Summary
In this chapter, you witnessed the use of Pandas to represent tabular data. You learned about the two main Pandas data structures: Series and DataFrame. I attempted to keep things simple and to show you some of the most common operations that you would perform on these data structures. As extracting rows and columns from DataFrames is so common, I have summarized some of these operations in Table 3.1.
Table 3.1: Common DataFrame Operations
| DESCRIPTION | CODE EXAMPLES |
| Extract a range of rows using row numbers | df[2:4]
df.iloc[2:4] |
| Extract a single row using row number |
df.iloc[2]
|
| Extract a range of rows and range of columns |
df.iloc[2:4, 1:4]
|
| Extract a range of rows and specific columns using positional values |
df.iloc[2:4, [1,3]]
|
| Extract specific row(s) and column(s) |
df.iloc[[2,4], [1,3]]
|
| Extract a range of rows using labels |
df['20190601':'20190603']
|
| Extract a single row based on its label |
df.loc['20190601']
|
| Extract... |
