Pandas time series data manipulation is a must have skill for any data analyst/engineer. More than 70% of the world’s structured data is time series data. And pandas library in python provides powerful functions/APIs for time series data manipulation. So let’s learn the basics of data wrangling using pandas time series APIs.
In any data science/data analysis work, the first step is to read CSV file (with pandas library). Pandas read_csv function is popular to load any CSV file in pandas. In this post we’ll explore various options of pandas read_csv function.
In post, we’ll learn to create pandas dataframe from python lists and dictionary objects. Creating pandas dataframe is fairly simple and basic step for Data Analysis. There are also other ways to create dataframe (i.e. from csv, excel files or even from databases queries). But we’ll cover other steps in other posts.