Htykuut

df is a csv file that contains ship_date, order_date and cumulative_ordered. cumulative_ordered is the sum of orders added on every day up until ship_date. There are 30 days prior to every ship_date and those days only counts for one ship_date. after ship_date 2018-07-01, then next ship_date will be 2018-08-01 with same procedure.

My problem is that I can't get days remaining(see last code output below) when I calculate the percentage average of cumulative_ordered on each of those 30 days prior.

I have the following code, that gives me the days_remaining from a csv file with several different ship_date and order_date counting down to each separate ship_date.

df['days_remaining'] = pd.to_datetime(df['ship_date']).sub

(pd.to_datetime(df['order_date'])).dt.days

df['difference'] = df['ship_date'] - df['order_date']



df.head()

output:

ship_date    Order_date   cumulative_ordered   days_remaining    difference



2018-07-01   2018-06-01     7                  30               30 days

2018-07-01   2018-06-02     10                 29               29 days

2018-07-01   2018-06-03     15                 28               28 days

2018-07-01   2018-06-04     30                 28               27 days

2018-07-01   2018-06-05     41                 28               26 days

I then try to find total ordered on each day prior to ship_date

m = df.groupby("difference").mean()

m.head()

which gives me this output:

             cumulative ordered    days_remaining

difference                            

      0 days    352.458124             0.0

      1 days    291.234747             1.0

      2 days    244.122137             2.0

      3 days    201.178765             3.0

      4 days    190.153641             4.0

I'm running into an issue when I try to find an average of cumulative ordered on each day in terms of percentage filled from cumulative_ordered output on 0 days above, by running this code:

   v = m/m[m.index.days == 0].iloc[0]

   v.head()



          cumulative_ordered      days_remaining

difference                           

0 days        1.000000              NaN

1 days        0.891324              inf

2 days        0.812534              inf

3 days        0.752339              inf

4 days        0.673745              inf

days_remaining changes to NaN and inf.. How can I keep it so it still gives me integers?

The NaN and inf result from dividing by 0.0.

It seems that you are trying to apply the operation only to the cumulative_ordered column, so you should just run this for your last block of code:

m['cumulative_ordered'] = m['cumulative_ordered'] / m['cumulative_ordered'][m['cumulative_ordered'].index.days == 0]