Google BigQuery is a serverless data warehouse fully managed by Google. It supports storing and accessing huge data and also accommodates querying the data with ease. We can access Google BigQuery from the Google Cloud Console which hosts many useful APIs and other services for building, deploying, and scaling our applications. One such useful service …
How to Load Data From Google BigQuery Returning a Data Frame? Read More »
Python is gifted with an variety of tools to optimise the cosmetics of the data analysed. One among them is the Styler which shall be explored to its lengths & breadths in this article. We shall narrow down particularly to how these styling are transferred from Python to an Excel spreadsheet. Styler object is very …
In this article, we make ourselves familiar with one more file type the Stata files in Python which come with several extensions(.dta,.ado,.do,.smcl, etc explained below). We also look at different methods to return a dictionary associating each variable name with the corresponding label. Understanding Stata Files Academic and research communities widely use Stata software a …
Working with Stata Files in Python: Reading Variable Labels with Pandas Read More »
To read data from fixed-width formatted text files to DataFrame, pandas have introduced a function called read_fwf().So what are fixed-width formatted text files? Fixed-width formatted text files are files where each field in a row has a fixed width or fixed number of characters. These types of files were primarily used in legacy systems for …
The Groupby function of the Pandas library is used to categorize the data based on a certain condition. The Pandas data frame can be split based on criteria with the help of the groupby function. It is similar to the groupby function in SQL querying where the output is printed based on certain conditions. The …
The most useful, easy to understand, and efficient open-source library tool for handling data, cleaning the data, modification, and analysis in Python is Pandas. As a result, Pandas is quite useful when working with large datasets. Pandas’ built-in function facilitates reading datasets in a variety of formats. Python users can read CSV files (Comma Separated Values files) in …
ORC stands for Optimized Row Columnar storage format was introduced to store the Hive workloads efficiently. As the name suggests, the ORC format stores the data in the form of columns which enables us to perform parallel processing of data and also helps to store the data efficiently. The ORC format was initially introduced by …
What Is ORC and How to Write a Data Frame to ORC Format? Read More »
When you’re working with Pandas, you must have seen the axis as the argument for many functions. What is this axis? What does it mean? Why is it so important? Let’s dive deep into Pandas and understand what this axis is and how to use it. What is Pandas? Pandas is one of the most …
A Data Frame Index is a column in the data frame that represents the data frame as a whole. It can be specified while creating the data frame or we can even set the index after analyzing it. While we are talking about the index of a data frame, it is essential to know what …
Using a Pandas Data Frame Index for X-Axis in Matplotlib Plot Read More »
Stata is a powerful statistical software package used for data science-related tasks. Stata is a complete, integrated software package that is a one-stop solution for all your data science needs—data manipulation, visualization, statistics, and automated reporting. It is a combination of the two words statistics and data. Stata is mainly used by researchers and academicians in …