I am trying to iterate over a pandas dataframe and update the value if condition is met but i am getting an error.

for line, row in enumerate(df.itertuples(), 1):
    if row.Qty:
        if row.Qty == 1 and row.Price == 10:
            row.Buy = 1
AttributeError: can't set attribute

First iterating in pandas is possible, but very slow, so another vectorized solution are used.

I think you can use iterrows if you need iterating:

for idx, row in df.iterrows():
    if  df.loc[idx,'Qty'] == 1 and df.loc[idx,'Price'] == 10:
        df.loc[idx,'Buy'] = 1

But better is to use vectorized solutions – set value by boolean mask with loc:

mask = (df['Qty'] == 1) & (df['Price'] == 10)
df.loc[mask, 'Buy'] = 1

Or solution with mask:

df['Buy'] = df['Buy'].mask(mask, 1)

Or if you need if...else use numpy.where:

df['Buy'] = np.where(mask, 1, 0)

Samples.

Set values by conditions:

df = pd.DataFrame({'Buy': [100, 200, 50], 
                   'Qty': [5, 1, 1], 
                   'Name': ['apple', 'pear', 'banana'], 
                   'Price': [1, 10, 10]})

print (df)
   Buy    Name  Price  Qty
0  100   apple      1    5
1  200    pear     10    1
2   50  banana     10    1

mask = (df['Qty'] == 1) & (df['Price'] == 10)


df['Buy'] = df['Buy'].mask(mask, 1)
print (df)
   Buy    Name  Price  Qty
0  100   apple      1    5
1    1    pear     10    1
2    1  banana     10    1
df['Buy'] = np.where(mask, 1, 0)
print (df)
   Buy    Name  Price  Qty
0    0   apple      1    5
1    1    pear     10    1
2    1  banana     10    1

Ok, if you intend to set values in df then you need track the index values.

option 1
using itertuples

# keep in mind `row` is a named tuple and cannot be edited
for line, row in enumerate(df.itertuples(), 1):  # you don't need enumerate here, but doesn't hurt.
    if row.Qty:
        if row.Qty == 1 and row.Price == 10:
            df.set_value(row.Index, 'Buy', 1)

option 2
using iterrows

# keep in mind that `row` is a `pd.Series` and can be edited...
# ... but it is just a copy and won't reflect in `df`
for idx, row in df.iterrows():
    if row.Qty:
        if row.Qty == 1 and row.Price == 10:
            df.set_value(idx, 'Buy', 1)

option 3
using straight up loop with get_value

for idx in df.index:
    q = df.get_value(idx, 'Qty')
    if q:
        p = df.get_value(idx, 'Price')
        if q == 1 and p == 10:
            df.set_value(idx, 'Buy', 1)

pandas.DataFrame.set_value method is deprecated as of 0.21.0 pd.DataFrame.set_value

Use pandas.Dataframe.at

for index, row in df.iterrows():
        if row.Qty and row.Qty == 1 and row.Price == 10:
            df.at[index,'Buy'] = 1