Pandas + CSV + Matplotlib — Complete Lesson

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0) Setup (install + verify)

📦 Install

pip install pandas matplotlib

✅ Verify

import pandas as pd
import matplotlib.pyplot as plt

print("pandas:", pd.__version__)
print("matplotlib OK")

2) Read CSV properly (real-world CSV handling)

📄 Basic read

import pandas as pd

df = pd.read_csv("sales.csv")
print(df.head())
print(df.shape)
print(df.columns)

🛠 Robust read (dates + missing)

import pandas as pd

df = pd.read_csv(
    "sales.csv",
    parse_dates=["date"],
    na_values=["NA", "N/A", "-", "null", ""],
    on_bad_lines="skip"
)

print(df.info())

9) Chart examples

sales.csv (sample)

date,city,amount
2026-01-01,Varanasi,1200
2026-01-01,Delhi,800
2026-01-02,Varanasi,600
2026-01-02,Lucknow,500
2026-01-03,Delhi,1200
2026-01-03,Varanasi,900

📊 city_bar.py

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv("sales.csv")
by_city = df.groupby("city")["amount"].sum().sort_values(ascending=False)

plt.figure()
plt.bar(by_city.index, by_city.values)
plt.title("Total Sales by City")
plt.xlabel("City")
plt.ylabel("Total Amount")
plt.tight_layout()
plt.show()

📈 daily_line.py

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv("sales.csv", parse_dates=["date"])
daily = df.groupby(df["date"].dt.date)["amount"].sum()

plt.figure()
plt.plot(daily.index, daily.values, marker="o")
plt.title("Daily Sales")
plt.xlabel("Date")
plt.ylabel("Amount")
plt.xticks(rotation=45)
plt.tight_layout()
plt.show()

10) Full workflow script (end-to-end)

⭐ pandas_csv_matplotlib_workflow.py

import pandas as pd
import matplotlib.pyplot as plt

CSV_FILE = "sales.csv"

def main():
    df = pd.read_csv(CSV_FILE, parse_dates=["date"])
    df.columns = [c.strip().lower().replace(" ", "_") for c in df.columns]
    df["amount"] = pd.to_numeric(df["amount"], errors="coerce").fillna(0)
    df = df.drop_duplicates()

    by_city = df.groupby("city")["amount"].sum().sort_values(ascending=False)
    daily = df.groupby(df["date"].dt.date)["amount"].sum()

    by_city.to_csv("report_city_totals.csv")
    daily.to_csv("report_daily_totals.csv")

    plt.figure()
    plt.bar(by_city.index, by_city.values)
    plt.title("Total Sales by City")
    plt.xlabel("City")
    plt.ylabel("Total Amount")
    plt.tight_layout()
    plt.show()

    plt.figure()
    plt.plot(daily.index, daily.values, marker="o")
    plt.title("Daily Sales Trend")
    plt.xlabel("Date")
    plt.ylabel("Amount")
    plt.xticks(rotation=45)
    plt.tight_layout()
    plt.show()

if __name__ == "__main__":
    main()