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Categorical pitfalls Using categories can be frustrating Using the .str accessor object to manipulate data converts the Series to an object. The .apply() method outputs a new Series as an object. The common methods of adding, removing, replacing, ...
Introduction to categorical plots using seaborn Categorical plot import seaborn as sns import matplotlib.pyplot as plt sns.catplot(...) plt.show() The catplot function Parameters x: name of the variable in data. y: name of the variable in data. ...
Setting category variables The .cat accessor object Series.cat.method_name Common parameters: new_categories: a list of categories inplace: Boolean - whether or not the update should overwrite the series ordered: Boolean - whether or not the cate...
Introduction What does it mean to be "categorical"? Categorical Finite number of groups (or categories) These categories are usually fixed or known (gender, hair color, etc.) Numerical Known as qualitative data Expressed using a numerical value...
Consideration for categorical data Why perform EDA? Detecting patterns and relationships Generating questions or hypotheses Prepare data for machine learning model Representative data Sample represents the population Categorical classes Class...
Patterns over time When data includes dates or time values, we'll want to examine whether there might be patterns over time Importing DateTime data df = pd.read_csv('datasets.csv', parse_dates=['birth_date']) Converting to DateTime data df['birth_da...