![]() columns function, you can print out all the columns of the dataset: df.columns When you have a big dataset like that it can be hard to see all the columns. If I wanted 7 rows I would have mentioned in the. ![]() If you want a specific number of rows instead of five rows, you can specify that. Here I am showing the first five rows of the DataFrame df above: df.head() By default, it shows the first 5 rows of the DataFrame. head() function after read_csv or read_excel to see the data frame. If you have an excel file instead of a csv file you will use pd.read_excel. read_csv() function using the following syntax: data = pd.read_csv(file.txt, sep=" ") It has several great parameters that help to clean up the dataset a little bit when you read the dataset.Ī. I have a detailed video on the read_csv function. Here I am using the read_csv function to read the FIFA dataset: df = pd.read_csv("fifa.csv") They are used to read a CSV or an excel file to a pandas DataFrame format. The functions are self-explanatory already. ![]() Till now I used at least one of these functions in every project. ![]() The first function to mention is read_csv or read_excel. Let’s start talking about the functions: 1. Pd.set_option('display.max_columns', 100) I am importing the necessary packages and the dataset: import numpy as np ![]()
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