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Community Data Science Course (Spring 2023)/Week 7 lecture notes
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== Getting setup == Importing pandas: * <code>import pandas as pd</code> * If your data has any numbers, it's very normal to also import a closely related package called numpy: <code>import numpy as np</code> Quick intro to Series: * we can build series from lists and they basically ask like lists in terms of indexing, including etc * we can also add an index to them <code>my_series.index</code> which makes them a lot like dictionaries (except we can have multiple things with the same key!!) * they come with cool built in functions (like <code>.value_counts()</code> and <code>.hist()</code>) * tons of functions associated with Series: https://pandas.pydata.org/docs/reference/api/pandas.Series.html Quick introduction to DataFrames: * a DataFrame is of Series ''that are all of the same length'' * we can build them up from a dictionary of lists or a list of dictionaries (I typically prefer the latter but either works)! * tons of functions associated with DataFrames: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html A more common situation however is that we import them from some other tabular data source
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