cgmtutorial5.py

# Instantiate a new dataframe. We will call this one "df"
df = pd.DataFrame() # This creates an empty data frame

# Pull timestamp and glucose columns into the new, empty dataframe. We will change their names to "DateTime" and "Glucose" 
df['DateTime'] = data['Timestamp (YYYY-MM-DDThh:mm:ss)']
# For glucose, we also want to change the data to a number. Right now, Python thinks the glucose column values are strings (you can think of a string as text). We will wrap the function in pd.to_numeric() to convert the column to numbers.
df['Glucose'] = pd.to_numeric(data['Glucose Value (mg/dL)'])

# The first 12 rows don't even have matching glucose + time values, so let's drop those
df.drop(df.index[:12], inplace=True)