Loading a CSV file into a Pandas DataFrame with Python

Python Pandas Numpy: Exercise-1 with Solution

Load a CSV file into a Pandas DataFrame.

test.csv:

col1,col2,col3
20,40,60
30,50,80
40,60,100

Sample Solution:

Python Code:

import pandas as pd

# Replace 'your_file.csv' with the actual path to your CSV file
file_path = 'test.csv'

# Load CSV file into a Pandas DataFrame
df = pd.read_csv(file_path)

# Display the DataFrame
print(df)

Output:

col1  col2  col3
0    20    40    60
1    30    50    80
2    40    60   100

Explanation:

• importing Pandas Library:
  import pandas as pd - Import the Pandas library and alias it as "pd" for convenience. This is a common convention in the Python data science community.
• Specifying the File Path:
  file_path = 'test.csv' - Replace 'test.csv' with the actual path to your CSV file. This variable holds the path or URL of the CSV file that you want to load into the DataFrame.
• Loading CSV File into DataFrame:
  df = pd.read_csv(file_path) - The "read_csv()" function reads the CSV file and create a Pandas DataFrame (df). It automatically detects the delimiter (comma, semicolon, etc.) in the CSV file. If your CSV file has a different delimiter, you can specify it using the 'sep' parameter. For example,
  df = pd.read_csv(file_path, sep=';') # Replace ';' with your actual delimiter.
• Displaying the DataFrame:
  print(df) - This line prints the DataFrame contents to the console. You'll see the data, column names, and other information about the DataFrame.

Flowchart:

Python Code Editor:

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