Use groupby with size and unstack or crosstab alternative for reshape.

For change order of days need ordered Categorical or reindex by columns:

cats = ['Monday','Tuesday','Wednesday','Thursday','Friday']

df['Weekday'] = pd.Categorical(df['Weekday'], categories=cats, ordered=True)

df = df.groupby(['Time', 'Weekday']).size().unstack(fill_value=0)

df = df.groupby(['Time', 'Weekday']).size().unstack(fill_value=0).reindex(columns=cats)

Alternatives:

df = pd.crosstab(df['Time'], pd.Categorical(df['Weekday'], categories=cats, ordered=True))

df = pd.crosstab(df['Time'], df['Weekday']).reindex(columns=cats)

print (df)

col_0     Monday  Tuesday  Wednesday  Thursday  Friday
Time                                                  
21:10:00       0        1          0         0       0
21:15:00       0        1          0         0       0
21:20:00       0        2          0         0       0
21:25:00       0        0          2         0       0
21:30:00       0        0          0         0       1
21:35:00       0        0          1         1       0
21:40:00       1        0          2         0       0

Last use seaborn.heatmap:

import seaborn as sns

sns.heatmap(df, annot=True, fmt="g", cmap='viridis')