Im doing some analytics using python 3.5 and anaconda. in K means Clustering pyt
ID: 3896080 • Letter: I
Question
Im doing some analytics using python 3.5 and anaconda.
in K means Clustering python will not recognise ggplot, even after importing.
any alternatives to ggplot?
this is my code
import pandas as pd
import numpy as np
from sklearn.cluster import KMeans
from sklearn.decomposition import PCA
from ggplot import aes
from ggplot import *
data = pd.read_csv(r'C:UsersuserAnaconda3envsssignland-area-population-density-london.csv')
data.columns = ["Codes","Ward names" ,"Borough", "Hectares", "Square Kilometres", "Population 2015", "Population per hectare 2015", "Population per square kilometre 2015",
"Census population(2011)", "Population per hectare 2011"]
#creating a matrix table
matrix = data.pivot_table(index=['Ward names'], columns=['Borough','Population per hectare 2015', 'Population per hectare 2011'])
print(matrix)
matrix = matrix.fillna(0).reset_index()
x_cols = matrix.columns[1:]
cluster = KMeans(n_clusters=5)
matrix['cluster']= cluster.fit_predict(matrix[matrix.columns[3:]])
pca = PCA(n_components=2)
matrix['x'] = pca.fit_transform(matrix[x_cols])[:,0]
matrix['y'] = pca.fit_transform(matrix[x_cols])[:,1]
matrix = matrix.reset_index()
customer_clusters = matrix [['Ward names', 'cluster', 'x', 'y']]
#works up to here
g = ggplot(data, aes(x='x', y='y',color='cluster')) +
geom_point(size=75) +
ggtitle("Clustering based on Area")
Explanation / Answer
The alternative to ggplot is matplotlib.
matplotlib is widely use to from plot, graph etc..
Scatter plot is most commonaly use to form a cluster.
import matplotlib.pyplot.scatter
Syntax:
matplotlib.pyplot.scatter(x, y, s=None, c=None, marker=None, cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, verts=None, edgecolors=None, hold=None, data=None, **kwargs)
Parameters:
x, y : shape of array(n, )
s : scalar
c : color
marker : MarkerStyle
cmap : Colormap
norm : Normalize
vmin, vmax : scalar
alpha : scalar, values from 0 to 1
linewidths: width of line
verts : sequence of (x, y)
edgecolors : color of edge
Example: