Python 按重复顺序填充列

我有一个如下所示的数据框，我想在重复模式（4组）中插入某些值。因此，我的数据帧看起来像“df2”（显示在“df”下面）。我希望此模式继续，直到行结束（在本例中是向下10行）

我们可以在这里使用：

---

---

另一种方法是基于

NumPy

的，它是对df.shape[0]之前的序列进行排序。请注意，如文档中所述，此方法使用输入数组的重复副本填充新数组：

a = np.array(['MS', 'MU', 'MN','MO'])
df['Code'] = np.resize(a, df.shape[0])

---

第一种方法的工作原理是创建一个将索引映射到序列的字典，其中迭代器已经循环了尽可能多的次数，以适应数据帧的

索引

大小。这是因为

zip

将合并两个iterables中的元素，直到第一个iterables用尽为止，第一个iterables总是非无限的，很明显：）

---

然后，我们可以通过将索引与创建的字典映射来将其分配给新列

这不是最优雅的解决方案，但非常直观

#create a dataframe with 10 rows
import pandas as pd
df = pd.DataFrame()
df['ID'] = [1,2,3,4,5,6,7,8,9,10]

#create a list containg the seqence of values we want to repeat
values = ['a','b','c','d']

#define the number of times this series can be repeated for a given dataframe length
n_repeats = len(df) % len(values)

#define new column as a list
repeated_values = []

#repeatedly extend the list
for iteration in range(1,n_repeats+2):
    repeated_values.extend(values)

#create a column which takes the repeated values and stops at the length of the dataframe
df['repeated_values'] = repeated_values[0:len(df)]

print(df)

   ID  Descrip Code
0   1      NaN   MS
1   2      3.0   MU
2   3      4.0   MN
3   4      7.0   MO
4   5      NaN   MS
5   6     11.0   MU
6   7      NaN   MN
7   8     20.0   MO
8   9     22.0   MS
9  10     15.0   MU

a = np.array(['MS', 'MU', 'MN','MO'])
df['Code'] = np.resize(a, df.shape[0])

print(dict(zip(df.index, cycle(i))))
# {0: 'MS', 1: 'MU', 2: 'MN', 3: 'MO', 4: 'MS', 5: 'MU'...

#create a dataframe with 10 rows
import pandas as pd
df = pd.DataFrame()
df['ID'] = [1,2,3,4,5,6,7,8,9,10]

#create a list containg the seqence of values we want to repeat
values = ['a','b','c','d']

#define the number of times this series can be repeated for a given dataframe length
n_repeats = len(df) % len(values)

#define new column as a list
repeated_values = []

#repeatedly extend the list
for iteration in range(1,n_repeats+2):
    repeated_values.extend(values)

#create a column which takes the repeated values and stops at the length of the dataframe
df['repeated_values'] = repeated_values[0:len(df)]