python - 试图用for循环填充数据框中的新列

基于另一列的值，我想用for循环填充新列。遗憾的是没有得到我需要的结果；

profit = []

# For each row in the column,
for row in df3['Result']:
    # if value is;
    if row == 'H':
        # Append a Profit/Loss
        profit.append(df3['column value H'])
    # else, if value is,
    elif row == 'D':
        # Append a Profit/Loss
        profit.append(df3['column value D'])
    # otherwise,
    else:
        # Append a Profit/Loss
        profit.append(df3['column value A'])

df3['profit'] = profit

最佳答案

我认为您需要加倍numpy.where：

df3['profit'] = np.where(df3['Result'] == 'H', df3['column value H'],
                np.where(df3['Result'] == 'D', df3['column value D'], df3['column value A']))

样品：

df3 = pd.DataFrame({'Result':['H','D','E'],
                   'column value H':[4,5,6],
                   'column value D':[7,8,9],
                   'column value A':[1,3,5]})

print (df3)
  Result  column value A  column value D  column value H
0      H               1               7               4
1      D               3               8               5
2      E               5               9               6

df3['profit'] = np.where(df3['Result'] == 'H', df3['column value H'],
                np.where(df3['Result'] == 'D', df3['column value D'], df3['column value A']))

print (df3)
  Result  column value A  column value D  column value H  profit
0      H               1               7               4       4
1      D               3               8               5       8
2      E               5               9               6       5

时间：

In [198]: %timeit (jez(df3))
100 loops, best of 3: 7.59 ms per loop

In [199]: %timeit (wwii(df4))
1 loop, best of 3: 1.49 s per loop

In [200]: %timeit (wwii1(df5))
1 loop, best of 3: 4.48 s per loop

测试代码：

df3 = pd.DataFrame({'Result':['H','D','E'],
                   'column value H':[4,5,6],
                   'column value D':[7,8,9],
                   'column value A':[1,3,5]})

print (df3)
df3 = pd.concat([df3]*10000).reset_index(drop=True)

df4 = df3.copy()
df5 = df3.copy()

def jez(df3):
    df3['profit'] = np.where(df3['Result'] == 'H', df3['column value H'],
                    np.where(df3['Result'] == 'D', df3['column value D'], df3['column value A']))

    return (df3)

def foo(series):
    # d maps Result column values to DataFrame/Series column names
    d = {'H':'column value H', 'D':'column value D'}
    try:
        return series[d[series['Result']]]
    except KeyError as e:
        return series['column value A']

def wwii(df3):
    df3['Profit'] = df3.apply(foo, axis = 1)
    return df3

def wwii1(df3):
    profit = []
    for row in df3.iterrows():
        series = row[1]
        if series.Result == 'H':
            # Append a Profit/Loss
            profit.append(series['column value H'])
        # else, if value is,
        elif series.Result == 'D':
            # Append a Profit/Loss
            profit.append(series['column value D'])
        # otherwise,
        else:
            # Append a Profit/Loss
            profit.append(series['column value A'])

    df3['profit'] = profit
    return df3

print (jez(df3))
print (wwii(df4))
print (wwii1(df5))

关于python - 试图用for循环填充数据框中的新列，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/40636572/