The Basics of Tabular Data
Contents
The Basics of Tabular Data¶
Content Summary¶
The basics of tabular data consist of understanding:
the structure of a table and how it represents a realworld phenomenon,
the basic operations that can be performed on a table and how they reflect the realworld phenomenon it represents,
the computational foundations for tabular data structures in Pandas.
Datasets¶
The primary dataset in this chapter consists of player statistics from the US Women’s National Team in Soccer between 1991 and 2019. The data is taken from Football Reference.
Summary of Library References¶
In the lists below, assume that the usual imports have been executed:
import pandas as pd
import numpy as np
Creating Tabular Structures:¶
Function or Method Name 
Description 

Series constructor 

DataFrame constructor 

Reading CSV from file 
Series/DataFrame attributes and methods:¶
Function or Method Name 
Description 

Number of rows/columns 

Returns first few lines 

Returns the last few lines 

Returns the number of unique values 

Returns the type of the column(s) 

Returns column(s) coerced to a given type 

sorts Series/DataFrame according to its values 

drops duplicates indices/columns 

apply a function to the entries of a Series / slices of a DataFrame 

apply a collection of functions to a Series/DataFrame 
Methods for computing descriptive statistics on Series/DataFrames:¶
Function or Method Name 
Description 

Returns descriptive statistice of column(s) 

Returns the number of nonnull entries 

Returns the sum 

Returns the median 

Returns the median 

Returns the sample standard deviation 

Returns the sample variance 