I am using a bar chart to plot query frequencies, but I consistently see uneven spacing between the bars. These look like they should be related to to the ticks, but they're in different positions
This shows up in larger plots
And smaller ones
def TestPlotByFrequency (df, f_field, freq, description):
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.bar(df[f_field][0:freq].index,\
df[f_field][0:freq].values)
plt.show()
This is not related to data either, none at the top have the same frequency count
count
0 8266
1 6603
2 5829
3 4559
4 4295
5 4244
6 3889
7 3827
8 3769
9 3673
10 3606
11 3479
12 3086
13 2995
14 2945
15 2880
16 2847
17 2825
18 2719
19 2631
20 2620
21 2612
22 2590
23 2583
24 2569
25 2503
26 2430
27 2287
28 2280
29 2234
30 2138
Is there any way to make these consistent?
The space between bars can be added by using rwidth parameter inside the “plt. hist()” function. This value specifies the width of the bar with respect to its default width and the value of rwidth cannot be greater than 1.
To set width for bars in a Bar Plot using Matplotlib PyPlot API, call matplotlib. pyplot. bar() function, and pass required width value to width parameter of bar() function. The default value for width parameter is 0.8.
If graphs have different number of bars, Prism will change the width of the bars to fill in the specified width (length) of the X axis. The fewer bars you have, the wider they become to fit the range of the X axes length. The more bars you have, the shorter the width.
We can use the plt. subplots_adjust() method to change the space between Matplotlib subplots. The parameters wspace and hspace specify the space reserved between Matplotlib subplots. They are the fractions of axis width and height, respectively.
The problem has to do with aliasing as the bars are too thin to really be separated. Depending on the subpixel value where a bar starts, the white space will be visible or not. The dpi of the plot can either be set for the displayed figure or when saving the image. However, if you have too many bars increasing the dpi will only help a little.
As suggested in this post, you can also save the image as svg to get a vector format. Depending where you want to use it, it can be perfectly rendered.
import matplotlib
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
matplotlib.rcParams['figure.dpi'] = 300
t = np.linspace(0.0, 2.0, 50)
s = 1 + np.sin(2 * np.pi * t)
df = pd.DataFrame({'time': t, 'voltage': s})
fig, ax = plt.subplots()
ax.bar(df['time'], df['voltage'], width = t[1]*.95)
plt.savefig("test.png", dpi=300)
plt.show()
Image with 100 dpi:
Image with 300 dpi:
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