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Tabular database1/29/2024 So I'll type pd.read_csv, parentheses, and now I'll type in the name of the CSV file as a string. To read in the CSV file, I'll use the read_csv method located in the pandas library. And a reminder that that CSV file is stored in the same directory as this notebook. Now I want to read in the CSV file called us_baby_names.csv. This means that going forward in this notebook, I need to use pd to refer to pandas. And I do this by writing the keyword import followed by pandas. The first thing I'm going to do is import the pandas library. To access the data, you can read in the file like this. For example, say you're working with data regarding the names of babies born in the United States, and this data is stored in a CSV file called us_baby_names.csv. Pandas is a powerful library in Python that provides data analysis tools that are really easy to use. If your data is stored in a CSV file, you can use the read_csv method from a library called pandas to quickly read the file into memory. One of the most common file formats for storing tabular data is comma-separated values, or CSV, where each record is stored as a line and each field is separated by a comma. Tabular data is arranged in rows and columns, and data files are stored in specific formats. Now, there are several ways to structure data, but a lot of data scientists prefer working with tabular data, and the main reason is tabular structure is just more convenient to work with. A data set's structure refers to the arrangement of the data. Data sets can be structured in different ways.
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