Matplotlib scatters color by categorical factors

Question

I have a basic spread, where x and y are float. But I want to change the color of the marker based on the third categorical variable. The categorical variable is in string form. This seems to be causing the problem.

To use the aperture diaphragm set - here is the code that I think I would use:

#Scatter of Petal
x=df['Petal Length']
y=df['Petal Width']
z=df['Species']
plt.scatter(x, y, c=z, s=15, cmap='hot')
plt.xlabel('Petal Width')
plt.ylabel('Petal Length')
plt.title('Petal Width vs Length')

But I get an error: cannot convert string to float: iris-setosa

Should I change the categorical variable to a numeric one before launching, or can I do something with the data in its current format?

thank

: whole trace:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-47-d67ee3bffc3b> in <module>()
      3 y=df['Petal Width']
      4 z=df['Species']
----> 5 plt.scatter(x, y, c=z, s=15, cmap='hot')
      6 plt.xlabel('Petal Width')
      7 plt.ylabel('Petal Length')

/Users/mpgartland1/anaconda/lib/python2.7/site-packages/matplotlib/pyplot.pyc in scatter(x, y, s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, verts, hold, **kwargs)
   3198         ret = ax.scatter(x, y, s=s, c=c, marker=marker, cmap=cmap, norm=norm,
   3199                          vmin=vmin, vmax=vmax, alpha=alpha,
-> 3200                          linewidths=linewidths, verts=verts, **kwargs)
   3201         draw_if_interactive()
   3202     finally:

/Users/mpgartland1/anaconda/lib/python2.7/site-packages/matplotlib/axes/_axes.pyc in scatter(self, x, y, s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, verts, **kwargs)
   3605 
   3606         if c_is_stringy:
-> 3607             colors = mcolors.colorConverter.to_rgba_array(c, alpha)
   3608         else:
   3609             # The inherent ambiguity is resolved in favor of color

/Users/mpgartland1/anaconda/lib/python2.7/site-packages/matplotlib/colors.pyc in to_rgba_array(self, c, alpha)
    420             result = np.zeros((nc, 4), dtype=np.float)
    421             for i, cc in enumerate(c):
--> 422                 result[i] = self.to_rgba(cc, alpha)
    423             return result
    424 

/Users/mpgartland1/anaconda/lib/python2.7/site-packages/matplotlib/colors.pyc in to_rgba(self, arg, alpha)
    374         except (TypeError, ValueError) as exc:
    375             raise ValueError(
--> 376                 'to_rgba: Invalid rgba arg "%s"\n%s' % (str(arg), exc))
    377 
    378     def to_rgba_array(self, c, alpha=None):

ValueError: to_rgba: Invalid rgba arg "Iris-setosa"
to_rgb: Invalid rgb arg "Iris-setosa"
could not convert string to float: iris-setosa

Answer 1

, . , , .

: http://matplotlib.org/api/pyplot_api.html?highlight=plot#matplotlib.pyplot.plot

, , ( : https://raw.githubusercontent.com/pydata/pandas/master/pandas/tests/data/iris.csv):

import matplotlib.pyplot as plt
import matplotlib.colors as colors
import matplotlib.cm as cmx
from pandas import read_csv

df = read_csv('iris.csv')

#Scatter of Petal
x=df['PetalLength']
y=df['PetalWidth']

# Get unique names of species
uniq = list(set(df['Name']))

# Set the color map to match the number of species
z = range(1,len(uniq))
hot = plt.get_cmap('hot')
cNorm  = colors.Normalize(vmin=0, vmax=len(uniq))
scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=hot)

# Plot each species
for i in range(len(uniq)):
    indx = df['Name'] == uniq[i]
    plt.scatter(x[indx], y[indx], s=15, color=scalarMap.to_rgba(i), label=uniq[i])

plt.xlabel('Petal Width')
plt.ylabel('Petal Length')
plt.title('Petal Width vs Length')
plt.legend(loc='upper left')
plt.show()

- :

: .

Answer 2

Altair .

from altair import *
import pandas as pd

df = datasets.load_dataset('iris')
Chart(df).mark_point().encode(x='petalLength',y='sepalLength', color='species')

Answer 3

@jonnybazookatone, . groupby Dataframe Name name_id. , ...

import matplotlib
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import matplotlib.cm as cmx
from pandas import read_csv

df = read_csv('iris.csv')

# map Name to integer
pos = df.loc[:,["Name"]].groupby("Name").count().reset_index()

# create a new column in the dataframe which contains the numeric value
tag_to_index = lambda x: pos.loc[pos.Name == x.Name].index[0]
df.loc[:,"name_index"]=df.loc[:,["Name"]].apply(tag_to_index, axis=1)

# Set the color map to match the number of species
hot = plt.get_cmap('hot')
cNorm  = colors.Normalize(vmin=0, vmax=len(pos))
scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=hot)

# Get unique names of species
for (name, group) in df.groupby("name_index"):
    plt.scatter(group.PetalWidth, group.PetalLength, s=15, label=pos.iloc[name].get("Name"), color=scalarMap.to_rgba(name))

plt.xlabel('Petal Width')
plt.ylabel('Petal Length')
plt.title('Petal Width vs Length')
plt.legend()
plt.show()