Python Pandas html output from DataFrame & using MySQL sample table as source by to_html()
We can create html table output or file by using data from Pandas DataFrame. We will first create one Pandas DataFrame by using some sample data.
https://www.plus2net.com/python/panda...
import pandas as pd
my_dict={
'NAME':['Ravi','Raju','Alex'],
'ID':[1,2,3],'MATH':[30,40,50],
'ENGLISH':[20,30,40]
}
df = pd.DataFrame(data=my_dict)
After creating the DataFrame we used to_html() to create html tags out of the data
df.to_html()
This output we can use to create file to store the string.
df.to_html('D:\\my_data\\my_html.html')
This will create the my_html.html file . A different path can be given to store the file in different location in the system.
We can add different options while generating the html tags . One important options is columns(), col_space, header, index, justify , max_width etc.
df.to_html(columns=['NAME','ID'])
From MySQL database using read_sql()
We can connect to MySQL database by using SQLAlchemy engine and after connection we will create our DataFrame by using data from sample table by using read_sql.
from sqlalchemy import create_engine
my_conn = create_engine("mysql+mysqldb://root:test@localhost/my_tutorial")
sql="SELECT * FROM student LIMIT 0,10"
df=pd.read_sql(sql,my_conn)
df.to_html('D:\\my_data\\my_html.html')
Here 10 rows of data from the student table is taken and displayed as string .
Excel or CSV file to string
From excel file we can create string by first creating the dataframe by reading the excel file by using the method read_excel()
df=pd.read_excel("D:\\my_data\\student.xlsx")
df.to_html('D:\\my_data\\my_html.html')
Similarly we can read csv file and generate JSON string
df=pd.read_csv("D:\\my_data\\student.csv")
df.to_html('D:\\my_data\\my_html.html')
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