在 Pandas 中复制行并添加一个新的（月）列

Question

我正在努力解决我确信是一个简单的问题。我有一个数据框，它的 1000 rows 是独一无二的。

这会按位置按类别显示expenses for the year。每个都有相同的类别组。

我想为每个站点的每项费用创建一个monthly budget 列。

我还想创建一个年初至今的预算列，该列将当年的总预算除以 12 以得出每月的数字。然后将其乘以月份（4 月 = 第 1 个月），得出年初至今的值 - 例如，5 月将是每月数字 * 2 等。

我正在尝试使用 pandas 来执行此操作。我试过了

    pd.DataFrame(np.repeat(budget.values,12,axis=0)) #replicate each row by 12

然后我的计划是遍历每个组中的每一行以添加月份，但我正在努力实现任何目标。

任何帮助将不胜感激。

（抱歉我无法正确粘贴表格 - 请看图片）

当前

+------------+-------------+--------+
|  Location  |  Expense    | Amount |
+------------+-------------+--------+
| Sheffield  | Electricity |  10000 |
| Sheffield  | Gas         |  12000 |
| Manchester | Electricity |  15000 |
| Manchester | Electricity |  13000 |
+------------+-------------+--------+

想要的

+------------+-------------+--------+--------+---------+-------+
|  Location  |  Expense    | Amount | Budget |  Month  |  YTD  |
+------------+-------------+--------+--------+---------+-------+
| Sheffield  | Electricity |  10000 |  10000 | April   |  1000 |
| Sheffield  | Electricity |  10000 |  10000 | May     |  2000 |
| Sheffield  | Electricity |  10000 |  10000 | June    |  3000 |
| Sheffield  | Electricity |  10000 |  10000 | July    |  4000 |
| Sheffield  | Electricity |  10000 |  10000 | August  |  5000 |
| Sheffield  | Electricity |  10000 |  10000 | Sep     |  6000 |
| Sheffield  | Electricity |  10000 |  10000 | Oct     |  7000 |
| Sheffield  | Electricity |  10000 |  10000 | Dec     |  8000 |
| Sheffield  | Electricity |  10000 |  10000 | Jan     |  9000 |
| Sheffield  | Electricity |  10000 |  10000 | Feb     | 10000 |
| Sheffield  | Electricity |  10000 |  10000 | March   | 11000 |
| Sheffield  | Gas         |  12000 |  20000 | April   |  2000 |
| Sheffield  | Gas         |  12000 |  20000 | May     |  4000 |
| Sheffield  | Gas         |  12000 |  20000 | June... |  6000 |
| Sheffield  | Gas         |  12000 |  20000 | ..March |  8000 |
| Manchester | Electricity |  15000 |  36000 | April   |  4000 |
| Manchester | Electricity |  15000 |  36000 | May     |  8000 |
+------------+-------------+--------+--------+---------+-------+

   

Answer 1

您可以创建您的特定月份表，将四月作为会计年度开始月份的数字 1。

import pandas as pd 
  
# intialise data from list. 
data = {'Month':['April', 'May', 'June', 'July', 'August', 'September', 'October', 'November', 'December', 'January', 'February', 'March'], \
        'Number':range(1,13), \
        'key': [1] * 12 }

  
# Create DataFrame 
df_months = pd.DataFrame(data)

生成这样的表格：

+------------+--------+-----+
| Month      | Number | key |
+------------+--------+-----+
| April      |  1     | 1   |
| May        |  2     | 1   |
| June       |  3     | 1   |
| July       |  4     | 1   |
| August     |  5     | 1   |
| September  |  6     | 1   |
| October    |  7     | 1   |
| November   |  8     | 1   |
| December   |  9     | 1   |
| January    |  10    | 1   |
| February   |  11    | 1   |
| March      |  12    | 1   |
+------------+--------+-----+

现在调整您的第二张表，我们称之为 df_amounts 以拥有一个虚构的键列 (key)，这将确保每个月都与每个位置/费用组合相连接：

df_amounts['key'] = 1

df_amounts：

+------------+-------------+--------+-----+
|  Location  |  Expense    | Amount | key |
+------------+-------------+--------+-----+
| Sheffield  | Electricity |  10000 | 1   |
| Sheffield  | Gas         |  12000 | 1   |
| Manchester | Electricity |  15000 | 1   |
| Manchester | Electricity |  13000 | 1   |
+------------+-------------+--------+-----+

然后加入key上的表格：

df = pd.merge(df_amounts, df_months, on="key", how="left")

获取下表：

+------------+-------------+--------+-----+-------+--------+
|  Location  |  Expense    | Amount | key | Month | Number | 
+------------+-------------+--------+-----+-------+--------+

现在将number 列除以12，然后将值与Amount 相乘，得到新列YTD。

df['YTD']= df['Amount'] * (df['Number'] / 12)

您每月的Budget 专栏的工作方式类似：

df['Budget']= df['Amount'] / 12