擅长:python、mysql、java
<p>我还没有测试代码,但我会这样做</p>
<pre><code># make your code clear (what is 2?)
df = df_conversion_dolar_2
precio_dolar = 800
# first, let's make a boolean selector
dolar_select = df['Currency'] == '$$$'
# Selecting dollar rows at the column Amount is as follow:
# This line is only to show you what happens and is not
# needed in your final code
df.loc[dolar_select, 'Amount']
# Anyway, now we apply your function to the selected data:
df['ED'] = df.loc[dolar_select, 'Amount'].map(lambda x: (x*1000)/float(precio_dolar))
# Finally, fill the NaN values in your dataframe (the non selected rows)
df.loc[df['ED'].isna(), 'ED'] = df['Amount']
</code></pre>