Our Dataset:
I am adding the image of the dataset that we will be using in this article. This is our data frame df.
Reset index column
Suppose we want to set the index of our columns by Product Category, we can do it with:
df_ind = df.set_index(“Product Category”)
df_ind.head()
Result
Reindex and sort by two columns
df_ind = df.set_index([“Product Category”,”Product Subcategory”])
df_ind = df_ind.sort_index(level=[“Product Category”,”Product Subcategory”],ascending=[False, True])
df_ind
Filter Dataframe by a value in a particular column.
Suppose we want to filter the data and only keep rows where the product subcategory is ‘Sweet’, here’s how you do it.
df_filter = (df[df[‘Product Subcategory’] == ‘Sweets’])
df_filter
Result
Calculate the range of a column.
def range(column):
return column.max() — column.min()print(df[[‘Price’, ‘Age’]].agg(range))
Result:
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