Python lists are quite versatile and can store a wide range of data in a sequential manner. It might be handy to know if an element belongs to a list or not. For example, you are a librarian at a public library, a person wants to check whether a book is available or not. Fortunately, […]
Python – Check if an element is in a list Read More »
In this tutorial, we will look at how to get a list of unique values in a pandas dataframe column. Additionally, we will also look at how to get a count of each unique value within the column and the total unique count. First, let’s create a sample dataframe that we will be using throughout
Pandas – Get All Unique Values in a Column Read More »
Pandas is a powerful library for manipulating tabular data in python. When working with pandas dataframes, it might happen that you require to delete rows where a column has a specific value. In this tutorial, we will look at how to delete rows based on the column values of a pandas dataframe. How to delete
Pandas – Delete rows based on column values Read More »
Measuring the performance of your model using the correct metric is a very important step in the data science process. In this tutorial, we’ll look at how to compute the accuracy of your predictions from scratch and with sklearn in Python. What is accuracy? Accuracy is one of the most common metrics used to judge
Get Accuracy of Predictions in Python with Sklearn Read More »
Pandas groupby is a great way to group values of a dataframe on one or more column values. When performing such operations, you might need to know the number of rows in each group. In this tutorial, we will look at how to count the number of rows in each group of a pandas groupby
Pandas Groupby – Count of rows in each group Read More »
In this tutorial, we’ll look at how to iterate over multiple lists in parallel using the zip() function in python. Python zip() function The zip() function in python is used to aggregate elements from multiple iterable objects element-wise into an iterable of tuples. For example, if you combine the lists [1, 2, 3] and [‘a’,
Python – Iterate over multiple lists in parallel using zip() Read More »
Correlation is an important statistic that tells us how two sets of values are related to each other. A positive correlation indicates that the values tend to increase with one another and a negative correlation indicates that values in one set tend to decrease with an increase in the other set. In this tutorial, we
Get correlation between columns of Pandas DataFrame Read More »
Writing a dataframe to a pickle file instead of a CSV file can be very helpful particularly if you want to preserve the state of the dataframe. If you are loading the pickle file back, it saves you time on data type transformations since the data type information is already saved in the pickle file.
Save Pandas DataFrame to a Pickle File Read More »
Pandas is a powerful data manipulation library in python. Among other manipulations, you can use it to compute cumulative sum of a row or a column in a dataset. In this tutorial, we’ll look at how to get the cumulative sum of a pandas dataframe column. How to calculate cumulative sum in pandas? You can
Cumulative Sum of Column in Pandas DataFrame Read More »
Treating missing values is an important step in cleaning the data and making it ready for further analysis and usage. It is thus important to correctly identify them. Having an idea of how these values are present can give us directions in treating them. For example, if a column has mostly missing values with very
Pandas – Count Missing Values in Each Column Read More »
