将简单的移动平均值作为附加列添加到python DataFrame

Question

我在sales_training.csv中有如下销售数据：

time_period sales
1   127
2   253
3   123
4   253
5   157
6   105
7   244
8   157
9   130
10  221
11  132
12  265

我想添加包含移动平均值的第三列。 我的代码-

import pandas as pd
df = pd.read_csv("./Sales_training.csv", index_col="time_period")
periods = df.index.tolist()
period = int(input("Enter a period for the moving average :"))
sum1 = 0
for i in periods:
    if i < period:
        df['forecast'][i] = i
    else:
        for j in range(period):
            sum1 += df['sales'][i-j]
        df['forecast'][i] = sum1/period
        sum1 = 0
print(df)
df.to_csv("./forecast_mannual.csv")

这在行df['forecast'][i] = i处给出了KeyError: 'forecast' 。 有什么问题

Answer 1

一个简单的解决方案，只需df['forecast'] = df['sales']

import pandas as pd
df = pd.read_csv("./Sales_training.csv", index_col="time_period")
periods = df.index.tolist()
period = int(input("Enter a period for the moving average :"))
sum1 = 0
df['forecast'] = df['sales'] # add one line
for i in periods:
    if i < period:
        df['forecast'][i] = i
    else:
        for j in range(period):
            sum1 += df['sales'][i-j]
        df['forecast'][i] = sum1/period
        sum1 = 0
print(df)
df.to_csv("./forecast_mannual.csv")

Answer 2

您的代码给出'keyerror'是因为引用'forecast'的列值的方式不正确。由于您的代码是第一次运行，因此'forecast'列尚未创建，当它尝试为第一次迭代引用df'forecast '时，它给出了关键错误。

在这里，我们的任务是更新动态创建的称为“预测”的新列中的值。 因此，您可以编写df.at [i，'forecast']代替df ['forecast'] [i]。

代码中还有另一个问题。当i的值小于周期时，您将分配``i''来预测我认为不正确的预测，在这种情况下它不应显示任何内容。

这是我的更正代码版本：

 import pandas as pd df = pd.read_csv("./sales.csv", index_col="time_period") periods = df.index.tolist() period = int(input("Enter a period for the moving average :")) sum1 = 0 for i in periods: print(i) if i < period: df.at[i,'forecast'] = '' else: for j in range(period): sum1 += df['sales'][ij] df['forecast'][i] = sum1/period sum1 = 0 print(df) df.to_csv("./forecast_mannual.csv") 

当我输入period = 2来计算移动平均值时的输出：

希望这可以帮助。