Problem Formulation and Solution Overview In this article, you’ll learn how to extract specific columns or a sub-set thereof from a NumPy array in Python. Often, a sub-set of data needs to be extracted from a larger dataset. This sub-set could be a pre-determined number of column(s) or row(s). These examples show you how to … Read more
The easiest way to convert a space-delimited file to a comma-separated values (CSV) file is to use the following three lines of code: import pandas as pd df = pd.read_csv(‘my_file.txt’, sep=’\s+’, header=None) df.to_csv(‘my_file.csv’, header=None) We’ll explain this and other approaches in more detail next—scroll down to Method 3 for this exact method. Problem Formulation Given … Read more
Problem Formulation and Solution Overview In this article, you’ll learn how to get the first Key and Value from a key:value pair in a Python Dictionary. A Dictionary in Python is used to store information in a key:value pair format. These pairs are modifiable and do not allow duplicates. 💡 Note: In theory, the dictionary … Read more
How to write a NumPy array to a CSV file in Python? To write a NumPy array to a CSV file, use the np.savetxt() function and pass the filename as a string, as well as the array into it. Optionally, you can specific the file format, the delimiter such as comma or semicolon, and other … Read more
💬 Question: How to convert a list of custom objects to a csv file? Example: Given is a list of custom objects of, say, type Employee that holds the name, job description, and income like so: Your goal is to write the content of the list of objects into a comma-separated-values (CSV) file format. Your … Read more
Problem Formulation and Solution Overview In this article, you’ll learn how to convert a List of Booleans to Integers. In Python, the Boolean is a built-in data type. These values represent True (1) or False (0). Also referred to as Truthy or Falsy values. In this article, we will articulate how these values behave. To … Read more
Problem Formulation and Solution Overview In this article, you’ll learn how to increment a dictionary value in Python. To make it more fun, we have the following running scenario: Trinity Bank keeps track of its latest mortgage rates in a Dictionary format. Recently there has been a steady increase in rates. How would Trinity Bank … Read more
Problem Formulation Given a CSV file (e.g., stored in the file with name ‘my_file.csv’). INPUT: file ‘my_file.csv’ 9,8,7 6,5,4 3,2,1 Challenge: How to convert it to a NumPy Array? OUTPUT: 2D NumPy Array [[9. 8. 7.] [6. 5. 4.] [3. 2. 1.]] Method 1: np.loadtxt() You can convert a CSV file to a NumPy array … Read more
Problem Formulation and Solution Overview In this article, you’ll learn how to create high-precision data types in Python. 💡 Definition: High-precision data types are numeric data types, such as integers, or floats, that use additional memory when complex mathematical calculations require extreme accuracy. 💬 Question: How would we write Python code to create high-precision data … Read more
Problem Formulation and Solution Overview In this article, you’ll learn how to initialize a NumPy array in Python using six (6) of the most commonly used methods. Background: NumPy is Python’s impressive array-based data structure library used to perform intense mathematical calculations popularized by the Machine Learning and Data Science community. Let’s start by creating … Read more
Problem Formulation Input: You have some data in a CSV file stored in ‘my_file.csv’ where the first row is the header and the remaining rows are values associated to the column names in the header. Name,Job,Age,Income Alice,Programmer,23,110000 Bob,Executive,34,90000 Carl,Sales,45,50000 Desired Output: You want to store the data in an XML file ‘my_file.xml’ so that each … Read more
💬 Question: How to import a CSV file to a Pandas DataFrame in Python? This article will discuss the most interesting examples to read a CSV file to a Pandas DataFrame. If not specified otherwise, we use the following CSV file for all examples: my_file.csv: Name,Job,Age,Income Alice,Programmer,23,110000 Bob,Executive,34,90000 Carl,Sales,45,50000 Let’s get started! Example 1 – … Read more