Join seaborn stripplot with line plot using pandas groupby mean values

Question

I am working on plot with seaborn and want to plot two graphs in one figure.

data frame likes below.

        liquidity   lcindex
86493   0.611899    decline
86494   0.585814    revival
86495   0.553165    revival
86496   0.527779    revival
86497   0.521026    mature
86498   0.530813    decline
86499   0.530970    decline
86500   0.564019    revival
86501   0.564535    mature
86502   0.529418    start
86503   0.584290    start
86504   0.550692    start
86505   0.529517    start
86506   0.520906    start
86507   0.535492    revival
86508   0.653324    decline
86509   0.549327    revival
86510   0.528509    revival
86511   0.531548    revival
86512   0.555610    revival
86513   0.517208    decline
86514   0.516283    decline
86515   0.510123    mature
86516   0.512255    revival
86517   0.700632    mature
86518   0.505878    revival
86519   0.551810    revival
86520   0.812280    revival
86521   0.733664    decline
86522   0.714617    decline

first graph is below.

sns.stripplot(x="lcindex", y="liquidity", data=finaldf, jitter = True)

and I want to add line plot for mean value of liquidity by every x-values. I can obtain those values by

finaldf.groupby('lcindex')['liquidity'].mean().plot()

       lcindex
decline    0.557899
growth     0.553409
mature     0.556915
revival    0.559233 
start      0.585221

and plot like this

if I plot together the figure cropped the both edge side of plots but I want the graph looks like first graph and add lines.

ax1 = sns.stripplot(
    x="lcindex", y="liquidity", data=finaldf, jitter=True,
    palette="husl", 
    order=['start','growth','mature','revival','decline']
)

finaldf.groupby('lcindex')['liquidity'].mean().plot()
ax1.set_title ('title',fontsize=35)
ax1.set(xlabel='Life cycle Index', ylabel='Liquidity Index')
ax1.set(xticks=range(0, 5), xticklabels=["Start-up",'Growth', 'Mature', 'Revival',"Decline"])

How I can do it?

Answer 1

You should be able to set the xlimits as usual

ax1.set_xlim(-0.5, 4.5)

Answer 2

Not exactly answering your question, but an alternative way to visualise your datapoints together with the means could be to draw your strip plot on top of a violin or box plot as in the last examples on http://seaborn.pydata.org/generated/seaborn.stripplot.html:

>>> ax = sns.boxplot(x="tip", y="day", data=tips, whis=np.inf)
>>> ax = sns.stripplot(x="tip", y="day", data=tips,
...                    jitter=True, color=".3")