what if I have a dataset of 1,000,000 rows? I can't manually input every single row.
For this reason, pandas offers several methods to read and write data from and to various file formats, such as CSV, Excel, and JSON. These functions come with many options and parameters that allow you to customize how data is read and written.
P.S. These are just a few of the methods available. Did you know that you can also run SQL queries via pd.read_sql()?
Task
- Use the appropriate function to read the CSV file into a DataFrame.
- Use the appropriate function to export the DataFrame to an Excel file.
- Display the first 6 rows of the
dataDataFrame.
Switch to desktop for real-world practiceContinue from where you are using one of the options belowThanks for your feedback!
You may be wondering: Yes, working with DataFrames is engaging, but what if I have a dataset of 1,000,000 rows? I can't manually input every single row.
For this reason, pandas offers several methods to read and write data from and to various file formats, such as CSV, Excel, and JSON. These functions come with many options and parameters that allow you to customize how data is read and written.
P.S. These are just a few of the methods available. Did you know that you can also run SQL queries via pd.read_sql()?
Task
- Use the appropriate function to read the CSV file into a DataFrame.
- Use the appropriate function to export the DataFrame to an Excel file.
- Display the first 6 rows of the
dataDataFrame.
Switch to desktop for real-world practiceContinue from where you are using one of the options below