向使用csv_read导入的DASK数据帧的列添加值 [英] Add a value to a column of DASK data-frames imported using csv_read

问题描述

假设使用csv_read将五个文件导入到DASK.为此，我使用以下代码:

Suppose that five files are imported to the DASK using csv_read. To do this, I use this code:

import dask.dataframe as dd
data = dd.read_csv(final_file_list_msg, header = None)

每个文件都有十列.我想在文件1的第一列中添加1，在文件2的第一列中添加2，在文件3的第一列中添加3，依此类推.

Every file has ten columns. I want to add 1 to the first column of file 1, 2 to the first column of file 2, 3 to the first column of file 3, etc.

推荐答案

假设您遵循此方案有几个文件:

Let assume that you have several files following this scheme:

dummy/
├── file01.csv
├── file02.csv
├── file03.csv

首先，我们通过创建它们

First we create them via

import os
import pandas as pd
import numpy as np
import dask.dataframe as dd
from dask import delayed

fldr = "dummy"

if not os.path.exists(fldr):
    os.mkdir(fldr)

for i in range(10):
    df = pd.DataFrame(np.random.rand(5,3))
    df.to_csv("{}/file{:02}.csv".format(fldr,i+1),
              index=False)

创建的文件列表为fns = sorted(os.listdir(fldr))

然后我们编写一个给定路径fn的函数:

Then we write a function that given the path fn:

• 读取文件
• 在fileXX.csv
中取数字XX
• 在第一列中插入int(XX)

• read the file
• takes the number XX in fileXX.csv
• insert int(XX) on the first column

那是

def addCol(fn):
    df = pd.read_csv(os.path.join(fldr, fn))
    first = int(fn.split(".")[0][-2:])
    df.insert(0, "first", first)
    return df

我们希望这个乐趣成为delayed，我们可以使用装饰器@delayed或使用delayed包装函数来实现它.因此，为了获得所需的输出，我们应该(相应地)触发

We wanted this fun to be delayed and we can achieve it using the decorator @delayed or wrapping the function with delayed. So to obtain the desired output we should fire (accordingly)

• ddf = dd.from_delayed([addCol(fn) for fn in fns])
• ddf = dd.from_delayed([delayed(addCol)(fn) for fn in fns])

• ddf = dd.from_delayed([addCol(fn) for fn in fns])
• ddf = dd.from_delayed([delayed(addCol)(fn) for fn in fns])

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