Key error on pandas merge (left join)
16,637
The KeyError arises from this:
df = pd.merge(df_purchase, df_login[['count']] <- this selects just count column,
how='left', on=['age', 'gender', 'region'])
You've specifically selected just a single column from df_login
, you need this:
df = pd.merge(df_purchase, df_login,
how='left', on=['age', 'gender', 'region'])
I'm assuming that this is not your complete data as you have no common values in the age and region column in df_login
.
Author by
metersk
Updated on July 20, 2022Comments
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metersk almost 2 years
I have two dataframes below, df_purchase(1) and df_login(2)
+--------+-----+--------+------------+--------------------+-------------+--------------------------+ | | age | gender | ttp | count | sum(amount) | region | +--------+-----+--------+------------+--------------------+-------------+--------------------------+ | 49427 | 63 | M | 824.731412 | 2 | 25.00 | Omaha, Nebraska | | 28433 | 49 | M | 1.166250 | 2 | 41.94 | Catasauqua, Pennsylvania | | 4162 | 29 | M | 5.620949 | 2 | 51.78 | Eagle Center, Iowa | | 18747 | 43 | M | 153.502072 | 2 | 23.84 | Pacific, Washington | | 45173 | 59 | M | 0.027257 | 2 | 13.98 | De Soto, Missouri | +--------+-----+--------+------------+--------------------+-------------+--------------------------+ +--------+-----+--------+------------+--------------------+-------------+--------------------------+ | | age | gender | count | region | | | | 671766 | 84 | M | 13900 | New York, New York | | | | 671166 | 84 | F | 7619 | New York, New York | | | | 672209 | 85 | F | 6483 | New York, New York | | | | 672671 | 85 | M | 5808 | New York, New York | | | | 195201 | 34 | M | 3817 | New York, New York | | | +--------+-----+--------+------------+--------------------+-------------+--------------------------+
I am trying to join df_logins to df_purchase on age, gender and region with the following pandas code:
df = pd.merge(df_purchase, df_login[['count']], how='left', on=['age', 'gender', 'region'])
However, I keep getting this error:
KeyError: 'age'
Any thoughts?