All this is asking me to do is write a code that shows if there are any missing values where it is not the customers first order. I have provided the DataFrame. Should I use column 'Order_number" instead? Is my code wrong?
I named the DataFrame df_orders.
I thought my code would find the columns that have missing values and a greater order number than 1.
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 478967 entries, 0 to 478966
Data columns (total 6 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 order_id 478967 non-null int64
1 user_id 478967 non-null int64
2 order_number 478967 non-null int64
3 order_dow 478967 non-null int64
4 order_hour_of_day 478967 non-null int64
5 days_since_prior_order 450148 non-null float64
dtypes: float64(1), int64(5)
memory usage: 21.9 MB
None
# Are there any missing values where it's not a customer's first order?
m_v_fo= df_orders[df_orders['days_since_prior_order'].isna() > 1]
print(m_v_fo.head())
Empty DataFrame
Columns: [order_id, user_id, order_number, order_dow, order_hour_of_day,
days_since_prior_order]
Index: []