'replace sqlite3 database table with pandas dataframe
My sqlite3 database look like the following:
id name
1 apple
2 orange
3 pear
4 bananna
Then I query each element from the database into a pandas dataframe.
After that I merge the dataframe with a list.
After that I sort the database element by the list.
conn = sqlite3.connect('db.sqlite3', isolation_level=None, detect_types=sqlite3.PARSE_COLNAMES)
df = pd.read_sql_query('select * from name', conn)
#I am getting the list .....
df["color"] = color #color is a list
df.sort_values(by=['color'], ascending=True, inplace=True)
How could I replace the original sqlite3 table with the sorted dataframe? I do not want to add the color column to the sqlite3 table.
Solution 1:[1]
The correct answer:
db.sort_values(by=['color'], ascending=True).drop('color',axis=1).to_sql("name",conn,if_exists='replace',index=False, index_label="id")
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 | palloc |
