如何在Pandas DataFrame中移动列？

我们可以使用Pandas中的shift()方法来移动DataFrame的列，而无需重写整个DataFrame。shift()接受以下参数

shift(self, periods=1, freq=None, axis=0, fill_value=None)

periods 要移动的周期数。它也可以是负数。
axis 它取一个布尔值；如果要移动索引，则为0；如果要移动列，则为1。
fill_value 它将替换缺失值。

让我们举个例子，看看如何使用这个 shift() 方法。

步骤

创建一个二维，大小可变，潜在异构的表格数据 df。
打印输入的DataFrame，df。
通过使用 df [“column_name] = df.column_name.shift() 选择一列并移动它
打印更新后的DataFrame。

示例

import pandas as pd

df = pd.DataFrame(
   dict(
      name=['John', 'Jacob', 'Tom', 'Tim', 'Ally'],
      marks=[89, 23, 100, 56, 90],
      subjects=["Math", "Physics", "Chemistry", "Biology", "English"]
   )
)

print "Input DataFrame is:\n", df

df["name"] = df.name.shift(1)
print "After shifting column name by 1:\n", df

df["marks"] = df.marks.shift(2)
print "After shifting column marks by 2:\n", df

df["subjects"] = df.subjects.shift(-1)
print "After shifting column subjects by -1:\n", df

输出

Input DataFrame is:
     name   marks   subjects
0    John    89         Math
1   Jacob    23      Physics
2     Tom   100    Chemistry
3     Tim    56      Biology
4    Ally    90      English

After shifting column name by 1:
     name   marks   subjects
0     NaN    89         Math
1    John    23      Physics
2   Jacob   100    Chemistry
3     Tom    56      Biology
4     Tim    90      English

After shifting column marks by 2:
     name   marks   subjects
0     NaN    100       Math
1    John    100    Physics
2   Jacob     89  Chemistry
3     Tom     23    Biology
4     Tim    100    English

After shifting column subjects by -1:
     name   marks   subjects
0     NaN   100      Physics
1    John   100    Chemistry
2   Jacob    89      Biology
3     Tom    23      English
4     Tim   100          NaN