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Machine Learning Tutorials

Seaborn Barplot Method 0

Machine Learning Tutorials

Seaborn Barplot Method

Program 1 Seaborn Dataset import pandas as pd import numpy as np import seaborn as sns df_tip=pd.read_csv(“D://scikit_data/Billing/tips.csv”) df_tip.head() df_tip.shape df_tip.info() df_tip.isnull().sum() sns.barplot(x=’day’,y=’total_bill’,hue=’sex’,data=df_tip,hue_order=[‘Male’,’Female’]) sns.barplot(x=’day’,y=’total_bill’,hue=’sex’,hue_order=[‘Male’,’Female’],order=[‘Thur’,’Fri’,’Sat’,’Sun’],data=df_tip) sns.barplot(x=’day’,y=’total_bill’,hue=’sex’,data=df_tip) sns.barplot(x=’day’,y=’total_bill’,hue=’sex’,data=df_tip,ci=12) sns.barplot(x=’day’,y=’total_bill’,hue=’sex’,data=df_tip,orient=’h’) sns.barplot(y=’day’,x=’total_bill’,hue=’sex’,data=df_tip) sns.barplot(x=’size’,y=’total_bill’,hue=’sex’,data=df_tip,orient=’v’) sns.barplot(x=’size’,y=’total_bill’,hue=’sex’,data=df_tip,color=’b’) sns.barplot(x=’size’,y=’total_bill’,hue=’sex’,data=df_tip,palette=’Accent’)      

Digits Prediction in Logistic Regression in ML 0

Machine Learning Tutorials

Digits Prediction in Logistic Regression in ML

Program 1 import matplotlib.pyplot as plt from sklearn.datasets import load_digits digits=load_digits() digits dir(digits) digits.images[0] plt.gray() plt.matshow(digits.images[9]) plt.show() for i in range(9): plt.matshow(digits.images[i]) digits.target[:10] from sklearn.model_selection import train_test_split x_train,x_test,y_train,y_test=train_test_split(digits.data,digits.target,test_size=0.2) x_train x_test from sklearn.linear_model import LogisticRegression...

How to Split a Dataset into Train and Test Sets in Machine Learning 0

Machine Learning Tutorials

How to Split a Dataset into Train and Test Sets in Machine Learning

Program 1 Machine Learning Dataset import matplotlib.pyplot as plt import pandas as pd import numpy as np df=pd.read_csv(“D:\scikit_data\cardata\carprices.csv”) df.head(5) df=df.rename(columns={‘Age(yrs)’:’Age’}) df=df.rename(columns={‘Sell Price($)’:’SellPrice’}) df.head(5) plt.scatter(df[‘Mileage’],df[‘SellPrice’],color=’red’) plt.scatter(df[‘Age’],df[‘SellPrice’],color=’red’) from sklearn.model_selection import train_test_split x=df[[‘Mileage’,’Age’]] y=df[[‘SellPrice’]] # x_train—> Training...

Seaborn Heatmap Method 0

Machine Learning Tutorials

Seaborn Heatmap Method

Program 1 Seaborn Dataset # Heat Map Plot import seaborn as sns import matplotlib.pyplot as plt import numpy as np import seaborn as sns import pandas as pd # array_2d=np.linspace(1,7,15).reshape(5,3) # #print(array_2d) # sns.heatmap(array_2d)...

Seaborn Scatterplot Method 0

Machine Learning Tutorials

Seaborn Scatterplot Method

Program 1 import seaborn as sns import matplotlib.pyplot as plt import numpy as np import seaborn as sns df_tips=sns.load_dataset(‘tips’) print(df_tips.info()) plt.figure(figsize=(15,10)) sns.scatterplot(x=”total_bill”,y=”tip”,hue=’time’,style=’smoker’,data=df_tips) plt.title(“Scatter plot of Bill vs Tip”) plt.xlabel(“Total Bill”) plt.ylabel(“Tip”) plt.show() Program 2...

Seaborn ECDF Plot Method 0

Machine Learning Tutorials

Seaborn ECDF Plot Method

Program 1 Seaborn Dataset 1 Seaborn Dataset 2 #ecdf= Empirical Cumulative Distribution Function plot import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sns # df_value=pd.read_csv(“D://scikit_data/Billing/data.csv”) # print(df_value)...

Histogram Plot in Seaborn 0

Machine Learning Tutorials

Histogram Plot in Seaborn

Program 1 import seaborn as sns import matplotlib.pyplot as plt import pandas as pd import numpy as np # Example DataFrame df = pd.DataFrame({“marks”: np.random.randint(40, 100, size=200)}) #print(df[‘marks’]) sns.histplot(df[‘marks’], bins=10, kde=True, color=’orange’) plt.title(“Student Marks...

Seaborn Barplot Method 0

Machine Learning Tutorials

Seaborn Barplot Method

Program 1 import seaborn as sns import matplotlib.pyplot as plt import pandas as pd import numpy as np data = { ‘Fruit’: [‘Apple’, ‘Mango’, ‘Apple’, ‘Mango’, ‘Apple’, ‘Mango’], ‘Sales’: [100, 80, 90, 70, 95,...

Types of Parameters in Seaborn 0

Machine Learning Tutorials

Types of Parameters in Seaborn

Program 1 Seaborn Dataset import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sns df_tips=pd.read_csv(“D://scikit_data/Billing/tips.csv”) #print(df_tips.head()) #print(df_tips.info()) # sns.lineplot(x=”size”,y=”total_bill”,data=df_tips,hue=’sex’, style=’sex’,palette=’Accent’,dashes=False,legend=’auto’,markers=[‘.’,’*’],size=1.0) # plt.title(“Information (Bill Vs Size)”,fontsize=15) # plt.xlabel(“No of...

Seaborn Lineplot Method 0

Machine Learning Tutorials

Seaborn Lineplot Method

Program 1 Seaborn Dataset import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sns # days=[1,2,3,4,5,6,7,8,9,10] # ind_temp=[34.4,41.4,45.4,24.4,34.4,36.2,44.4,33.2,28.7,33.5] # # Using matplot # plt.plot(days,ind_temp) # plt.xlabel(“Days”) # plt.ylabel(“Temprature”)...