Census data visualization

 import pandas as pd

import matplotlib.pyplot as plt

import seaborn as sns

df=pd.read_csv("/content/drive/MyDrive/Census2000")

df.head()

print(df.describe())

print(df.isnull().sum())

print(df["Age"].unique())

plt.figure(figsize=(12, 6))

sns.barplot(x="Age", y="People", hue="Year", data=df, palette="coolwarm")

#plt.xticks(rotation=45)

plt.title("Population Distribution by Age Group (1900 vs 2000)")

plt.xlabel("Age Group")

plt.ylabel("Population")

plt.legend(title="Year")

plt.show()

plt.figure(figsize=(10, 5))

sns.barplot(x="Sex", y="People", hue="Year", data=df, palette="Set1")

plt.title("Gender-wise Population Comparison (1900 vs 2000)")

plt.ylabel("Total Population")

plt.show()

plt.figure(figsize=(10, 6))

sns.boxplot(x="Year", y="People", data=df, palette="coolwarm")

plt.xlabel("Year")

plt.ylabel("Population Count")

plt.title("Box Plot of Population Distribution (1900 vs 2000)")

plt.show()

import matplotlib.pyplot as plt

import seaborn as sns

# Bar plot for People count by Sex (1900 vs 2000)

plt.figure(figsize=(6, 4))

sns.barplot(x='Sex', y='People', hue='Year', data=df, palette='viridis')

plt.title('People Count by Sex (1900 vs 2000)')

plt.xlabel('Sex')

plt.ylabel('People Count')

plt.legend(title='Year')

plt.show()

# Bar plot for Total People Count by Year (1900 vs 2000)

plt.figure(figsize=(6, 4))

sns.barplot(x='Year', y='People', data=df.groupby('Year').sum().reset_index(), palette='coolwarm')

plt.title('Total People Count by Year')

plt.xlabel('Year')

plt.ylabel('Total Population')

plt.show()