Python Regex Compile

The method re.compile(pattern) returns a regular expression object from the pattern that provides basic regex methods such as pattern.search(string), pattern.match(string), and pattern.findall(string). The explicit two-step approach of (1) compiling and (2) searching the pattern is more efficient than calling, say, search(pattern, string) at once, if you match the same pattern multiple times because it avoids … Read more

Python Int to String with Leading Zeros

To convert an integer i to a string with leading zeros so that it consists of 5 characters, use the format string f'{i:05d}’. The d flag in this expression defines that the result is a decimal value. The str(i).zfill(5) accomplishes the same string conversion of an integer with leading zeros. Challenge: Given an integer number. … Read more

How to Calculate the Column Variance of a DataFrame in Python Pandas?

Want to calculate the variance of a column in your Pandas DataFrame? In case you’ve attended your last statistics course a few years ago, let’s quickly recap the definition of variance: it’s the average squared deviation of the list elements from the average value. You can calculate the variance of a Pandas DataFrame by using … Read more

Python Function Call Inside List Comprehension

Question: Is it possible to call a function inside a list comprehension statement? Background: List comprehension is a compact way of creating lists. The simple formula is [expression + context]. Expression: What to do with each list element? Context: What elements to select? The context consists of an arbitrary number of for and if statements. … Read more

Python Regex Flags

In many Python regex functions, you see a third argument flags. What are they and how do they work? Flags allow you to control the regular expression engine. Because regular expressions are so powerful, they are a useful way of switching on and off certain features (e.g. whether to ignore capitalization when matching your regex). … Read more

How to Create a DataFrame in Pandas?

In Python’s pandas module, DataFrames are two-dimensional data objects. You can think of them as tables with rows and columns that contain data. This article provides an overview of the most common ways to instantiate DataFrames. We follow the convention to rename the pandas import to pd. Create a DataFrame From a CSV File Creating … Read more

Python TypeError: Object is Not Subscriptable (How to Fix This Stupid Bug)

Do you encounter this stupid error? You’re not alone—thousands of coders like you generate this error in thousands of projects every single month. This short tutorial will show you exactly why this error occurs, how to fix it, and how to never make the same mistake again. So, let’s get started! Python throws the TypeError … Read more

How Much Can You Earn as a Data Science Freelancer?

A recent study from O’Reilly found that data science is a wide field with many specializations and job descriptions. However, the average earning of an employed data scientist—45% of all respondents would consider themselves as such—is between $60,000 and $110,000. This means that experienced data scientists over time quite certainly reach six-figure income levels if … Read more

[Ultimate Guide] Freelancing as a Data Scientist

Two mega trends can be observed in the 21st century: (I) the proliferation of data—and (II) the reorganization of the biggest market in the world: the global labor market towards project-based freelancing work. By positioning yourself as a freelance data scientist, you’ll not only work in an exciting area with massive growth opportunities but you’ll … Read more