DATA TRANSFER BETWEEN CSV FILES/SQL DB & DATAFRAME
DATA TRANSFER BETWEEN CSV FILES/SQL DB & DATAFRAME
ASSIGNMENTS
1. What is csv file?
2. What is dataframe object of python pandas?
3. What is sql database?
4. Which method of dataframe object is used to store dataframe object's data to a
csv file?
5. Write python code to Create a dataframe with name and dob of three person and
store this dataframe to a csv file.
6. Write python code to read csv file into dataframe and then display the contents of
this dataframe.
7. How we can load csv file without header?
8. Write syntax to load a csv file with specifying headers.
9. Write the names of two important modules required to interact with sql databases
with dataframe
10. Write short notes on 3 driver required to interact with sql databases with
dataframe.
11. Write short notes on followings
a. Sqlalchemy
b. pymysql
12. write steps to install sqlalchemy in python.
13. write steps to install sqlalchemy in anaconda.
14. What is mysql?
15. What is sqlite?
16. What are the features of mysql?
17. What are the features of sqlite?
18. Write python code to read mysql database to python pandas dataframe
object.
19. Write python code to append a new record in mysql database to existing
table.
20. Write python code to read sqlite database to python pandas dataframe
object.
21. Write python code to append a new record in sqlite database to existing
table.
................
................
In order to avoid copyright disputes, this page is only a partial summary.
To fulfill the demand for quickly locating and searching documents.
It is intelligent file search solution for home and business.
Related searches
- read csv files in r
- importing csv files into r
- import csv files into excel
- azure sql db pricing page
- using csv files in powershell
- how do i transfer files between computers
- windows 10 transfer files between computers
- transfer programs and files to new computer
- converting csv files to excel
- how to read csv files in python
- importing csv files python
- azure sql db best practices