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• • head(n): This method returns the first n rows of the DataFrame. If n is not specified, it defaults to 5.
print(df.head(2))
Output:
Product Price Stock Rating
0 Laptop 1000 50 4.5
1 Tablet 500 150 4.0
• • tail(n): This method returns the last n rows of the DataFrame. If n is not specified, it defaults to 5.
print(df.tail(2))
Output:
Product Price Stock Rating
2 Smartphone 800 200 4.7
3 Monitor 300 100 4.3
Importing a CSV file into a DataFrame
This function is versatile and handles various configurations of CSV files, making it straightforward to load data for
analysis or manipulation.
You can import a CSV file into a pandas DataFrame using the read_csv() function. The syntax of the read_csv()
function is:
pd.read_csv("filename.csv")
where, filename.csv is the name of the file with .csv extension that you want to import.
The pd.read_csv() function in pandas is quite versatile and allows you to specify various parameters to customise
how the CSV file is read. Some commonly used parameters are as follows:
• • filepath: The path to the CSV file.
• • sep: The delimiter to use for separating columns. These delimiters can be a comma, semicolon, tab, or any other
character. The default value for ‘sep’ is a comma.
• • header: It specifies which row to use as column names. ‘header=0’ means the column names are taken from the
first line of the file. By default, ‘header=0’.
• • index_col: It specifies which column to use as the row labels.
• • dtype: A dictionary where keys are column names and values are data types.
• • encoding: It specifies the encoding to use for reading the file.
• • compression: It specifies the compression mode for reading compressed files.
Program 56: To import a CSV file into DataFrame
# importing pandas library
import pandas as pd
# making data frame
#specify path of file in case file is in a different folder
df = pd.read_csv("Customer.csv",sep=',', header=0)
print(df)
222 Touchpad Artificial Intelligence (Ver. 3.0)-XI

