We can do simple calculations on dataframe columns by applying functions on every element of the column, that is, elementwise application of functions. These functions can be built-in Python functions, NumPy functions, or user-defined functions, such as lambda functions (see Section 7.7, Anonymous functions).
The simplest way is to operate on the columns directly. In the following example, we convert watts into kilowatts and Swedish crowns (SEK) into Euros by using the conversion rate, which was the actual rate on the day of the measurement:
solar_converted=pd.DataFrame()
solar_converted['kW']=solar_all['Watt']/1000
solar_converted['Euro']=solar_all['SEK']/solar_all['Euro_SEK']
Tacitly, we also adjusted the column labels to the converted units.
The command solar_converted.loc['2020-07-01 7:00':'2020-07-01 7:04']Â then returns the converted data for July...
