如何移动 pandas 中的列

Question

我有 pyarrow table 和 header 这样的：['column1','column2','column3','column4','column5' ] 我想交换和模式列 header 和数据： ['column1','column2','column5','column3','column4' ] 我如何使用 pandas 或 pyarrow

Answer 1

df = df[['column1','column2','column5','column3','column4' ]]

这将重新排列列

Answer 2

在 PyArrow 中，您可以尝试使用 select() 方法：

import pyarrow as pa

# Define an example pa.Table
n_legs = pa.array([2, 4, 5, 100])
animals = pa.array(["Flamingo", "Horse", "Brittle stars", "Centipede"])
names = ["n_legs", "animals"]
table = pa.table([n_legs, animals], names=names)

# Select columns
table.select([1,0])

你会得到：

>>> table.select([1,0])
pyarrow.Table
animals: string
n_legs: int64
----
animals: [["Flamingo","Horse","Brittle stars","Centipede"]]
n_legs: [[2,4,5,100]]

对比原来的：

>>> table
pyarrow.Table
n_legs: int64
animals: string
----
n_legs: [[2,4,5,100]]
animals: [["Flamingo","Horse","Brittle stars","Centipede"]]

将 Pandas 数据帧转换为 PyArrow 时，您还可以使用自定义模式 table:

import pyarrow as pa
import pandas as pd

# Define Pandas dataframe
df = pd.DataFrame({'year': [2020, 2022, 2019, 2021],
                   'n_legs': [2, 4, 5, 100],
                   'animals': ["Flamingo", "Horse", "Brittle stars", "Centipede"]})

# Define custom PyArrow schema
my_schema = pa.schema([
    pa.field('n_legs', pa.int64()),
    pa.field('animals', pa.string()),
    pa.field('year', pa.int64())
])

# Read Pandas dataframe as PyArrow table with specified schema
table = pa.table(df, my_schema)

你会得到：

>>> table.to_pandas()
   n_legs        animals  year
0       2       Flamingo  2020
1       4          Horse  2022
2       5  Brittle stars  2019
3     100      Centipede  2021
>>> df
   year  n_legs        animals
0  2020       2       Flamingo
1  2022       4          Horse
2  2019       5  Brittle stars
3  2021     100      Centipede

Answer 3

在pyarrow中你可以这样做：

columns = ['column1', 'column2']
table.select(columns)

如何移动 pandas 中的列

how to move columns in pandas

python

pandas

pyarrow

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