如何在python中将csv文件拆分为固定数量的列？

Question

您好，我有一个包含 622 列的 csv 文件。我需要将它分成 100-100 列。我尝试了一些代码，但没有得到输出。请告诉我我在这里做错了什么。

例子：

文件 - cleanBaby.csv

在我想要的输出中：

cleanBaby1.csv ---- 1 to 100 columns
cleanBaby2.csv ---- 101 to 200 
cleanBaby3,csv ---- 201 to 300
cleanBaby4.csv ---- 301 to 400
cleanBaby5.csv ---- 401 to 500
cleanBaby6.csv ---- 501 to 600
cleanBaby7.csv ---- 601 to 622

我试过下面的代码-

df = pd.read_csv(r"D:\Users\SPate233\Downloads\iMedical\raw_layer\cleanBaby.csv", delimiter=',')
lst = df.columns

print(len(lst))
csvfile = open(r'D:\Users\SPate233\Downloads\iMedical\raw_layer\cleanBaby.csv', 'r', encoding='utf-8').readlines()
def chunks(lst, n):
    for i in range(0, len(lst), n):
        yield lst[i:i + n]

for n, headers_chunk in enumerate(chunks(lst, 100)):
    with open(r"D:\Users\SPate233\Downloads\iMedical\raw_layer\cleanBaby{}.csv".format(n), "w") as f:
        for header in headers_chunk:
            f.write(header + ",")
            f.writelines(csvfile[n+100:n])

Answer 1

使用pandas.DataFrame.groupby 和enumerate 的一种方式：

# Sample data
df = pd.DataFrame(np.random.random((500, 622)))

# Make grouper
indices = np.arange(df.shape[1])//100

for n, (k, d) in enumerate(df.groupby(indices, axis=1), 1):
    name = "test%s.csv" % n
    print(name, d.shape)
    d.to_csv(name, index=False)

输出：

test1.csv (500, 100)
test2.csv (500, 100)
test3.csv (500, 100)
test4.csv (500, 100)
test5.csv (500, 100)
test6.csv (500, 100)
test7.csv (500, 22)