how plot multiples dataframe csv in same plot

Question

I have 4 dataframes in 4 csv. I need to plot timeseries ( Date , mean ) in the same plot.

This is my script :

cc = Series.from_csv('D:/python/means2000_2001.csv' , header=0)

fig = plt.figure()
plt.plot(cc , color='red')
fig.suptitle('test title', fontsize=20)
plt.xlabel('Date', fontsize=15)
plt.ylabel('MEANS ', fontsize=15)
plt.xticks(rotation=90)

The 4 dataframes are like this ( x=Date and y=mean )

 Out[307]: 
 Date
07-28     0.17
08-13     0.18
08-29     0.17
09-14     0.19
09-30     0.19
10-16     0.20
11-01     0.18
11-17     0.22
12-03     0.21
12-19     0.82
01-02     0.59
01-18     0.52
02-03     0.54
02-19     0.53
03-07     0.33
03-23     0.32
04-08     0.31
04-24     0.39
05-10     0.40
05-26     0.40
06-11     0.37
06-27     0.33
07-13     0.29
Name: mean, dtype: float64

when I plot the timeseries i have this graph :

how can i plot all dataframes in the same plot with different colors?

I need something like this :

Answer 1

You can do both:

• plot all curves with one singel command, see: plt.plot()
• adress each singel curve to plot, see for-loop with plt.fill_between()
• if you have 2 DataFrames, say df1 and df2, then use plt.plot() twice: plt.plot(t,df1); plt.plot(t,df2); plt.show() plt.plot(t,df1); plt.plot(t,df2); plt.show()

import numpy as np
import pandas as pd
import matplotlib.pylab as plt

#--- generate data and DataFrame --
nt = 100
t= np.linspace(0,1,nt)*3*np.pi
y1 = np.sin(t); y2 = np.cos(t); y3 = y1*y2
df = pd.DataFrame({'y1':y1,'y2':y2,'y3':y3 })

#--- graphics ---
plt.style.use('fast')  
fig, ax0 = plt.subplots(figsize=(20,4))
plt.plot(t,df, lw=4, alpha=0.6);           # plot all curves with 1 command

for j in range(len(df.columns)):           # add on: fill_between for each curve
    plt.fill_between(t,df.values[:,j],label=df.columns[j],alpha=0.2)
plt.legend(prop={'size':15});plt.grid(axis='y');plt.show()

Answer 2

The answer

You can plot multiple dataframes on a single graph by capturing the Axes object that df.plot returns and then reusing it. Here's an example with two dataframes, df1 and df2 :

ax = df1.plot(x='dates', y='vals', label='val 1')
df2.plot(x='dates', y='vals', label='val 2', ax=ax)
plt.show()

Output:

Details

Here's the code I used to generate random example values for df1 and df2 :

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

def random_dates(start, end, n=10):
    if isinstance(start, str): start = pd.to_datetime(start)
    if isinstance(end, str): end = pd.to_datetime(end)

    start_u = start.value//10**9
    end_u = end.value//10**9
    return pd.to_datetime(np.random.randint(start_u, end_u, n), unit='s')

# generate two random dfs
df1 = pd.DataFrame({'dates': random_dates('2016-01-01', '2016-12-31'), 'vals': np.random.rand(10)})
df2 = pd.DataFrame({'dates': random_dates('2016-01-01', '2016-12-31'), 'vals': np.random.rand(10)})