Pandas to_sql() inserting index

Question

I am using Pandas 0.18.1, and while fiddling with this code,

import pd

def getIndividualDf(item):
    var1 = []
    # ... populate this list of numbers
    var2 = []
    # ... populate this other list of numbers

    newDf = pd.DataFrame({'var1': var1, 'var2': var2})
    newDf['extra_column'] = someIntScalar
    yield newDf

dfs = []
for item in someList:
    dfs.append(getIndividualDf(item))

resultDf = pd.concat(dfs)
resultDf['segment'] = segmentId # this is an integer scalar

from sqlalchemy import create_engine
engine = create_engine('postgresql://'+user+':'+password+'@'+host+'/'+dbname)
resultDf.reset_index().to_sql('table_name', engine, schema="schema_name", if_exists="append", index=False)

I was getting this exception:

(psycopg2.ProgrammingError) column "index" of relation "table_name" does not exist

Indeed, there is no such column in the table, only because there is no such explicit column in the data frame. Which is why it's weird.

Running

print(list(resultDf))

just before the to_sql() call, yields

['var1', 'var2', 'extra_column', 'segment']

Removing index=False from the to_sql() call changes the error to this:

(psycopg2.ProgrammingError) column "level_0" of relation "table_name" does not exist

I am puzzled. How do I get rid of index column?

Update
print(resultDf.head()) yielded this information:

     var1       var2  extra_column  segment
0       8   0.101653    2077869737   201606
1       9   0.303694    2077869737   201606
2      10   0.493210    2077869737   201606
3      11   0.661064    2077869737   201606
4      12   0.820924    2077869737   201606

Answer 1

You need not to reset the index before writing to sql such has:

resultDf.to_sql('table_name', engine, schema="schema_name", if_exists="append", index=False)