read_excel() method from the p
.xls format. It takes the file name or directory as the first argument with the sheet name as the second argument value. As a matter of course, it takes an excel file as input and returns it as a DataFrame.
pd.read_excel(io:path_to_file, sheet_name="Sheet1", header=0, names=None, index_col=None, na_values=None)
It takes the following argument values:
path_to_file: This is the excel spreadsheet name with an extension or path to the file.
sheet_name: Its default value is
None. It shows the sheet name because a single excel spreadsheet may contain multiple sheets.
header: Its default value is 0, and the header value is 0 as well. This means the first row will be used as the header of the returned DataFrame. Use
Noneif the file does not have header or column labels.
names: This is a list of column names or header values. Its default value is
index_col: This helps us use columns as row labels. Its default value is
na_values: This helps us assign some value to NA or empty fields in the excel file. Its default value is
It returns a DataFrame.
Now, let’s discuss this method in detail with code examples.
data.xlsx file has two workbooks (Employee and Payment). The "Employee" sheet contains the EID, name, and salary, while the "Payment" sheet contains EID, payment, and the hiring date.
import pandas as pd import numpy as np # invoking read_excel() with # io= data.xlsx, # sheet_name= "Payment" # header=0 df = pd.read_excel("data.xlsx", index_col=0) print(df)
read_excel()method to extract excel data into a DataFrame.
import pandas as pd import numpy as np # loading data.xlsx excel file in program xlsx = pd.ExcelFile("data.xlsx") # reading excel file to convert into dataframe df = pd.read_excel(xlsx) print(df)
ExcelFile()from pandas to load an excel file in the
read_excel()method to convert excel data into a DataFrame. It helps manipulate the dataset easily after loading it into the program.
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