Importing Data For Datasets Using CSV Files
This is the simplest method of importing any dataset from a CSV file. For this we will be using the Panda, so importing the Pandas library is a must.
Syntax: pd.read_csv(‘path of the csv file’)
Consider the CSV file we want to import is price.csv.
Python3
import pandas as pd print('Read data...') # enter the complete path of the csv file df = pd.read_csv('../price.csv',header=0).head(1000) data = df.values |
PyBrain – Importing Data For Datasets
In this article, we will learn how to import data for datasets in PyBrain.
Datasets are the data to be given to test, validate and train on networks. The type of dataset to be used depends on the tasks that we are going to do with Machine Learning. The most commonly used datasets that Pybrain supports are SupervisedDataSet and ClassificationDataSet. As their name suggests ClassificationDataSet is used in the classification problems and the SupervisedDataSet for supervised learning tasks.