Compare two lists from sql in python and show result using pandas.io

Question

I'm having a question on python. I'm trying to compare two dataframes and check which elements are different and insert them into another dataframe. So here are my dataframes. df1:

PN      Stock        WHS      Cost
1111     1           VLN       0.2
1111     2           VLN       0.2
1115     1           KNS       0.5

df2:

    PN      Stock        WHS      Cost    Time
   1111        1         VLN       0.2     15:00
   1111        3         VLN       0.2     16:00

So the idea is to add to df1 the data from df2 that is not yet in df1; line 2 in df2 does not exist in df1 so I want to insert it. How should i write code to find not existing line so that I could insert it? I have tried:

   for index, row in df1.iterrows():
        if df2[(df2['PN']==row['PN']) & (df2['Stock'] ==row['Stock']) & (df2['Whs'] = row['Whs']) & (df2['Cost']==row['Cost'])].empty
              print row['PN']

To check which rows to update but i get basically all rows printed, not the ones that do not match. How can I solve this please? Is it possible to use somehow 'IN' function, comparing each df1 line with whole df2???

line 2 in List2 does not exist in List1?? It does. Only the Time columns does not exist... — paulo.filip3
– paulo.filip3, Commented May 19, 2015 at 8:05
Your question doesn't make sense can you post desired output, also you state line2 in your 2nd df does not exist but it does — EdChum
– EdChum, Commented May 19, 2015 at 8:08
sorry guys, updated question, now line 2 in list2 does not exist in list1 — orangutangas
– orangutangas, Commented May 19, 2015 at 8:14

EdChum · Accepted Answer · 2015-05-19 08:28:16Z

1

I believe you want to perform an outer merge:

In [29]:

df.merge(df1, how='outer')
Out[29]:
     PN  Stock  WHS  Cost   Time
0  1111      1  VLN   0.2  15:00
1  1111      2  VLN   0.2    NaN
2  1115      1  KNS   0.5    NaN
3  1111      3  VLN   0.2  16:00

answered May 19, 2015 at 8:28

EdChum

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sachin saxena · Accepted Answer · 2015-05-19 08:23:44Z

1

You can use outer join to achieve this result

    pd.concat([df1,df2],join='outer')

http://pandas.pydata.org/pandas-docs/stable/generated/pandas.concat.html for more options about how you want to deal with indexes etc..

answered May 19, 2015 at 8:23

sachin saxena

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