From the course: Python for Data Visualization (2019)
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Basic operations
From the course: Python for Data Visualization (2019)
Basic operations
- After reading the contents of a file into your Pandas DataFrame, it's important to examine your data for a couple of reasons. First, you need to assure that you've correctly loaded the data. Second, you have to see what kind of data you have. And third, you have to check the validity of your data set. And I'll go through a couple ways we can do this. So one of the first things you do after loading your data, is look at the head and the tail of your data set. The method head selects the top end number of records from your data set. The method tail selects the bottom end number of records from your data set. This is really important to do as often times your data format could change the route of your data set. Another important thing to do is to check your column data types. You can do this by using the d types attribute. One thing you'll notice is that certain columns are ints, certain columns are floats, whereas others can be objects and you can think…
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Contents
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Introduction to pandas52s
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Create sample data3m 50s
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Load sample data2m 17s
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Basic operations1m 57s
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Slicing4m 12s
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Filtering5m 39s
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Renaming and deleting columns3m 16s
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Aggregate functions2m 39s
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Identifying missing data3m 41s
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Removing or filling in missing data5m 3s
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Convert pandas DataFrames to NumPy arrays or dictionaries1m 15s
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Export pandas DataFrames to CSV and Excel files1m 28s
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