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])
这篇关于向使用csv_read导入的DASK数据帧的列添加值的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!