计算每日温度数据的月平均值，包括负值和正值

Question

I am trying to calculate monthly average temperatures for a dataset with daily temperature values that spans three years. With the data.frame appearing like this example"

   Date        Month      Temperature
   12-2-2016   December   -10
   12-3-2016   December   -12
   01-2-2017   January    -15
   01-3-2017   January    -14
   02-3-2017   February    3
   02-4-2017   February    7
   03-2-2017   March       8
   03-3-2017   March       9

I tried running the following code in order to create a new dataframe with the Month and the average temperature:

   group_by(df$month) %>%
   summarise(mean_airtemp = mean(Temperature))

However, when running this code I get NA for certain months which I believe is attributed to negative values. I have tried to figure it out but have only found solutions that seem to separate the values based on whether they are negative or positive.

Answer 1

you can use groupby of month and temp together

df.groupby(['Month'])['Temperature'].mean().reset_index(name = 'avg')