Notebook

In [ ]:

import numpy as np
import pandas as pd

In [ ]:

df = pd.DataFrame({
    'ticker': ['AAPL', 'AAPL', 'MSFT', 'IBM', 'YHOO'],
    'date': ['2015-12-30', '2015-12-31', '2015-12-30', '2015-12-30', '2015-12-30'],
    'open': [426.23, 427.81, 42.3, 101.65, 35.53]
})

Exercise:

Select the open column as a Series using attribute lookup
Select the open column as a Series using dict-style lookup
Select the date column as a DataFrame

Exercise:

Select all rows with the AAPL ticker and the date and open columns.
Assign to the variable df1 a new DataFrame with ticker as the index.
Assign to the variable df2 a new DataFrame with date as the index. Create this DataFrame from df1 with a single statement.
Sort df2 by the index values.

Exercise:

Create a copy of df called df3. Add a new column of NaNs to df3 called close. Assign close the same value as open for all open values greater than 100.
Sort df3 by its close values.