DATE:
GITHUB LINK: https://github.com/saran7d/DS-EX-10.git
COLAB LINK: https://colab.research.google.com/drive/1NVXuiyaSNIa2AyA1-P9UxAfYcm096ZPl?usp=sharing
To Perform Bivariate/Multivariate Analysis
1.Read the given data
2.Get information from the data
3.Perform the Multivariate Analysis
4.Save the clean data to file
Developed by: Saran S S
Reg no: 212221220048
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import io
from google.colab import files
uploaded = files.upload()
dd = pd.read_csv(io.BytesIO(uploaded['FlightInformation.csv']))
print(dd)
sns.scatterplot (dd['Date_of_Journey'],dd['Dep_Time'])
sns.barplot (x=dd['Duration'],y=dd['Price'])
sns.barplot(x=dd["Arrival_Time"],y=dd["Price"],data=dd)
states=dd.loc[:,["Duration","Price"]]
states=states.groupby(by=["Duration"]).sum().sort_values(by="Price")
sns.barplot(x=states.index,y="Price",data=states)
plt.xticks(rotation = 90)
plt.xlabel=("Duration")
plt.ylabel=("Price")
plt.show()
dd.corr()
data = np.random.randint(low = 1, high = 100, size = (10, 10))
print("The data to be plotted:\n")
print(data)
hm = sns.heatmap(data = data)
plt.show()
Thus, Bivariate/Multivariate Analysis is performed successfully.