Dhrumilcse

from sklearn.preprocessing import StandardScaler
scaler = StandardScaler()
X_train = scaler.fit_transform(X_train)
X_test = scaler.transform(X_test)

Dhrumilcse

from sklearn.model_selection import train_test_split

X = df.iloc[:, 1:10]
Y = df.iloc[:, 10]

X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size = 0.2, random_state = 0)

Dhrumilcse

df[10] = df[10].replace(2,0).replace(4,1)
print(df)

Dhrumilcse

import pandas as pd
from google.colab import files
file = files.upload()
data = pd.read_csv("breastCancer.csv", header = None)

Dhrumilcse

df = pd.DataFrame(data)
df[6] = df[6].replace('?',0)
df[6] = df[6].astype(int)
print(df.dtypes)

mean = int(df[6].mean())
df[6] = df[6].replace(0,mean)
print(df)

Dhrumilcse

#Import libraries
from pandas_datareader import data
import datetime
from bokeh.plotting import figure, show, output_file

#Define time-frame
start_time = datetime.datetime(2018,10,1)
end_time = datetime.datetime(2018,10,9)

#Fetch the data

Dhrumilcse

#Import libraries
from pandas_datareader import data
import datetime
from bokeh.plotting import figure, show, output_file

#Define time-frame
start_time = datetime.datetime(2018,10,1)
end_time = datetime.datetime(2018,10,9)

#Fetch the data

Dhrumilcse

#Import libraries
from pandas_datareader import data
import datetime
from bokeh.plotting import figure, show, output_file

#Define time-frame
start_time = datetime.datetime(2018,10,1)
end_time = datetime.datetime(2018,10,9)

#Fetch the data

Dhrumilcse

#Import libraries
from pandas_datareader import data
import datetime
from bokeh.plotting import figure, show, output_file

#Define time-frame
start_time = datetime.datetime(2018,10,1)
end_time = datetime.datetime(2018,10,9)

#Fetch the data

Dhrumilcse

#Import libraries
from pandas_datareader import data
import datetime

#Define time-frame
start_time = datetime.datetime(2018,10,1)
end_time = datetime.datetime(2018,10,9)

#Fetch the data
df = data.DataReader(name="TSLA",data_source="yahoo", start = start_time, end = end_time)