如何做每个月的子情节？

Question

I have grouped the dataset by month and date and I have added third column for count the data in each day.

Dataframe before

    month   day  
0    1      1   
1    1      1    
2    1      1      
..
3000 12      31   
3001 12      31   
3002 12      31     

Dataframe now:

   month   day  count
0    1      1    300
1    1      2    500
2    1      3    350  
..
363  12      28   700
364  12      29   1300
365  12      30   1000  

How to do subplot for each month , x will be the days and y will be the count

    import pandas as pd
    import matplotlib.pyplot as plt
    %matplotlib inline
    df= pd.read_csv('/home/rand/Downloads/Flights.csv')
    by_month= df.groupby(['month','day']).day.agg('count').to_frame('count').reset_index()

I'm beginner in data science field

Answer 1

I think you could use pandas.DataFrame.pivot to change the shape of your table to make it more convenient for the plot. So in your code you could do something like this:

 plot_data= df.pivot(index='day', columns='month', values='count')
 plot_data.plot()
 plt.show()

This is assuming you have equal number of days in every month since in the sample you included, month 12 only has 30 days. More on pivot .

Answer 2

Try this

fig, ax = plt.subplots()
ax.set_xticks(df['day'].unique())
df.groupby(["day", "month"]).mean()['count'].unstack().plot(ax=ax)

Above code will give you 12 lines representing each month in one plot. If you want to have 12 individual subplots for those months, try this:

fig = plt.figure()
for i in range(1,13):
    df_monthly = df[df['month'] == i] # select dataframe with month = i
    ax = fig.add_subplot(12,1,i) # add subplot in the i-th position on a grid 12x1   
    ax.plot(df_monthly['day'], df_monthly['count'])
    ax.set_xticks(df_monthly['day'].unique()) # set x axis 

Answer 3

Try this:

df = pd.DataFrame({
    'month': list(range(1, 13))*3, 
    'days': np.random.randint(1,11, 12*3), 
    'count': np.random.randint(10,20, 12*3)})

df.set_index(['month', 'days'], inplace=True)
df.sort_index()

df = df.groupby(level=[0, 1]).sum()

Code to plot it:

df.reset_index(inplace=True)
df.pivot(index='days', columns='month', values='count').fillna(0).plot()