使用 Python 一步删除 csv 中的特定行和列

Question

我有一个 csv 文件，我需要在其中删除第二行和第三行以及第 3 到第 18 列。我能够分两步让它工作，这产生了一个临时文件。我在想必须有一个更好、更紧凑的方法来做到这一点。任何建议将不胜感激。

另外，如果我想删除多个列范围，我该如何在这段代码中指定。例如，如果我想删除第 25 到 29 列，除了已经指定的第 3 到 18 列，我将如何添加到代码中？谢谢

remove_from = 2
remove_to = 17

with open('file_a.csv', 'rb') as infile, open('interim.csv', 'wb') as outfile: 

    reader = csv.reader(infile)
    writer = csv.writer(outfile)

    for row in reader:
        del row[remove_from : remove_to]
        writer.writerow(row)

with open('interim.csv', 'rb') as infile, open('file_b.csv', 'wb') as outfile:

    reader = csv.reader(infile)
    writer = csv.writer(outfile)

    writer.writerow(next(reader))  

    reader.next()
    reader.next()

    for row in reader: 
        writer.writerow(row)

Answer 1

这是一种熊猫方法：

第 1 步，创建示例数据框

import pandas as pd

# Create sample CSV-file (100x100)
df = pd.DataFrame(np.arange(10000).reshape(100,100))
df.to_csv('test.csv', index=False)

第 2 步，施展魔法

import pandas as pd
import numpy as np

# Read first row to determine size of columns
size = pd.read_csv('test.csv',nrows=0).shape[1]

#want to remove columns 25 to 29, in addition to columns 3 to 18 already specified,
# Ok so let's create an array with the length of dataframe deleting the ranges
ranges = np.r_[3:19,25:30]
ar = np.delete(np.arange(size),ranges)

# Now let's read the dataframe
# let us also skip rows 2 and 3
df = pd.read_csv('test.csv', skiprows=[2,3], usecols=ar)

# And output
dt.to_csv('output.csv', index=False)

还有证明：