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In [1]:
import matplotlib.pyplot as plt
import pandas
data=pandas.read_csv('Advertising_data.csv')
data.head()
Out[1]:
In [97]:
#Age
#Purchased
#EstimatedSalary
X1=data['EstimatedSalary']
X2=data['Age']
y=data['Purchased']In [98]:
plt.scatter(X1,X2,c=y)
plt.show()
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In [75]:
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.decomposition import PCA as sklearnPCA
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
from sklearn.datasets.samples_generator import make_blobs
from pandas.tools.plotting import parallel_coordinatesIn [76]:
X, y = make_blobs(n_samples=200, centers=3, n_features=3, random_state=0)
X[:,0]
Out[76]:
array([ 0.31516585, 1.88178095, -0.84444675, -0.49352946, -0.27461614,
0.20050773, -2.4363981 , 0.64321268, 0.26802175, 1.6904939 ,
1.02616849, 1.94129325, 1.92980864, 2.08493453, -1.30118956,
-0.19811382, -1.04964926, -2.17839577, 0.97052064, 1.62747942,
-0.55709073, 2.09220853, 0.29221083, -1.94613952, 0.40957246,
0.11599596, 1.81398984, 0.41198749, 1.60847149, -2.40005384,
1.91616706, 1.81136947, 1.90373658, -1.00960179, -2.40116503,
1.839498 , 1.59503648, 2.42110579, 1.13692862, 1.00970901,
-0.30052305, -3.5358957 , 0.04811089, 0.03787294, -0.76985089,
1.90690819, -2.60795281, -1.49675174, 0.68977921, -0.20453243,
0.30124825, 1.02317454, 0.15804912, -2.99059289, 1.26331511,
1.46469655, 2.17004979, 0.78276481, 1.32574461, 0.10770002,
-1.23031732, 0.54605398, -1.02592163, -0.59375765, 1.33669735,
-1.15479631, 0.51517745, -0.54141339, 2.45225991, 0.49685028,
-3.71777886, 1.32455968, 0.50466574, 1.71713027, 2.81901062,
1.39017006, 0.7927672 , -1.18271996, 0.74913678, 1.44841908,
-3.06502844, -0.38851046, -1.05404913, -0.39597062, 1.96549724,
0.514242 , 2.81996161, -1.34568581, 2.03549053, 1.73718012,
0.32411974, -1.12370913, 0.63599159, 1.10267675, 1.08020599,
0.79468751, 2.05708199, 0.7856141 , 0.64423968, 0.66890527,
-0.0146332 , 1.08461963, -1.38527578, 1.47746246, -0.1632272 ,
-0.44549307, 1.09112396, -3.1626634 , -0.35497942, -1.2334963 ,
-1.32023781, -2.60145572, 1.02961499, 1.25146839, -1.16211747,
1.05965318, 0.98777645, -0.42982027, -3.05856275, -2.79131221,
-2.63368589, 0.75033042, -0.03516817, 2.71652354, 0.01220672,
0.29749269, 0.61613731, 1.94986879, -2.85364968, -1.38260202,
0.83903766, -0.82772206, 1.22480071, 0.39459708, 0.40675281,
1.58737379, 1.34638254, 0.76714146, -0.52529231, 2.00528834,
2.50049689, 0.77904754, -1.52559872, 0.4253917 , 1.10473923,
-0.33292946, 0.68764686, 0.99585035, 0.89189476, 2.24238861,
1.19852998, 0.6399999 , -1.212813 , -1.37757259, 2.51129921,
1.83450786, -1.16927747, 2.98210535, 0.56264262, 0.32656157,
-0.3963238 , -0.45254962, 1.40068254, -0.10200792, 1.96191334,
0.10147782, 0.39959056, 0.92180523, 1.35343069, -1.76270127,
2.27696635, 0.70224646, 0.40366931, 1.82725799, -0.01389006,
-1.59187303, 1.29624939, 3.99919424, 2.18363622, -2.18806121,
-1.66996165, 2.40553958, -1.55435561, -0.10953052, 0.51834766,
-0.36955718, -1.12195202, 1.72723475, 2.76743854, 0.04407919,
-1.37554022, 1.945249 , -1.05283555, -2.76327092, -0.92431418,
-2.02184254, -1.65048059, 0.66647695, 0.78008887, 0.3904472 ])In [77]:
#plt.scatter(X[:,0], X[:,1], c=y)
plt.scatter(X[:,2],X[:,0],c=y)
plt.show()
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import jovian
jovian.commit()
[jovian] Saving notebook..
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