In machine learning, it is important to distinguish the matrix of features (independent variables) and dependent variables from dataset. We can also change the format of our dataset by clicking on the format option.Įxtracting dependent and independent variables: Consider the below image:Īs in the above image, indexing is started from 0, which is the default indexing in Python. We can also check the imported dataset by clicking on the section variable explorer, and then double click on data_set. Once we execute the above line of code, it will successfully import the dataset in our code. Here, data_set is a name of the variable to store our dataset, and inside the function, we have passed the name of our dataset. Using this function, we can read a csv file locally as well as through an URL. Now to import the dataset, we will use read_csv() function of pandas library, which is used to read a csv file and performs various operations on it. Now, the current folder is set as a working directory. Here, in the below image, we can see the Python file along with required dataset. Note: We can set any directory as a working directory, but it must contain the required dataset. Click on F5 button or run option to execute the file.Go to File explorer option in Spyder IDE, and select the required directory.Save your Python file in the directory which contains dataset.To set a working directory in Spyder IDE, we need to follow the below steps: But before importing a dataset, we need to set the current directory as a working directory. Now we need to import the datasets which we have collected for our machine learning project. Consider the below image: 3) Importing the Datasets Here, we have used pd as a short name for this library. It is an open-source data manipulation and analysis library. Pandas: The last library is the Pandas library, which is one of the most famous Python libraries and used for importing and managing the datasets. Here we have used mpt as a short name for this library. It also supports to add large, multidimensional arrays and matrices. It is the fundamental package for scientific calculation in Python. Numpy: Numpy Python library is used for including any type of mathematical operation in the code. There are three specific libraries that we will use for data preprocessing, which are: These libraries are used to perform some specific jobs. In order to perform data preprocessing using Python, we need to import some predefined Python libraries. We can also create our dataset by gathering data using various API with Python and put that data into a. For real-world problems, we can download datasets online from various sources such as, etc. Here we will use a demo dataset for data preprocessing, and for practice, it can be downloaded from here, ". It is useful for huge datasets and can use these datasets in programs. What is a CSV File?ĬSV stands for " Comma-Separated Values" files it is a file format which allows us to save the tabular data, such as spreadsheets. However, sometimes, we may also need to use an HTML or xlsx file. To use the dataset in our code, we usually put it into a CSV file. So each dataset is different from another dataset. The collected data for a particular problem in a proper format is known as the dataset.ĭataset may be of different formats for different purposes, such as, if we want to create a machine learning model for business purpose, then dataset will be different with the dataset required for a liver patient. To create a machine learning model, the first thing we required is a dataset as a machine learning model completely works on data.
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