✅ 📘 Intermediate Level Projects of Data Frame

 

Beginner Level Projects of DataFrame 

Pandas DataFrame for Beginners

1. Project: COVID-19 Cases Analysis

Objective: Analyze daily cases, 7-day average, and plot graphs.

Concepts Used: CSV reading, rolling average, line plot.

Sample Code:

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv("covid_data.csv")   # columns: date, cases
df['7_day_avg'] = df['cases'].rolling(window=7).mean()

plt.plot(df['date'], df['cases'], label='Daily Cases')
plt.plot(df['date'], df['7_day_avg'], label='7 Day Average')
plt.legend()
plt.xticks(rotation=45)
plt.title("COVID-19 Daily Cases")
plt.show()

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2.Project: Online Store Sales Analysis

Objective: Compare monthly revenue using bar + line chart.

Concepts Used: Groupby, sum, multiple plots.

Sample Code:

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv("sales.csv")  # columns: month, revenue

monthly = df.groupby('month')['revenue'].sum()

plt.bar(monthly.index, monthly.values)
plt.plot(monthly.index, monthly.values, marker='o')
plt.title("Monthly Revenue")
plt.xlabel("Month")
plt.ylabel("Revenue")
plt.show()

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3.Project: Movie Ratings Analysis

Objective: Show average movie rating per genre.

Concepts Used: Groupby, sorting, bar plot.

Sample Code:

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv("movies.csv")  # genre, rating

genre_rating = df.groupby('genre')['rating'].mean().sort_values()

plt.barh(genre_rating.index, genre_rating.values)
plt.title("Average Rating by Genre")
plt.xlabel("Rating")
plt.show()