From the course: Python Data Analysis
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DataFrames and Series - Python Tutorial
From the course: Python Data Analysis
DataFrames and Series
- [Instructor] The two key objects in pandas are the DataFrame and the Series. A DataFrame is basically a table of data. Each column has a name and an assigned data type as a NumPy. In addition though, the DataFrame has an index, which is not necessarily the ordinal number of the row. In this example, where the columns contain name, date of birth and city, the index could be the social security number or an alphanumerical employee ID. A Series is effectively a single column from a DataFrame with its own index. Having an index makes it more powerful than a simple NumPy array. For instance, if we have two time Series that have partially overlapping indices, times, we can still combine them and pandas will figure out which entries it can actually compute. Just as for NumPy arrays the easiest way to get a pandas DataFrame is to load it from a file. And pandas can read and write an even larger variety of formats than NumPy…
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