Visulalization of dataset
"""Untitled0.ipynb
Automatically generated by Colaboratory.
Original file is located at https://colab.research.google.com/drive/11i8-u-Xb-60Jans2sT7RT3EySQ6yo5hv """
import pandas as pd a=pd.read_csv("dataanime.csv")
from sklearn import preprocessing label_encoder=preprocessing.LabelEncoder() a["Episodes"]=label_encoder.fit_transform(a["Episodes"])
from matplotlib import pyplot as plt plt.plot(a["Title"],a["Score"]) plt.show()
import seaborn as sd sd.barplot(x="Title",y="Episodes",data=a) plt.show()
import seaborn as sd sd.scatterplot(x="Title",y="Episodes",data=a) plt.show()
import seaborn as sd sd.histplot(x="Title",y="Episodes",data=a) plt.show()
import seaborn as sd sd.boxplot(x="Title",y="Episodes",data=a) plt.show()
import seaborn as sd sd.lineplot(x="Title",y="Episodes",data=a) plt.show()
sd.countplot(x="Episodes",data=a) plt.show()
sd.pairplot(a)
import pandas as pd import matplotlib.pyplot as plt import seaborn as sns
sns.set_theme()
data = {'period': [1, 7], 'Title': [7, 5], 'Episodes': [5, 9], }
df = pd.DataFrame(data) plt.stackplot(df.period, df.Title, df.Episodes, labels=['Title', 'Episodes'])
import matplotlib.pyplot as plt
labels = ['Rating','Episodes','Score'] sizes = [88,22,75] plt.figure(figsize=(6, 6)) plt.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=140) plt.axis('equal') plt.show()
import plotly.express as px fig=px.scatter_polar(a['Score'],a['Episodes']) fig.show()
import pandas as pd
data = {'Category': ['Title', 'Episodes', 'Score'], 'Value': [a['Title'],a['Episodes'],a['Score']]}
df = pd.DataFrame(data)
print(df)
import matplotlib.pyplot as plt x = a['Title'] y = a['Episodes'] plt.plot(x, y, marker='o', linestyle='-', color='b', label='My Data')
plt.xlabel('X-axis Label') plt.ylabel('Y-axis Label') plt.title('Line Chart for My Dataset')
plt.show()