Pandas DataFrames Archives • Page 2 of 3 • datagy

Pandas: Number of Columns (Count Dataframe Columns)

Learn how to use Python and Pandas to count the number of columns in a dataframe, using counting the number of columns meeting a condition.

Learn how to use the Python Pandas shift function to move a dataframe’s rows up or down, including working with time series and missing data.

Learn how to sample data in Pandas using Python, including how to use the sample function, reproduce results, and weighted samples of data.

Learn how to use Python and Pandas to iterate over rows of a dataframe, why vectorization is better, and how to use iterrows and itertuples.

Learn how to use Python and Pandas to convert a dataframe column values to strings, including how to optimize for memory and efficiency.

Learn how to rename a Pandas index, including a single index or multi-index, as well as how to drop an index name altogether.

Learn how to transpose a pandas dataframe, including how to work with mixed datatypes and what their outputs may be.

Learn how to split a Pandas dataframe in Python. Split a dataframe by column value, by position, and by random values.

Learn how to get Pandas columns as a list, a sorted list and how to check if a column exists in a particular dataframe.

Learn how to count the number of rows in a Pandas Dataframe, including identifying how many rows contain a value or meet a condition.

Learn the ways in which you can rename Pandas columns, using Pandas .rename() method. Learn how to rename one, all, including automatically.

Learn different ways to reorder Pandas columns, including the Pandas reindex function as well as a custom function.