我正在尝试迭代pandas数据帧并在条件满足时更新值但是我收到错误。
blur
答案 0 :(得分:22)
首先在pandas中迭代是可能的,但速度非常慢,因此使用了另一种向量化解决方案。
如果您需要迭代,我认为您可以使用iterrows
:
for idx, row in df.iterrows():
if df.loc[idx,'Qty'] == 1 and df.loc[idx,'Price'] == 10:
df.loc[idx,'Buy'] = 1
但更好的是使用矢量化解决方案 - 通过布尔掩码设置值loc
:
mask = (df['Qty'] == 1) & (df['Price'] == 10)
df.loc[mask, 'Buy'] = 1
或使用mask
的解决方案:
df['Buy'] = df['Buy'].mask(mask, 1)
或者如果您需要if...else
使用numpy.where
:
df['Buy'] = np.where(mask, 1, 0)
<强>样品强>
按条件设置值:
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
答案 1 :(得分:9)
好的,如果您打算在df
中设置值,则需要跟踪index
值。
选项1
使用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)
选项2
使用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)
选项3
使用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)
答案 2 :(得分:1)
pandas.DataFrame.set_value方法自0.21.0 pd.DataFrame.set_value以来已弃用
for index, row in df.iterrows():
if row.Qty and row.Qty == 1 and row.Price == 10:
df.at[index,'Buy'] = 1