pandas - Calculate the min, max and mean windspeeds and standard deviations

Question

Calculate the min, max and mean windspeeds and standard deviations of the windspeeds
: across all locations for each week (assume that the first week starts on January 2 1961) for the first 52 weeks.

get data
https://github.com/prataplyf/Wind-DateTime/blob/master/wind_data.csv

not understad how to solve

weekly average of each location

          RTP    VAL   ....... . ..... ..  .. . . .. . . .. ... BEL   MAL
1961-1-1
1961-1-8
1961-1-15

Answer 1

Load the data:

df = pd.read_csv('wind_data.csv')

Convert date to datetime and set as the index

df.date = pd.to_datetime(df.date)
df.set_index('date', drop=True, inplace=True)

Create a DateFrame for 1961

df_1961 = df[df.index < pd.to_datetime('1962-01-01')]

Resample for statistical calculations

df_1961.resample('W').mean()
df_1961.resample('W').min()
df_1961.resample('W').max()
df_1961.resample('W').std()

Plot the data for 1961:

fix, axes = plt.subplots(12, 1, figsize=(15, 60), sharex=True)
for name, ax in zip(df_1961.columns, axes):
    ax.plot(df_1961[name], label='Daily')
    ax.plot(df_1961_mean[name], label='Weekly Mean Resample')
    ax.plot(df_1961_min[name], label='Weekly Min')
    ax.plot(df_1961_max[name], label='Weekly Max')
    ax.set_title(name)
    ax.legend()