Python Pandas Create USD_Converted column
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0
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I have two dataframes, deals
Currency Deal_Amount
0 USD 18.40
1 USD 18.40
2 USD 5559.00
3 USD 14300.00
4 USD 1000.00
5 EUR 3072.00
6 USD 500.00
7 CAD 100000.00
8 USD 250.00
15 EUR 6000.00
and currency_rates
currency_code year quarter from_usd_rate to_usd_rate
AED 2018 3 3.67285 0.27226813
ARS 2018 3 17.585 0.056866648
AUD 2018 3 1.27186 0.786250059
BRL 2018 3 3.1932 0.313165477
CAD 2018 3 1.2368 0.808538163
EUR 2018 3 0.852406 1.173149884
GBP 2018 3 0.747077 1.338550109
GHS 2018 3 4.4 0.227272727
I want to create a column in deals that converts deals where deals['Currency'] != USD, and apply the currency_rate['to_usd_rate'] to deals['Deal_Amount'] to get the USD converted amount.
So far i tried
def convert_amount(data):
if data['Currency']==currency_rates['currency_code']:
Converted_amount=data['Deal_Amount'] * currency_rates['to_usd_rate']
return Converted_amount
but its not working.
python pandas
asked Nov 9 at 19:06
TH14
255
add a comment |
up vote
0
down vote
favorite
I have two dataframes, deals
Currency Deal_Amount
0 USD 18.40
1 USD 18.40
2 USD 5559.00
3 USD 14300.00
4 USD 1000.00
5 EUR 3072.00
6 USD 500.00
7 CAD 100000.00
8 USD 250.00
15 EUR 6000.00
and currency_rates
currency_code year quarter from_usd_rate to_usd_rate
AED 2018 3 3.67285 0.27226813
ARS 2018 3 17.585 0.056866648
AUD 2018 3 1.27186 0.786250059
BRL 2018 3 3.1932 0.313165477
CAD 2018 3 1.2368 0.808538163
EUR 2018 3 0.852406 1.173149884
GBP 2018 3 0.747077 1.338550109
GHS 2018 3 4.4 0.227272727
I want to create a column in deals that converts deals where deals['Currency'] != USD, and apply the currency_rate['to_usd_rate'] to deals['Deal_Amount'] to get the USD converted amount.
So far i tried
def convert_amount(data):
if data['Currency']==currency_rates['currency_code']:
Converted_amount=data['Deal_Amount'] * currency_rates['to_usd_rate']
return Converted_amount
but its not working.
python pandas
asked Nov 9 at 19:06
TH14
255
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I have two dataframes, deals
Currency Deal_Amount
0 USD 18.40
1 USD 18.40
2 USD 5559.00
3 USD 14300.00
4 USD 1000.00
5 EUR 3072.00
6 USD 500.00
7 CAD 100000.00
8 USD 250.00
15 EUR 6000.00
and currency_rates
currency_code year quarter from_usd_rate to_usd_rate
AED 2018 3 3.67285 0.27226813
ARS 2018 3 17.585 0.056866648
AUD 2018 3 1.27186 0.786250059
BRL 2018 3 3.1932 0.313165477
CAD 2018 3 1.2368 0.808538163
EUR 2018 3 0.852406 1.173149884
GBP 2018 3 0.747077 1.338550109
GHS 2018 3 4.4 0.227272727
I want to create a column in deals that converts deals where deals['Currency'] != USD, and apply the currency_rate['to_usd_rate'] to deals['Deal_Amount'] to get the USD converted amount.
So far i tried
def convert_amount(data):
if data['Currency']==currency_rates['currency_code']:
Converted_amount=data['Deal_Amount'] * currency_rates['to_usd_rate']
return Converted_amount
but its not working.
python pandas
asked Nov 9 at 19:06
TH14
255
I have two dataframes, deals
Currency Deal_Amount
0 USD 18.40
1 USD 18.40
2 USD 5559.00
3 USD 14300.00
4 USD 1000.00
5 EUR 3072.00
6 USD 500.00
7 CAD 100000.00
8 USD 250.00
15 EUR 6000.00
and currency_rates
currency_code year quarter from_usd_rate to_usd_rate
AED 2018 3 3.67285 0.27226813
ARS 2018 3 17.585 0.056866648
AUD 2018 3 1.27186 0.786250059
BRL 2018 3 3.1932 0.313165477
CAD 2018 3 1.2368 0.808538163
EUR 2018 3 0.852406 1.173149884
GBP 2018 3 0.747077 1.338550109
GHS 2018 3 4.4 0.227272727
I want to create a column in deals that converts deals where deals['Currency'] != USD, and apply the currency_rate['to_usd_rate'] to deals['Deal_Amount'] to get the USD converted amount.
So far i tried
def convert_amount(data):
if data['Currency']==currency_rates['currency_code']:
Converted_amount=data['Deal_Amount'] * currency_rates['to_usd_rate']
return Converted_amount
but its not working.
python pandas
python pandas
asked Nov 9 at 19:06
TH14
255
asked Nov 9 at 19:06
TH14
255
asked Nov 9 at 19:06
TH14
255
asked Nov 9 at 19:06
TH14
255
asked Nov 9 at 19:06
TH14
255
255
add a comment |
add a comment |
1 Answer
1
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up vote
0
down vote
accepted
You can merge and fillna with 1 to use as new rate
A = df1.merge(df2, left_on='Currency', right_on='currency_code', how='left').fillna(1)
df1['converted'] = A['Deal_Amount']*A['to_usd_rate']
output
index Currency Deal_Amount converted
0 0 USD 18.4 18.400000
1 1 USD 18.4 18.400000
2 2 USD 5559.0 5559.000000
3 3 USD 14300.0 14300.000000
4 4 USD 1000.0 1000.000000
5 5 EUR 3072.0 3603.916444
6 6 USD 500.0 500.000000
7 7 CAD 100000.0 80853.816300
8 8 USD 250.0 250.000000
9 15 EUR 6000.0 7038.899304
answered Nov 9 at 19:24
Yuca
2,6192525
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
accepted
You can merge and fillna with 1 to use as new rate
A = df1.merge(df2, left_on='Currency', right_on='currency_code', how='left').fillna(1)
df1['converted'] = A['Deal_Amount']*A['to_usd_rate']
output
index Currency Deal_Amount converted
0 0 USD 18.4 18.400000
1 1 USD 18.4 18.400000
2 2 USD 5559.0 5559.000000
3 3 USD 14300.0 14300.000000
4 4 USD 1000.0 1000.000000
5 5 EUR 3072.0 3603.916444
6 6 USD 500.0 500.000000
7 7 CAD 100000.0 80853.816300
8 8 USD 250.0 250.000000
9 15 EUR 6000.0 7038.899304
answered Nov 9 at 19:24
Yuca
2,6192525
add a comment |
up vote
0
down vote
accepted
You can merge and fillna with 1 to use as new rate
A = df1.merge(df2, left_on='Currency', right_on='currency_code', how='left').fillna(1)
df1['converted'] = A['Deal_Amount']*A['to_usd_rate']
output
index Currency Deal_Amount converted
0 0 USD 18.4 18.400000
1 1 USD 18.4 18.400000
2 2 USD 5559.0 5559.000000
3 3 USD 14300.0 14300.000000
4 4 USD 1000.0 1000.000000
5 5 EUR 3072.0 3603.916444
6 6 USD 500.0 500.000000
7 7 CAD 100000.0 80853.816300
8 8 USD 250.0 250.000000
9 15 EUR 6000.0 7038.899304
answered Nov 9 at 19:24
Yuca
2,6192525
add a comment |
up vote
0
down vote
accepted
up vote
0
down vote
accepted
You can merge and fillna with 1 to use as new rate
A = df1.merge(df2, left_on='Currency', right_on='currency_code', how='left').fillna(1)
df1['converted'] = A['Deal_Amount']*A['to_usd_rate']
output
index Currency Deal_Amount converted
0 0 USD 18.4 18.400000
1 1 USD 18.4 18.400000
2 2 USD 5559.0 5559.000000
3 3 USD 14300.0 14300.000000
4 4 USD 1000.0 1000.000000
5 5 EUR 3072.0 3603.916444
6 6 USD 500.0 500.000000
7 7 CAD 100000.0 80853.816300
8 8 USD 250.0 250.000000
9 15 EUR 6000.0 7038.899304
answered Nov 9 at 19:24
Yuca
2,6192525
You can merge and fillna with 1 to use as new rate
A = df1.merge(df2, left_on='Currency', right_on='currency_code', how='left').fillna(1)
df1['converted'] = A['Deal_Amount']*A['to_usd_rate']
output
index Currency Deal_Amount converted
0 0 USD 18.4 18.400000
1 1 USD 18.4 18.400000
2 2 USD 5559.0 5559.000000
3 3 USD 14300.0 14300.000000
4 4 USD 1000.0 1000.000000
5 5 EUR 3072.0 3603.916444
6 6 USD 500.0 500.000000
7 7 CAD 100000.0 80853.816300
8 8 USD 250.0 250.000000
9 15 EUR 6000.0 7038.899304
answered Nov 9 at 19:24
Yuca
2,6192525
answered Nov 9 at 19:24
Yuca
2,6192525
answered Nov 9 at 19:24
Yuca
2,6192525
answered Nov 9 at 19:24
Yuca
2,6192525
2,6192525
add a comment |
add a comment |
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