iterate over pandas dataframe and update the value - 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