I have the next plot but as you can see, its impossible to see the upright part. So I wanna know what I can do to see the entire plot and reduce his size. The code is from another user of Stack.
Thank you.
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
def _scale_data(data, ranges):
"""scales data[1:] to ranges[0],
"""
for d, (y1, y2) in zip(data[1:], ranges[1:]):
assert (y1 <= d <= y2) or (y2 <= d <= y1)
x1, x2 = ranges[0]
d = data[0]
sdata = [d]
for d, (y1, y2) in zip(data[1:], ranges[1:]):
sdata.append((d-y1) / (y2-y1)
* (x2 - x1) + x1)
return sdata
class ComplexRadar():
def __init__(self, fig, variables, ranges,
n_ordinate_levels=6):
angles = np.arange(0, 360, 360./len(variables))
axes = [fig.add_axes([0.1,0.1,0.9,0.9],polar=True,
label = "axes{}".format(i))
for i in range(len(variables))]
l, text = axes[0].set_thetagrids(angles,
labels=variables)
[txt.set_rotation(angle-90) for txt, angle
in zip(text, angles)]
for ax in axes[1:]:
ax.patch.set_visible(False)
ax.grid("off")
ax.xaxis.set_visible(False)
for i, ax in enumerate(axes):
grid = np.linspace(*ranges[i],
num=n_ordinate_levels)
gridlabel = ["{}".format(round(x,2))
for x in grid]
if ranges[i][0] > ranges[i][1]:
grid = grid[::-1] # hack to invert grid
# gridlabels aren't reversed
gridlabel[0] = "" # clean up origin
ax.set_rgrids(grid, labels=gridlabel,
angle=angles[i])
#ax.spines["polar"].set_visible(False)
ax.set_ylim(*ranges[i])
# variables for plotting
self.angle = np.deg2rad(np.r_[angles, angles[0]])
self.ranges = ranges
self.ax = axes[0]
def plot(self, data, *args, **kw):
sdata = _scale_data(data, self.ranges)
l = self.ax.plot(self.angle, np.r_[sdata, sdata[0]], *args, **kw)
return l
def fill(self, data, *args, **kw):
sdata = _scale_data(data, self.ranges)
self.ax.fill(self.angle, np.r_[sdata, sdata[0]], *args, **kw)
index = ["Carl","Michael","Peter","Louis","Sarah", "Laura","Nicholas"]
df = pd.DataFrame({
"Spe": pd.Series([89, 83, 70, 60, 30, 49, 28]),
"Str": pd.Series([69, 53, 30, 20, 10, 29, 48]),
"Det": pd.Series([82, 44, 79, 39, 20, 10, 85]),
"Extr": pd.Series([59, 74, 29, 36, 18, 29, 18]),
"Int": pd.Series([63, 11, 20, 36, 97, 58, 91]),
"Est": pd.Series([12, 69, 89, 59, 19, 58, 98]),
"Ape": pd.Series([29, 13, 94, 30, 20, 10, 67]),
})
variables = [k[0] for k in df.iteritems()]
ranges = [(1.,100.),(1.,100.),(1.,100.),(1.,100.),(1.,100.),(1.,100.),(1.,100.)]
fig1 = plt.figure(figsize=(8, 8))
radar = ComplexRadar(fig1, variables, ranges)
lax = []
for i, name in enumerate(index):
data=df.iloc[i].values
l, = radar.plot(data, label=name)
lax.append(l)
radar.fill(data,alpha=0.2)
legendax = fig1.add_axes([0.8,0.8,0.1,.1])
legendax.legend(handles = lax, labels=index, loc=3, bbox_to_anchor=(0,0,1,1), bbox_transform=fig1.transFigure )
legendax.axis('off')
sns.plt.show()
The size of the figure is determined by fig1 = plt.figure(figsize=(8, 8)), so it's 8x8 inches here. You can reduce the size by changing the values according to your needs.
The size of the plot inside the figure is determined by
fig.add_axes([0.1,0.1,0.9,0.9])
This command means that you add an axes with parameters [left, bottom, width, height]. So reducing the width and height will decrease the plot size. Try e.g. fig.add_axes([0.1,0.1,0.7,0.7]) or any other values you like.
