Why is only one hatch used in the bar graph? - pandas

Question

I have the following bar graph generated using pandas. My problem is all the bars have the same pattern. I have tried many approaches but could not manage to get around this issue.
Moreover, only one entry(for the last subplot) is shown in the legend.
The data used is
The code is :
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.ticker import ScalarFormatter
class ScalarFormatterForceFormat(ScalarFormatter):
def _set_format(self): # Override function that finds format to use.
self.format = "%1.1f" # Give format here
patterns = [ "\\" , "/" , "-","+" ,"x", "|", '.', "O" ]
yfmt = ScalarFormatterForceFormat()
yfmt.set_powerlimits((0, 0))
bar_gap=0.005
bar_width=0.01
bar_pos = [0 for i in range(5)]
bar_pos[0]=bar_gap
for i in range(1,5):
bar_pos[i]=bar_pos[i-1]+bar_gap+bar_width
colors = ['tab:blue', 'tab:green', 'tab:orange', 'tab:red','tab:olive']
patterns = [ "\\" , "/" , "+" , "-", ".", "*","x", "o", "O" ]
# file_locn = ''r'C:\Users\girum\Desktop\Throughput.csv'''
file_locn = ''r'my_file.csv'''
df = pd.read_csv(file_locn,index_col='Set')
df=df.T
fig, axes = plt.subplots(1,3,figsize=(8,5))#,sharey=True)
for i in range(3):
axes[i].yaxis.set_major_formatter(yfmt)
df.Type_A.plot(ax=axes[0],kind='bar',color=colors)
df.Type_B.plot(ax=axes[1],kind='bar',color=colors)
df.Type_C.plot(ax=axes[2],kind='bar',color=colors)
handles, labels = axes[0].get_legend_handles_labels()
for ax in fig.axes:
bars = ax.patches
hatches = ''.join(h*len(df) for h in patterns)
for bar, hatch in zip(bars, hatches):
bar.set_hatch(2*hatch)
plt.xticks(rotation=360)
axes[0].set_ylabel('Speed')
for i in range(len(df)):
axes[i].set_xlabel('')#Why is this line not working
axes[i].tick_params(axis='x', rotation=360)
plt.legend(loc='center right', bbox_to_anchor=(.2,1.08), ncol=1)
plt.show()

Answer 1

The code below has the following changes:
added some dummy test data to enable stand-alone test code
removed some unused variables
used the unaltered ScalarFormatter
only one loop through the axes and avoiding the plt interface
using ax.containers[0] to catch the bar container (ax.patches is a list of the rectangles, without the surrounding container)
change the label of the bar container to _no_legend, so it doesn't appear in the legend
used the patterns directly instead of concatenating them
removed h*len(df); note that multiplying a string such as '/' by e.g. 4, repeats the string (to '////'); repeated patterns are used in matplotlib to make the base pattern denser
used tick_params(axis='x', labelbottom=False, length=0) to remove the tick labels
added labels to the individual bars so they appear into the legend
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import ScalarFormatter
yfmt = ScalarFormatter()
yfmt.set_powerlimits((-9, 9))
colors = ['tab:blue', 'tab:green', 'tab:orange', 'tab:red', 'tab:olive']
patterns = ["\\", "/", "+", "-", ".", "*", "x", "o", "O"]
df = pd.DataFrame(np.random.randint(100000, 500000, (3, 3)),
columns=['A', 'B', 'C'],
index=['Type_A', 'Type_B', 'Type_C'])
df = df.T
fig, axes = plt.subplots(1, 3, figsize=(8, 5))
df.Type_A.plot(ax=axes[0], kind='bar', color=colors)
df.Type_B.plot(ax=axes[1], kind='bar', color=colors)
df.Type_C.plot(ax=axes[2], kind='bar', color=colors)
for ax in axes:
bars = ax.containers[0]
bars.set_label('_no_legend')
hatches = [h * 2 for h in patterns]
for bar, hatch, label in zip(bars, hatches, df.index):
bar.set_hatch(2 * hatch)
bar.set_label(label)
ax.yaxis.set_major_formatter(yfmt)
ax.tick_params(axis='x', labelbottom=False, length=0)
axes[0].set_ylabel('Speed')
axes[2].legend(loc='lower right', bbox_to_anchor=(1, 1.01), ncol=3)
plt.tight_layout()
plt.show()

Answer 2

The lines where you are joining the patterns generates a result, which you don't want.
patterns = [ "\\" , "/" , "+" , "-", ".", "*","x", "o", "O" ]
hatches = ''.join(h*3 for h in patterns)
>>> '\\\\\\///+++---...***xxxoooOOO'
# if you have the bars, this is the output
for bar, hatch in zip([0,1,3], hatches):
print(2*hatch)
>>>
\\
\\
\\
Try to simplify this section using the patterns in your loop directly:
for bar, hatch in zip([0,1,3], patterns):
print(2*hatch)`
>>>
\\
//
++
Output
I used your given code and data to create this output.