Python uses pandas and xlsxwriter to read and write xlsx files. Here are the relevant steps:
The existing xlsx files are as follows:
1. Read all the data in the first n rows
# coding: utf-8
import pandas as pd
# Read all the data in the first n rows
df = pd.read_excel('school.xlsx')#Read the first sheet in xlsx
data1 = df .head(7) # Read all the data in the first 7 rows, dataFrame structure
data2 = df.values #list format, read all the data in the table
print("Get all Value:\n{0}".format(data1)) #Formatted output
print("Get all values:\n{0}".format(data2)) #Formatted output
2. Read specific rows and columns
# coding: utf-8
import pandas as pd
# Read Get specific rows and columns
df = pd.read_excel('school.xlsx') #Read the first sheet in xlsx
data1 = df.ix[0].values # Read all the data in the first row, 0 means the first row, excluding the header
data2 = df.ix[1,1] #Read the specified row and column position data
data3 = df .ix[[1,2]].values #Read specified multiple rows
data4 = df.ix[:,[0]].values #Read all rows of specified column
#data4 = df[u'class'].values #Same as above
data5 = df.ix[:,[u'class',u'name']].values #Read the specified key value column All lines
print("Data:\n{0}".format(data1))
print("Data:\n{0}".format(data2))
print("Data:\n{0}".format(data3))
print("Data:\n{0}".format(data4))
print("Data:\n{0}".format(data5))
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3. Get xlsx file line number, all column names
# coding: utf-8
import pandas as pd
# Get xlsx file line number, all column names
df = pd.read_excel('school.xlsx') #Read the first sheet in xlsx
print("Output line number list{}".format(df.index.values )) # Get all row numbers of the xlsx file
print("Output column title{}".format(df.columns.values)) #All column names
4. Read xlsx data and convert it into dictionary
# coding: utf-8
import pandas as pd
# Read xlsx data and convert it into dictionary
df = pd.read_excel('school.xlsx') #Read the first sheet in xlsx
test_data=[]
for i in df.index.values:#Get The index of the row number and traverse it:
#Get the data specified in each row based on i and use to_dict to convert it into a dictionary
row_data=df.ix[i,['id ','name','class','data','stature']].to_dict()
test_data.append(row_data)
print("The final data obtained is :{0}".format(test_data))
5. Write xlsx file
#coding: utf-8
import xlsxwriter
# Create workbook
file_name = "first_book.xlsx"
workbook = xlsxwriter.Workbook(file_name)
# Create worksheet
worksheet = workbook.add_worksheet('sheet1')
# Write cells
worksheet.write(0, 0, 'id')
worksheet.write(0 ,1, 'name')
worksheet.write(0,2, 'class')
worksheet.write(0,3, 'data')
# Write rows
worksheet.write_row(1, 0, [1, 2, 3])
# Write columns, where column D needs to be capitalized
worksheet.write_column(' D2', ['a', 'b', 'c'])
# Close the workbook
workbook.close()
The xlsx file written is as follows :
##
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