Summary of processes often performed in Pandas 1 (CSV, Excel file related operations)

It's almost time to use Pandas for business, so I don't know what number to brew, but I would like to summarize the frequently used processes.

• Pandas version 0.25.1 is used for operation verification.

When reading from a CSV file

import pandas as pd

#File name: sample.csv
#The contents of the file are described below.
# 1,Sample Taro,30
# 2,Sample Hanako,25
# 3,Sample Jiro,28
df = pd.read_csv('sample.csv', 
                 #If None, there is no header, and if you specify a number, that line is interpreted as a header.
                 header=None, 
                 #Specify the column to be indexed * Here, the first column(1,2,Part 3)
                 index_col=0, 
                 #Define column name
                 names=('name', 'age'),
                 #Define the data type of the column
                 dtype={'name': str, 'age': int}
                )

When reading from an Excel file

import pandas as pd

#File name: sample.xlsx
#* The contents of the file are the same as the above CSV file.
df = pd.read_excel('sample.xlsx', 
                   dtype={'name': str, 'age': int}
                  )

When reading multiple sheets from an Excel file at the same time

• It is more convenient to know when you want to make a tool using Pandas rather than data analysis.

import pandas as pd

excel_book = pd.ExcelFile('sample.xlsx')

#You can get a list of sheet names of the loaded sheets in a list.
sheet_name_list = excel_book.sheet_names

#If you specify a sheet name, you can get the contents of that sheet.
df = excel_book.parse('sheet1')

When outputting the contents of the data frame to a CSV file

import pandas as pd

#The first argument is the output file name
df.to_csv('sample.csv', 
          #Set False if header is not needed
          header=False, 
          #Set False if no index is needed
          index=False, 
          #Set when limiting the output columns
          columns=['name']
         )

When outputting the contents of the data frame to an Excel file

import pandas as pd

#The first argument is the output file name
df.to_excel('sample.xlsx', 
          #Set False if header is not needed
          header=False, 
          #Set False if no index is needed
          index=False, 
          #Set when limiting the output columns
          columns=['name']
         )