pandas, apply with args which are dataframe row entries
<p>I have a pandas dataframe 'df' with two columns 'A' and 'B', I have a function with two arguments</p>

<pre><code>def myfunction(B, A):
    # do something here to get the result
    return result
</code></pre>

<p>and I would like to apply it row-by-row to df using the 'apply' function</p>

<pre><code>df['C'] = df['B'].apply(myfunction, args=(df['A'],))
</code></pre>

<p>but I get the error</p>

<pre><code>ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
</code></pre>

<p>whats happening here, it seems it takes df['A'] as the whole series! not just the row entry from that series as required.</p>

<p>I think you need:</p>

<pre><code>import pandas as pd
df = pd.DataFrame({'A':[1,2,3],
                   'B':[4,5,6]})

print (df)
   A  B
0  1  4
1  2  5
2  3  6

def myfunction(B, A):
    #some staff  
    result = B + A 
    # do something here to get the result
    return result

df['C'] = df.apply(lambda x: myfunction(x.B, x.A), axis=1)
print (df)
   A  B  C
0  1  4  5
1  2  5  7
2  3  6  9
</code></pre>

<p>Or:</p>

<pre><code>def myfunction(x):

    result = x.B + x.A
    # do something here to get the result
    return result

df['C'] = df.apply(myfunction, axis=1)
print (df)
   A  B  C
0  1  4  5
1  2  5  7
2  3  6  9
</code></pre>

python pandas apply args