Combining Series into a DataFrame

Multiple Series can be combined to form a DataFrame. Let’s try this by creating another Series and combining it with the emps_names Series: 

data = ['jeff.russell','jane.boorman','tom.heints']

emps_emails = pd.Series(data,index=[9001,9002,9003], name ='emails')

emps_names.name = 'names'

df = pd.concat([emps_names,emps_emails], axis=1)

print(df)

To create the new Series, you call the Series() constructor , passing the following arguments: the list to be converted to a Series, the indices of the Series, and the name of the Series.

You need to name Series before concatenating them into a DataFrame, because their names will become the names of the corresponding DataFrame columns. Since you didn’t name the emps_names Series when you created it earlier, you name it here by setting its name property to 'names'. After that, you can concatenate it with the emps_emails Series. You specify axis=1 in order to concatenate along the columns.

The resulting DataFrame looks like this:

names     emails

9001        Jeff Russell jeff.russell

9002        Jane Boorman jane.boorman

9003        Tom Heints tom.heints