Inside the read_table() function we pass in the name of the file which is "example.csv". Then we read the CSV file by applying the read_table() function. Let’s start with read_table(): import pandas as pdįirst, we import the Pandas library. Here you find the read_table() documentation, and here the read_csv() documentation. Reference: You can read more about these functions in the official Pandas documentation. We will start by simply reading the two files by using the read_csv() function and the read_table() function. Read a Flat file with read_csv() and read_table() The files contain information about three people, their age, and the number of children they have. This is how they both look like: Name Age Children The only difference is the file extension. A CSV file ( ".csv") and a text file ( ".txt") which both contain the same information. Typical formats for flat files are, for example, ".csv", ".txt", and ".xml".įor this tutorial, we will use two flat files. It is composed of one data set and has no text processing or structure markup. Before we start with the actual coding, let’s first clarify what a flat file is.Ī flat file is a text file that stores data and has no hierarchical structure.
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