I feel like I'm overlooking something really simple, but I can't make it work. I'm using SQLite
now, but a solution in SQLAlchemy
would also be very helpful.
Let's create our original dataset:
### This is just the setup part
import pandas as pd
import sqlite3
conn = sqlite3.connect('test.sqlite')
orig = pd.DataFrame({'COLUPC': [100001, 100002, 100003, 100004],
'L5': ['ABC ALE', 'ABC MALT LIQUOR', 'ABITA AMBER', 'ABITA AMBER'],
'attr1': [0.25, 0.25, 0.041, 0.041]})
orig.to_sql("UPCs", conn, if_exists='replace', index=False)
#Create an index just in case it's needed
conn.execute("""CREATE INDEX upc_index
ON UPCs (COLUPC);""")
Now suppose I take that orig
dataframe
and add a column called 'L5_lower'. Then I create the column in the SQLite database:
# Create new variable
orig['L5_lower'] = orig.L5.str.lower()
conn.execute("alter table UPCs add column L5_lower TEXT;")
Now suppose I want to fill in this single column L5_lower
to the SQLite table, without having to pass other columns (below I explain why I need this)
I tried passing the index and the new column as tuples:
query='''insert or replace into UPCs (COLUPC, L5_lower) values (?,?) '''
conn.executemany(query, orig[['COLUPC', 'L5_lower']].to_records(index=False))
conn.commit()
# But then:
df = pd.read_sql("SELECT * FROM UPCs;", conn)
conn.close()
gives this messed up result.
COLUPC L5 attr1 L5_lower
0 100001 ABC ALE 0.250 None
1 100002 ABC MALT LIQUOR 0.250 None
2 100003 ABITA AMBER 0.041 None
3 100004 ABITA AMBER 0.041 None
4 b'\xa1\x86\x01\x00\x00\x00\x00\x00' None NaN abc ale
5 b'\xa2\x86\x01\x00\x00\x00\x00\x00' None NaN abc malt liquor
6 b'\xa3\x86\x01\x00\x00\x00\x00\x00' None NaN abita amber
7 b'\xa4\x86\x01\x00\x00\x00\x00\x00' None NaN abita amber
Instead, the expected output is:
COLUPC L5 attr1 L5_lower
0 100001 ABC ALE 0.250 abc ale
1 100002 ABC MALT LIQUOR 0.250 abc malt liquor
2 100003 ABITA AMBER 0.041 abita amber
3 100004 ABITA AMBER 0.041 abita amber
So, why am I trying to pass a single column? I have a very big dataset and I won't be able to have the whole dataframe in memory. My intended workflow is to construct one column at a time and then update
or insert
into the SQLite database.
AFAIK you can't add COLUMNS using Pandas to_sql - you can add ROWS. One solution would be to insert a new column into a temporary table (with the same index as the original table has) and then update the source table on the SQLite side.
Here is a working example:
SETUP:
assuming we have the following original DF:
In [79]: orig
Out[79]:
COLUPC L5 attr1
0 100001 ABC ALE 0.250
1 100002 ABC MALT LIQUOR 0.250
2 100003 ABITA AMBER 0.041
3 100004 ABITA AMBER 0.041
In [80]: orig.set_index('COLUPC', inplace=True)
In [81]: conn = sqlite3.connect('d:/temp/test.sqlite')
In [82]: orig.to_sql('upcs', conn, if_exists='replace', index=True)
In [83]: conn.close()
SOLUTION:
In [84]: conn = sqlite3.connect('d:/temp/test.sqlite')
In [85]: df = pd.read_sql('select * from upcs', conn, index_col='COLUPC')
In [86]: df
Out[86]:
L5 attr1
COLUPC
100001 ABC ALE 0.250
100002 ABC MALT LIQUOR 0.250
100003 ABITA AMBER 0.041
100004 ABITA AMBER 0.041
create temporary table:
In [87]: tmp = orig.L5.str.lower().to_frame('L5_lower')
In [88]: tmp
Out[88]:
L5_lower
COLUPC
100001 abc ale
100002 abc malt liquor
100003 abita amber
100004 abita amber
In [89]: tmp.to_sql('tmp', conn, if_exists='replace', index=True)
add new column to SQLite table:
In [90]: conn.execute('alter table UPCs add column L5_lower varchar(50)')
Out[90]: <sqlite3.Cursor at 0xa558c00>
In [91]: qry = 'update upcs set L5_lower = (select L5_lower from tmp where tmp.COLUPC = upcs.COLUPC) where L5_lower is NULL'
In [92]: conn.execute(qry)
Out[92]: <sqlite3.Cursor at 0xa593570>
In [93]: conn.commit()
In [94]: conn.execute('drop table tmp')
Out[94]: <sqlite3.Cursor at 0xa5930a0>
Check:
In [95]: pd.read_sql('select * from upcs', conn, index_col='COLUPC')
Out[95]:
L5 attr1 L5_lower
COLUPC
100001 ABC ALE 0.250 abc ale
100002 ABC MALT LIQUOR 0.250 abc malt liquor
100003 ABITA AMBER 0.041 abita amber
100004 ABITA AMBER 0.041 abita amber
In [96]: conn.close()
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