Start Writing Python: A Guide for the Rookie "Create Bar Graph" 🐍 EP.3

Reading data from CSV and creating a bar graph with a simple Python

To work with data, we often need to manage CSV-type files that store data in a tabular format, such as user lists, sales reports, or demographics. In this article, we will learn how to:

• Read data from CSV files

• Display information on the screen

• Draw Bar Chart with each person's name and age

All of this uses Python in conjunction with popular libraries like pandas and matplotlib.

🔧 Sample code

Import pandas as pd.

Import matplotlib.pyplot as plt

# Read CSV file by full path

file _ path = '/ media / acdc / 473f8881-2823-4afa-aca5-e819a648674e / D1.csv'

df = pd.read _ csv (file _ page)

# Print all data

Print (df)

# Print each row

For index, row in df.iterrows ():

Print (f "Name: {row ['Name']}, Age: {row ['Age']}, Gender: {row ['Gender']}")

# Plot bar chart of Age by name

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

plt.bar (df ['Name'], df ['Age'], color = 'skyblue')

plt.xlabel ('name')

plt.ylabel ('Age')

plt.title ('Age of Each Person')

plt.xticks (rotation = 45)

plt. Tight _ layout ()

plt.show ()

📖 Describe the code part by part.

📦 1.Import library

Import pandas as pd.

Import matplotlib.pyplot as plt

• Pandas are used for managing table data and CSV

• Matplotlib.pyplot is used to create graphs such as bar, line and circle graphs.

📄 2. Read the data from the CSV file.

file _ path = '/ media / acdc /.../ D1.csv'

df = pd.read _ csv (file _ page)

• We use read _ csv () to load the data file.

• The df variable becomes a DataFrame data table.

📤 3. Show all the information.

Print (df)

• Use to view all data in the loaded CSV file

🔁 4. Show row-by-row data.

For index, row in df.iterrows ():

Print (f "Name: {row ['Name']}, Age: {row ['Age']}, Gender: {row ['Gender']}")

• Loop by row to display the information by name. Explicit description

• Suitable for checking data one by one

📊 5. Create a bar graph.

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

plt.bar (df ['Name'], df ['Age'], color = 'skyblue')

• Create a 10x6 inch graph

• df ['name'] is used as the X-axis

• df ['Age'] is used as the height of the stick.

🏷️ 6. Decorate the graph to look good.

plt.xlabel ('name')

plt.ylabel ('Age')

plt.title ('Age of Each Person')

plt.xticks (rotation = 45)

plt. Tight _ layout ()

• Enter the names of the X and Y axes

• Name the graph

• Rotate the X-axis name to tilt slightly for easy reading.

• Tight _ layout () keeps the graph from cutting edges

👁️ 7. Show the graph.

plt.show ()

• This last command will open a graph display window for the user.

📌 Summary

This code allows you to:

1.Load data from CSV file easily

2. Simple to understand each row data check

3. Create a bar graph to see each person's age trend.

You can extend this code immediately or ask me more. 😊

I have a little problem with PC. (Persona 😏) Now will come back down more often.

By the round ⚽️

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