10 Pandas Methods That Helped Me Replace Microsoft Excel with Python

10 Pandas Methods That Helped Me Replace Microsoft Excel with Python

How you can use these pandas methods to transition from Microsoft Excel to Python, saving you serious time and sanity.

1. Import an Excel file

This reads your Excel file into a pandas dataframe (the python equivalent of the tabular structure you’re used to). You’ll want to reuse this dataframe, so we’ll save it to the variable df.

df = pd.read_excel(some_file_path)

2. View your new dataframe

It might seem a bit strange at first that you’re not viewing every single row of data like in an Excel file. Here’s how to view the first five records — you can specify this value inside the parentheses, it’s default is just five.


3. Count rows

It’s usually helpful to know how many rows you’re working with, so to get this you can call the count method.


4. Basic descriptive statistics

With one line of code you’re able to get the min, max and mean of all columns within your dataframe — hopefully you’re starting to be sold using Pandas already…


5. Replace null values

This one is fairly self explanatory, to replace all null values (these appear as NaN -not a number- within a dataframe) with a zero.


You can take this one step further by forward filling, or backwards filling the value with that above or below that particular row.


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