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import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from pyexpat import model
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import accuracy_score
import joblib
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
df=pd.read_csv(r"C:\Users\hp\PycharmProjects\PythonProject5\Arka_Tea_Traders_Zoho_Ledger-1.csv")
print(df)
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_absolute_error
df= pd.read_csv(r'C:\Users\hp\PycharmProjects\PythonProject5\Salary_Data.csv')
print (df)
sns.jointplot('data=df, x="Years of experience", y="Salary")')
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from pyexpat import model
from sklearn.preprocessing import LabelEncoder
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_absolute_error
df=pd.read_csv(r"C:\Users\hp\PycharmProjects\PythonProject5\Admission.csv")
print(df)
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