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PANDAS PERMUTE COLUMNS HOW TO

Let’s take a quick look at why using the dot operator is often not recommended (while it’s easier to type). # print(df.Name) (This returns the same value) Let’s see how we can do this by accessing the 'Name' column: # Accessing a Single Column by Its Name

Using square-brackets to access the column.

Using dot notation to access the column.

Pandas makes it easy to select a single column, using its name. This often has the added benefit of using less memory on your computer (when removing columns you don’t need), as well as reducing the amount of columns you need to keep track of mentally. In this case, you’ll want to select out a number of columns. In many cases, you’ll run into datasets that have many columns – most of which are not needed for your analysis. The data you work with in lots of tutorials has very clean data with a limited number of columns. For example, the column with the name 'Random_C' has the index position of -1. For example, the column with the name 'Age' has the index position of 1.Īs with other indexed objects in Python, we can also access columns using their negative index. Each of the columns has a name and an index.

PANDAS PERMUTE COLUMNS HOW TO

We then loaded a DataFrame using the pd.read_csv() function.īefore diving into how to select columns in a Pandas DataFrame, let’s take a look at what makes up a DataFrame.Ī DataFrame has both rows and columns.# Name Age Height Score Random_A Random_B Random_C Random_D Random_E This allows us to print out the entire DataFrame, ensuring us to follow along with exactly what’s going on. The DataFrame contains a number of columns of different data types, but few rows. By copying the code below, you’ll load a dataset that’s hosted on my Github page. To follow along with this tutorial, let’s load a sample Pandas DataFrame. Conclusion: Using Pandas to Select Columns.How to Select Columns Meeting a Condition.

How to Select Column Names Containing a String in Pandas.How to Select Columns by Data Type in Pandas.How to Select Multiple Columns in Pandas.How to Select a Single Column in Pandas.