Write data on CSV format using pandas from DataFrame?
If we want to convert application data into CSV format under data science then we can use to_csv().
Syntax
Now I am creating dictionary objects to store student records that will be saved into CSV file using data frames.
import pandas as pd
stu = {'rno':[1001,1002,1003],'sname':['stu1','stu2','stu3']}
df=pd.DataFrame(stu)
df.to_csv('stu.csv')
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If we want to write a CSV file without an index or Without a Column Header then we can use the following property.
Example without header and indexing?
import pandas as pd
stu = {'rno':[1001,1002,1003],'sname':['stu1','stu2','stu3']}
df=pd.DataFrame(stu)
df.to_csv('stu.csv',header=False,index=False)
How to read excel files in pandas?
pip install openpyxl.
import pandas as pd
# Import the excel file and call it xls_file
excel_file = pd.ExcelFile('Test.xlsx')
# View the excel_file's sheet names
print(excel_file.sheet_names)
# Load the excel_file's Sheet1 as a dataframe
df = excel_file.parse('Sheet1')
print(df)
Program to take input as dictionary data and convert it into dataframe and calculating the total and percentage of all students and adding their columns.
ReplyDeleteimport pandas as pd
import numpy as np
mark = {'NAME':['HARISH','PIYUSH','YOGESH','TANISHQ','AYUSH','DEEPAK'],'PHYSICS':[50,60,70,32,45,79],'CHEMISTRY':[44,12,70,60,57,99],'MATHS':[89,88,70,40,78,98]}
xl = pd.DataFrame(mark)
supply = []
total = []
eligible = []
percent = []
#loop for finding the list of students having supplementary
for i in range(0,len(xl)):
for j in range(1,len(xl.columns)):
if xl.iloc[i,j] < 33:
# print(f'{xl.iloc[i,0]} got supplementary')
supply.append(xl.iloc[i,0])
#loop for finding the list of students who are not gettting supplementary
for a in range(0,len(xl)):
if xl.iloc[a,0] not in supply:
eligible.append(xl.iloc[a,0])
#loop for calculating total and percentage list
for check in range(0,len(xl)):
if xl.iloc[check,0] not in supply:
sum = xl['PHYSICS'][check] + xl['CHEMISTRY'][check] + xl['MATHS'][check]
total.append(sum)
per = sum/3
percent.append(per)
t = pd.Series(total) #converting total list into series
p = pd.Series(percent) #converting percentage into series
xl['total'] = t #adding new column named total in csv
xl['percentage'] = p #adding new column names percenage in csv
xl.to_csv('student_marksheet.csv') #converting a dataframe into csv with name student_marksheet.csv
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