Lineplot with Seaborn and ci=“sd” function in Python

Question

I'm trying to produce some snazzy charts in seaborn and need some help.

I have some stock data, consisting of 5 stocks. I'm basically trying to visually display how Stock A has performed in comparison to the others. To do this I am looking at cumulative returns, and have also calculated the average cumulative returns for the other 4 stocks. I have split this data up in to the following 2 df :

Stock A's data let's call df :

Date              Stock A               
2019-04-24 07:59  0.433366
2019-04-24 08:59  0.397984
2019-04-24 09:59  0.403971
2019-04-24 10:59  0.399131
2019-04-24 11:59  0.386641
2019-04-24 12:59  0.388572
2019-04-24 13:59  0.396266
2019-04-24 14:59  0.391609
2019-04-24 15:59  0.399412
2019-04-24 16:59  0.401715

And then Stocks B, C, D & E, PLUS the calculated average let's call df2 (I can't print all 5 columns):

Date              Stock B   Stock C    Stock E   Average                                             
2019-04-24 07:59  0.273965  0.000982    0.409717  0.472029
2019-04-24 08:59  0.235606  -0.076309   0.345047  0.407299
2019-04-24 09:59  0.240826  -0.059274   0.346769  0.413197
2019-04-24 10:59  0.234849  -0.056013   0.338185  0.407962
2019-04-24 11:59  0.230158  -0.062947   0.331907  0.397927
2019-04-24 12:59  0.237573  -0.055506   0.334907  0.412206
2019-04-24 13:59  0.239994  -0.047875   0.334213  0.413846
2019-04-24 14:59  0.230461  -0.059781   0.312962  0.395924
2019-04-24 15:59  0.236968  -0.054398   0.320990  0.406967
2019-04-24 16:59  0.239918  -0.049522   0.328713  0.412818

What I am ultimately looking to do is chart all 5 stocks plus the average on one graph, that has a nice grey background and perhaps some grid lines etc (at the minute I can only chart with ugly white backgrounds), but I would like the line for Stock A and for Average to be slightly different and make use of seaborns standard deviation line plot.

I found this example code sns.relplot(x="timepoint", y="signal", kind="line", ci="sd", data=fmri) but when I tried to alter it to my needs I got error messages and couldn't get all the data to appear on the same chart.

Here is a near perfect example of what I'm aiming for, but I would like to include Stock B, C, D & E from df2 and change the axis labeling of course.

Any help greatly appreciated. Cheers

Answer 1

This should produce what you asked for:

sns.set() #This sets the style to the seaborn default (gray background with white grid on)
fig,ax = plt.subplots() #create your figure and ax objects
sns.lineplot('Date', 'Stock A', ci="sd", data=df,ax=ax) #plot lines
sns.lineplot('Date', 'Stock B', ci="sd", data=df2,ax=ax)
sns.lineplot('Date', 'Stock C', ci="sd", data=df2,ax=ax)
sns.lineplot('Date', 'Stock E', ci="sd", data=df2,ax=ax)
sns.lineplot('Date', 'Average', ci="sd", data=df2,ax=ax)
plt.xticks(rotation=-45) #makes ticks visible (a long date would be unreadable otherwise)

EDIT

Answering OP questions from comments:

Transform your dates from strings to datetime objects, then matplotlib will take care of the ticks and tickslabels .
As they are right now they are interpreted as strings and they all get plotted.

df['Date']=pd.to_datetime(df['Date'])
df2['Date']=pd.to_datetime(df2['Date'])

Use the following line to change the ylabel

ax.set_ylabel('Returns')