Bar format (kind) is not displaying the right plot (matplotlib)

Question

I need to do a plot using three variables. One of them should be on the secondary Y axis in bar format (kind), the remaining variables (two) should be on the left axis using a simple line. However, I got the following chart:

When I use the three variables in line format I get the right plot (which is not very useful for a visual analysis):

I did a quick test using a small sample from my data (code below). I get the right pic when I use bar format for the third one.

I wonder, what is going on? Is there a problem with the data size (which I dont think so bcs I get less than 100 rows)?

df2 = pd.DataFrame({'ind':[120.29, 125.45, 127.37, 130.39, 128.30], 
                    'var1':[129.907990, 129.571185, 129.234380, 128.897574, 128.560769], 
                    'var2':[-0.074037, -0.031806, -0.014426, 0.011578, -0.002028]})

fig, ax1 = plt.subplots()
ax2 = ax1.twinx()
df2['ind'].plot(ax=ax1)
df2['var1'].plot(ax=ax1)
df2['var2'].plot(kind='bar', ax=ax2, color='r')
plt.show()

PD: In addition, I noted that in the third pic the line is behind the bar. How can I change that?

A pandas bar plot is a categorical plot; you get one tick and label per bar. I suppose you can google for something like "pandas plot line and bar in same chart" or so to find an appropriate duplicate Q&A. — ImportanceOfBeingErnest
– ImportanceOfBeingErnest, Commented Feb 28, 2019 at 15:05
I can't reproduce the behavior shown, can you post the code you used to create the first plot? — William Miller
– William Miller, Commented Feb 28, 2019 at 18:32

Pithit · Accepted Answer · 2019-03-01 18:59:38Z

1

I found the solution for this (this link helped me a lot ). Basically, it is based on the index you set up previously.

This is the new code:

fig, ax1 = plt.subplots()
ax2 = ax1.twinx()
ax1.plot(df2.index, df2['ind']) 
ax1.plot(df2.index, df2['var1'])
ax2.bar(df2.index, df2['var2'], color='r')
plt.show()

Hope this helps.

edited Mar 1, 2019 at 18:59

answered Mar 1, 2019 at 18:54

Pithit

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