A Time Series is essentially a tabular data with the special feature of having a time index. The common forecast task is ‘knowing the past (and sometimes the present), predict the future’. This task, taken as a principle, reveals itself in several ways: in how to interpret your problem, in feature engineering, and in which … Read more
💬 Challenge: Given a Pandas DataFrame. How to find the longest string in a given DataFrame column? We’re going to discuss different variants of this problem next. Let’s get started with the easiest next! Method 1: Find Length of Longest String in DataFrame Column To find the length of the longest string in a DataFrame … Read more
Problem Formulation and Solution Overview This article will show you how to add days to a Pandas DataFrame Date column. To make it more interesting, we have the following running scenario: CheckersTV is a new channel offering streaming news and games. They have a large subscriber base, each paying a monthly fee of $12.99. For … Read more
Problem Formulation and Solution Overview This article will show you how to find the most common element in a Pandas Column. To make it more interesting, we have the following running scenario: You have been provided with a downloadable CSV file containing crime statistics for the San Diego area, including their respective NCIC Crime Codes. … Read more
Problem 💬 Challenge: How to convert a Parquet file ‘my_file.parquet’ to a CSV file ‘my_file.csv’ in Python? In case you don’t know what a Parquet file is, here’s the definition: 💡 Info: Apache Parquet is an open-source, column-oriented data file format designed for efficient data storage and retrieval using data compression and encoding schemes to … Read more
A not-so-fictious problem: Say, you’ve created a web application that runs on a dedicated Linux server in the cloud. Thousands of users visit your web app and suddenly … it crashes. Your users start complaining, and you lose revenue. More importantly, you bleed credibility by the hour. Your server is down, so what do you … Read more
Problem Formulation and Solution Overview This article will show you how to find DataFrame row indices in Python with NaN or Null (empty) values. To make it more interesting, we have the following scenario: Rivers Clothing has given you a CSV file that requires a clean-up to make it usable for Payroll and Data Analysis. … Read more
Problem Formulation Given the following DataFrame df: 💬 Challenge: How to apply a function f to each cell in the DataFrame? For example, you may want to apply a function that replaces all odd values with the value ‘odd’. Solution: DataFrame applymap() The Pandas DataFrame df.applymap() method returns a new DataFrame where the function f … Read more
Given an HTML table (code) in a file or at a given URL. First, load all HTML tables into the Python script by calling Pandas’ pd.read_html() passing the URL of the HTML document. The result is a list of DataFrames, one per HTML table in the document. Second, convert any specific DataFrame to a CSV … Read more
The Pandas read_html() function is an easy way to convert an HTML table (e.g., stored at a given URL) to a Pandas DataFrame. You pass a location string or path to it and it returns a list of DataFrames, each representing one table from the location path or URL. The following code, for example, reads … Read more
Problem Formulation and Solution Overview In this article, you’ll learn how to iterate over a 1D, 2D and 3D NumPy array using Python. When working with the NumPy library, you will encounter situations where you will need to iterate through a 1D, 2D and even a 3D array. This article will show you how to … Read more
What is a Fixed-Width File? 💡 Definition: A fixed-width text file contains data that is structured in rows and columns. Each row contains one data entry consisting of multiple values (one value per column). Each column has a fixed width, i.e., the same number of characters, restricting the maximum data size per column. Example of … Read more