How Append a table from pandas data frame without truncating old data

Question

I have a table rate_card as shown below which I have inserted from data-frame using

 df5.to_sql('rate_card', cnx, if_exists='replace', schema='asia', index = False,method='multi')

Current data inside table

ORG_CNTY  DEST_CNTY   KG  Cost    Version
 DE         FR         1   50     2019-12-02
 DE         FR         2   80     2019-12-02
 DE         IND        2   65     2018-12-01
 DE         US         1   70     2019-12-01

I have new set data which need to insert to table again

New data

ORG_CNTY  DEST_CNTY   KG  Cost    Version
 DE         FR         1   60     2020-06-02
 DE         FR         2   90     2020-06-02
 DE         IND        1   55     2020-06-02
 DE         US         1   80     22020-06-02

Expected Output

ORG_CNTY  DEST_CNTY   KG  Cost    Version
 DE         FR         1   50     2019-12-02
 DE         FR         2   80     2019-12-02
 DE         IND        2   65     2018-12-01
 DE         US         1   70     2019-12-01
 DE         FR         1   60     2020-06-02
 DE         FR         2   90     2020-06-02
 DE         IND        1   55     2020-06-02
 DE         US         1   80     22020-06-02

my current code is truncating and loading the table new data. I want to old data and append the new data into the table. How can this done in python?

@Datanovice, if need append only based on specific keys. is there something more that i need to do. — aeapen, Jul 09 '20 at 15:39
then you should push the data into a staging table and invoke a stored procedure to update your table based on your keys. you could also pull the whole table down into pandas and update it from there. — Umar.H, Jul 09 '20 at 15:42

score 0 · Answer 1 · answered Jul 09 '20 at 23:15

0

df_expected = df_current.append(df_new)

answered Jul 09 '20 at 23:15

nav610

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How Append a table from pandas data frame without truncating old data

1 Answers1