Refresher - Constructing DataFrames:

• Recall that a DataFrame represents a rectangular table of data and contains an ordered, named collection of columns, each of which can be a different value type.
• The pd.DataFrame() function can be used to create a DataFrame.
  • For example, the data for the DataFrame below is hard coded into a list of lists. Each inner list represents a row of data. The first list contains the column headers, and the subsequent lists contain the actual data.

1import pandas as pd
2
3# Hardcode a dataframe 
4df = pd.DataFrame(
5    [
6        [
7            'BusinessEntityID', 'EmployeeName', 'EmailAddress',
8            'PhoneNumber', 'StartDate', 'CurrentSalary'
9        ],
10        [
11            1699, 'Robinett, David', 'david22@adventure-works.com',
12            '(827) 525-0100', '06-05-2010', '$80,950'
13        ],
14        [
15            1700, 'Robinson, Rebecca', 'rebecca5 @adventure-works.com',
16            '(829) 525-0101', '05-01-2015', '$70,950'
17        ],
18        [
19            1701, 'Robinson, Dorothy', 'dorothy3@adventure-works.com',
20            '(828) 555-0102', '03-01-2017', '$50,00'
21        ],
22    ]
23)
24  
25print(df.shape)
26df

Output

(4, 6)

Using First Row as Header/Column Names

• If the column names we want are actually the first row of the data, like in the example above, we can:
  1. Grab the Column Names out of the First Row of the DataFrame using iloc.
  2. Set the columns property of the DataFrame equal to the column names we extracted in step 1.
  3. Get rid of the first row of the DataFrame using df[1:].