Given the following bar chart:
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
df = pd.DataFrame({'A': ['A', 'B'], 'B': [1000,2000]})
fig, ax = plt.subplots(1, 1, figsize=(2, 2))
df.plot(kind='bar', x='A', y='B',
align='center', width=.5, edgecolor='none',
color='grey', ax=ax)
plt.xticks(rotation=25)
plt.show()
I'd like to display the y-tick labels as thousands of dollars like this:
$2,000
I know I can use this to add a dollar sign:
import matplotlib.ticker as mtick
fmt = '$%.0f'
tick = mtick.FormatStrFormatter(fmt)
ax.yaxis.set_major_formatter(tick)
...and this to add a comma:
ax.get_yaxis().set_major_formatter(
mtick.FuncFormatter(lambda x, p: format(int(x), ',')))
...but how do I get both?
Thanks in advance!
We can add dollar symbol to the salary values on x-axis using set_major_formatter() function in Matplotlib on the axis of interest. In this example, since we want to add dollar sign to x-axis ticks, we use xaxis. set_major_formatter() with the argument for formatting string.
Locator_params() function that lets us change the tightness and number of ticks in the plots. This is made for customizing the subplots in matplotlib, where we need the ticks packed a little tighter and limited. So, we can use this function to control the number of ticks on the plots.
Matplotlib removes both labels and ticks by using xticks([]) and yticks([]) By using the method xticks() and yticks() you can disable the ticks and tick labels from both the x-axis and y-axis. In the above example, we use plt.
You can use StrMethodFormatter
, which uses the str.format()
specification mini-language.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as mtick
df = pd.DataFrame({'A': ['A', 'B'], 'B': [1000,2000]})
fig, ax = plt.subplots(1, 1, figsize=(2, 2))
df.plot(kind='bar', x='A', y='B',
align='center', width=.5, edgecolor='none',
color='grey', ax=ax)
fmt = '${x:,.0f}'
tick = mtick.StrMethodFormatter(fmt)
ax.yaxis.set_major_formatter(tick)
plt.xticks(rotation=25)
plt.show()
You can also use the get_yticks()
to get an array of the values displayed on the y-axis (0, 500, 1000, etc.) and the set_yticklabels()
to set the formatted value.
df = pd.DataFrame({'A': ['A', 'B'], 'B': [1000,2000]})
fig, ax = plt.subplots(1, 1, figsize=(2, 2))
df.plot(kind='bar', x='A', y='B', align='center', width=.5, edgecolor='none',
color='grey', ax=ax)
--------------------Added code--------------------------
# getting the array of values of y-axis
ticks = ax.get_yticks()
# formatted the values into strings beginning with dollar sign
new_labels = [f'${int(amt)}' for amt in ticks]
# Set the new labels
ax.set_yticklabels(new_labels)
-------------------------------------------------------
plt.xticks(rotation=25)
plt.show()
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