![]() To play 720p HD video, an iTunes LP, or iTunes Extras, a 2.0GHz Intel Core 2 Duo or faster processor, 1GB of RAM, and an Intel GMA X3000, ATI Radeon X1300, or NVIDIA GeForce 6150 or better is required.To play standard-definition video from the iTunes Store, an Intel Pentium D or faster processor, 512MB of RAM, and a DirectX 9.0–compatible video card is required. ![]() PC with a 1GHz Intel or AMD processor with support for SSE2 and 512MB of RAM. ![]() We can use the row labels 'Morning' and 'Evening' to select the desired rows. Step 5: Select from temperatures the rows for 'Morning' and 'Evening' temperature readings. We can use the row label 'Morning' to select the desired row. Step 4: Select from temperatures the row of 'Morning' temperature readings. We can use the column name 'Maxine' to select the desired column. Step 3: Select from temperatures the column of temperature readings for 'Maxine'. We can pass the list of custom indices to the index keyword argument when creating the DataFrame. Step 2: Recreate the DataFrame temperatures from Part (a) with custom indices using the index keyword argument and a list containing 'Morning', 'Afternoon', and 'Evening'. We can create a dictionary with the temperature readings and pass it to the DataFrame constructor. Step 1: Create a DataFrame named temperatures from a dictionary of three temperature readings for 'Maxine', 'James', and 'Amanda'.
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