Pandas - 将值提取到基本的python float

Question

我试图将pandas数据帧中的单元格提取为简单的浮点数。我正在尝试

prediction = pd.to_numeric(baseline.ix[(baseline['Weekday']==5) & (baseline['Hour'] == 8)]['SmsOut'])

然而，这会返回

128   -0.001405
Name: SmsOut, dtype: float64

我希望它只返回一个simle Python float：-0.001405 我怎么能这样做？

Answer 1

输出为Series，只有一个值，因此更有可能是解决方案：

• Series.item
• 按values转换为numpy array并通过索引选择第一个值
• 按iloc或iat
按位置选择

prediction = pd.to_numeric(baseline.loc[(baseline['Weekday'] ==5 ) & 
                                        (baseline['Hour'] == 8), 'SmsOut'])

print (prediction.item())

print (prediction.values[0])

print (prediction.iloc[0])
print (prediction.iat[0])

样品：

baseline = pd.DataFrame({'Weekday':[5,3], 
                         'Hour':[8,4], 
                         'SmsOut':[-0.001405,6]}, index=[128,130])
print (baseline)
     Hour    SmsOut  Weekday
128     8 -0.001405        5
130     4  6.000000        3

prediction = pd.to_numeric(baseline.loc[(baseline['Weekday'] ==5 ) & 
                                        (baseline['Hour'] == 8), 'SmsOut'])

print (prediction)
128   -0.001405
Name: SmsOut, dtype: float64

print (prediction.item())
-0.001405
print (prediction.values[0])
-0.001405
print (prediction.iloc[0])
-0.001405
print (prediction.iat[0])
-0.001405