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