15. Python - Pandas - Sorting/Grouping

Group By:

// Basic Methods

data_frame.groupby('COLUMNA').COLUMNAA.count()

// creates a map with unique values of COLUMNA as index in the first column and then with values showing the count of them in the 2nd column (count of data_frame.COLUMNAA)

// also have min(), max(), etc instead of count()

// COLUMNAA placeholder is for values that relate to COLUMNA groups.

// can have more than one group along with COLUMNA.


// Lambda Functions

data_frame.groupby('COLUMNA').apply(lambda p: p.COLUMNAA.iloc[0])

// this gets the first item of the list of COLUMNAA items that correspond to each group made from COLUMNA.


// agg() function // this creates a data frame

data_frame.groupby(['COLUMNA']).COLUMNB.agg([len,min,max])

// groups by unique values in COLUMNA as keys and then provides values for len,min,and max of COLUMNB relating to COLUMNA.


data_frame.groupby(['COLUMNA']).COLUMNB.min()

// using this instead makes a series

// options: max(), mean(), min()


Multi-Indexes:

data_frame.groupby(['COL_A','COL_B']).COL_C.agg([len])

// have multiple index columns by adding them in a list


// Reset Index:

data_frame.reset_index()

// resets the index to regular 0...n


Sorting:

data_frame.sort_values(by = ['COLUMNA','COLUMNB',etc], ascending = FALSE)

// ascending can be false or true, but true on default


data_frame.sort_index()

// sort by index (if you have a multi-index that is not regular 0..n


Series Methods:

min()

max()

mean()

size() // get count

sort_values(by = ['ETC'], ascending = False)


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