Plotting multiple bars with matplotlib using ax.bar()

Question

Following up my previous question: Sorting datetime objects by hour to a pandas dataframe then visualize to histogram

I need to plot 3 bars for one X-axis value representing viewer counts. Now they show those under one minute and above. I need one showing the overall viewers. I have the Dataframe but I can't seem to make them look right. With just 2 bars I have no problem, it looks just like I would want it with two bars:

The relevant part of the code for this:

# Time and date stamp variables
allviews = int(df['time'].dt.hour.count())
date = str(df['date'][0].date())
hours = df_hist_short.index.tolist()
hours[:] = [str(x) + ':00' for x in hours]

The hours variable that I use to represent the X-axis may be problematic, since I convert it to string so I can make the hours look like 23:00 instead of just the pandas index output 23 etc. I have seen examples where people add or subtract values from the X to change the bars position.

fig, ax = plt.subplots(figsize=(20, 5))
short_viewers = ax.bar(hours, df_hist_short['time'], width=-0.35, align='edge')
long_viewers = ax.bar(hours, df_hist_long['time'], width=0.35, align='edge')

Now I set the align='edge' and the two width values are absolutes and negatives. But I have no idea how to make it look right with 3 bars. I didn't find any positioning arguments for the bars. Also I have tried to work with the plt.hist() but I couldn't get the same output as with the plt.bar() function.

So as a result I wish to have a 3rd bar on the graph shown above on the left side, a bit wider than the other two.

"I didn't find any positioning arguments for the bars." - this is because you have complete control over the positions of the bars in the first argument (your hours). This seems like a weird hassle compared with something like Excel, until you try and create a bar chart with uneven spacing and unequal bar widths in Excel :/ — Dan
– Dan, Commented May 10, 2019 at 13:05

Dan · Accepted Answer · 2019-05-10 13:01:15Z

5

In pure matplotlib, instead of using the width parameter to position the bars as you've done, you can adjust the x-values for your plot:

import numpy as np
import matplotlib.pyplot as plt

# Make some fake data:
n_series = 3
n_observations = 5
x = np.arange(n_observations)
data = np.random.random((n_observations,n_series))


# Plotting:

fig, ax = plt.subplots(figsize=(20,5))

# Determine bar widths
width_cluster = 0.7
width_bar = width_cluster/n_series

for n in range(n_series):
    x_positions = x+(width_bar*n)-width_cluster/2
    ax.bar(x_positions, data[:,n], width_bar, align='edge')

In your particular case, seaborn is probably a good option. You should (almost always) try keep your data in long-form so instead of three separate data frames for short, medium and long, it is much better practice to keep a single data frame and add a column that labels each row as short, medium or long. Use this new column as the hue parameter in Seaborn's barplot

edited May 10, 2019 at 13:01

answered May 10, 2019 at 12:55

Dan

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2 Comments

midi Over a year ago

Thanks Dan for following up on this question too, much appreciated! I just got into the habit of using pandas for literally everything, I'm working on picking up the syntax so I would come up with solutions in dataframes rather than pure python. :)

Dan Over a year ago

Pandas is great, just don't split your DataFrames unnecessarily. Seaborn works very well with pandas. Lastly, unless you want a lot of control over the look of the charts, there's probably no reason for you to stick with the pure matplotlib method.

tmdavison · Accepted Answer · 2019-05-10 11:31:05Z

5

pandas will do this alignment for you, if you make the bar plot in one step rather than two (or three). Consider this example (adapted from the docs to add a third bar for each animal).

import pandas as pd
import matplotlib.pyplot as plt

speed = [0.1, 17.5, 40, 48, 52, 69, 88]
lifespan = [2, 8, 70, 1.5, 25, 12, 28]
height = [1, 5, 20, 3, 30, 6, 10]
index = ['snail', 'pig', 'elephant',
         'rabbit', 'giraffe', 'coyote', 'horse']
df = pd.DataFrame({'speed': speed,
                   'lifespan': lifespan,
                   'height': height}, index=index)
ax = df.plot.bar(rot=0)

plt.show()

answered May 10, 2019 at 11:31

tmdavison

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1 Comment

midi Over a year ago

Thanks for pointing me in directions! Actually I have tried out with this example from the docs a few times yesterday but now you reassured me that this is the direction, so I pushed a little harder. The problem was obvious, and this simple and pragmatic solution worked after I converted my dataframe slices to lists.

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