python pandas dataframe from columns

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pandas is a powerful data manipulation and analysis library for python. one of its key data structures is the dataframe, which is a two-dimensional table with labeled axes (rows and columns). this tutorial will guide you through creating a dataframe from columns using pandas, along with code examples.
before we start, make sure you have pandas installed. if not, you can install it using:
first, import the pandas library in your python script or jupyter notebook.
define your data in the form of columns. you can use lists or numpy arrays.
use the pd.dataframe() constructor to create a dataframe from the columns.
print or display the dataframe to see the result.
the output will look like:
now that you have a dataframe, you can access specific columns.
you can add a new column to the dataframe easily.
this will add a 'salary' column to the dataframe.
in this tutorial, you learned how to create a pandas dataframe from columns using python. you also saw how to access specific columns and add a new column to the dataframe. pandas provides a wide range of functionality for data manipulation, exploration, and analysis, making it a valuable tool for data scientists and analysts. explore the official pandas documentation for more advanced features and methods.
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