How-to articles, tricks, and solutions about PYTHON

You can use the os.path.basename() function to extract the file name from a file path, regardless of the operating system or path format.

You can extract the file extension from a file name in Python by using the os.path module.

You can extract the month and year separately from a Pandas datetime column using the dt accessor.

To create a new DataFrame with a subset of columns from an existing DataFrame, you can use the pandas library.

The fastest way to check if a value exists in a list is to use the in operator.

It looks like you are trying to include the Python.h header file in a C or C++ program, but it is not found on your system.

Here is an example of how you can filter a pandas DataFrame by substring criteria:

Here is a code snippet that uses the os and glob modules to find all files in a directory with the extension '.txt':

To find the current directory in Python, you can use the following code:

You can use the following command to check the version of a package installed with pip:

Here is a Python code snippet that demonstrates how to find and replace elements in a list:

Here is a code snippet that uses the socket module from Python's standard library to find the local IP addresses of the host machine:

Here is a Python code snippet for finding the average of a list of numbers:

To find the index of an item in a list in Python, you can use the index() method of the list.

To generate a random integer between 0 and 9 in Python, you can use the random module and the randint function.

You can use the DataFrame.columns attribute to access the column labels of a DataFrame as an Index object.

You can use the set data type to find the difference between two lists with unique entries.

Here's an example of how you can get the first row value of a given column in a Pandas DataFrame in Python:

You can use the in keyword to check if a value exists in a dictionary, and then use the items() method to return a list of key-value pairs.

In Pandas, a DataFrame is a 2-dimensional labeled data structure with columns of potentially different types.

In pandas, you can use the groupby() method to group data by one or more columns and then use the agg() method to compute various statistics for each group.

In a Flask application, you can access the data received in a request using the request object.

In Python, you can use the set() function to get the unique values from a list.

Here is a code snippet in Python that gets a list of all subdirectories in the current directory:

You can use the built-in max() function in Python to get the key with the maximum value in a dictionary.