Python 如何将csv文件中的列附加到一个文件中？

我正在用Python编写一个脚本。我有一堆csv文件，每个文件包含一列。这些文件可能是这样的：

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

[['Header0', 'text_0_0', 'text_0_1', 'text_0_2', 'text_0_3', 'text_0_4'], # one files data
 ['Header1', 'text_1_0', 'text_1_1', 'text_1_2', 'text_1_3', 'text_1_4'], 
 ['Header2', 'text_2_0', 'text_2_1', 'text_2_2', 'text_2_3', 'text_2_4'], 
 ['Header3', 'text_3_0', 'text_3_1', 'text_3_2', 'text_3_3', 'text_3_4'], 
 ['Header4', 'text_4_0', 'text_4_1', 'text_4_2', 'text_4_3', 'text_4_4'], 
 ['Header5', 'text_5_0', 'text_5_1', 'text_5_2', 'text_5_3', 'text_5_4'], 
 ['Header6', 'text_6_0', 'text_6_1', 'text_6_2', 'text_6_3', 'text_6_4'], 
 ['Header7', 'text_7_0', 'text_7_1', 'text_7_2', 'text_7_3', 'text_7_4'], 
 ['Header8', 'text_8_0', 'text_8_1', 'text_8_2', 'text_8_3', 'text_8_4'], 
 ['Header9', 'text_9_0', 'text_9_1', 'text_9_2', 'text_9_3', 'text_9_4']]

FirstFile.csv

First
a
b
c

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

SecondFile.csv

Second
a2
b2
c2

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

我希望创建一个结果文件（我们称之为result.csv），该文件如下所示：

First    Second
a        a2
b        b2
c        c2

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

[('Header0', 'Header1', 'Header2', 'Header3', 'Header4', 'Header5', 'Header6', 'Header7', 'Header8', 'Header9'), 
 ('text_0_0', 'text_1_0', 'text_2_0', 'text_3_0', 'text_4_0', 'text_5_0', 'text_6_0', 'text_7_0', 'text_8_0', 'text_9_0'), 
 ('text_0_1', 'text_1_1', 'text_2_1', 'text_3_1', 'text_4_1', 'text_5_1', 'text_6_1', 'text_7_1', 'text_8_1', 'text_9_1'), 
 ('text_0_2', 'text_1_2', 'text_2_2', 'text_3_2', 'text_4_2', 'text_5_2', 'text_6_2', 'text_7_2', 'text_8_2', 'text_9_2'), 
 ('text_0_3', 'text_1_3', 'text_2_3', 'text_3_3', 'text_4_3', 'text_5_3', 'text_6_3', 'text_7_3', 'text_8_3', 'text_9_3'), 
 ('text_0_4', 'text_1_4', 'text_2_4', 'text_3_4', 'text_4_4', 'text_5_4', 'text_6_4', 'text_7_4', 'text_8_4', 'text_9_4')]

---

如何在python中将所有csv追加到一个目录中，并追加所有列，以便生成一个类似于此的result.csv（当然，还有更多列）？

您可以尝试使用Pandas

import pandas as pd
result = pd.concat([ pd.read_csv(f) for f in filenames ],axis=1)
result.to_csv("result.csv",index=False)

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

创建文件名列表（例如，

文件名

）

进口大熊猫

在列表理解中使用concat函数

---

你可以试着用熊猫

import pandas as pd
result = pd.concat([ pd.read_csv(f) for f in filenames ],axis=1)
result.to_csv("result.csv",index=False)

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

创建文件名列表（例如，

文件名

）

进口大熊猫

在列表理解中使用concat函数

---

您可以使用csv模块：

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

创建10个文件：

filenames = []
for i in range(10):
    filenames.append(f"file_{i}.txt")
    with open(filenames[-1],"w") as f:
        f.write(f"Header{i}\n")
        for row in range(5):
            f.write(f"text_{i}_{row}\n")

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

读取所有文件：

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

检查是否正常：

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

with open("joined.txt") as j:
    print(j.read())

输出：

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

Header0,Header1,Header2,Header3,Header4,Header5,Header6,Header7,Header8,Header9
text_0_0,text_1_0,text_2_0,text_3_0,text_4_0,text_5_0,text_6_0,text_7_0,text_8_0,text_9_0
text_0_1,text_1_1,text_2_1,text_3_1,text_4_1,text_5_1,text_6_1,text_7_1,text_8_1,text_9_1
text_0_2,text_1_2,text_2_2,text_3_2,text_4_2,text_5_2,text_6_2,text_7_2,text_8_2,text_9_2
text_0_3,text_1_3,text_2_3,text_3_3,text_4_3,text_5_3,text_6_3,text_7_3,text_8_3,text_9_3
text_0_4,text_1_4,text_2_4,text_3_4,text_4_4,text_5_4,text_6_4,text_7_4,text_8_4,text_9_4

---

数据

如下所示：

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

[['Header0', 'text_0_0', 'text_0_1', 'text_0_2', 'text_0_3', 'text_0_4'], # one files data
 ['Header1', 'text_1_0', 'text_1_1', 'text_1_2', 'text_1_3', 'text_1_4'], 
 ['Header2', 'text_2_0', 'text_2_1', 'text_2_2', 'text_2_3', 'text_2_4'], 
 ['Header3', 'text_3_0', 'text_3_1', 'text_3_2', 'text_3_3', 'text_3_4'], 
 ['Header4', 'text_4_0', 'text_4_1', 'text_4_2', 'text_4_3', 'text_4_4'], 
 ['Header5', 'text_5_0', 'text_5_1', 'text_5_2', 'text_5_3', 'text_5_4'], 
 ['Header6', 'text_6_0', 'text_6_1', 'text_6_2', 'text_6_3', 'text_6_4'], 
 ['Header7', 'text_7_0', 'text_7_1', 'text_7_2', 'text_7_3', 'text_7_4'], 
 ['Header8', 'text_8_0', 'text_8_1', 'text_8_2', 'text_8_3', 'text_8_4'], 
 ['Header9', 'text_9_0', 'text_9_1', 'text_9_2', 'text_9_3', 'text_9_4']]

它看起来像：

First    Second
a        a2
b        b2
c        c2

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

[('Header0', 'Header1', 'Header2', 'Header3', 'Header4', 'Header5', 'Header6', 'Header7', 'Header8', 'Header9'), 
 ('text_0_0', 'text_1_0', 'text_2_0', 'text_3_0', 'text_4_0', 'text_5_0', 'text_6_0', 'text_7_0', 'text_8_0', 'text_9_0'), 
 ('text_0_1', 'text_1_1', 'text_2_1', 'text_3_1', 'text_4_1', 'text_5_1', 'text_6_1', 'text_7_1', 'text_8_1', 'text_9_1'), 
 ('text_0_2', 'text_1_2', 'text_2_2', 'text_3_2', 'text_4_2', 'text_5_2', 'text_6_2', 'text_7_2', 'text_8_2', 'text_9_2'), 
 ('text_0_3', 'text_1_3', 'text_2_3', 'text_3_3', 'text_4_3', 'text_5_3', 'text_6_3', 'text_7_3', 'text_8_3', 'text_9_3'), 
 ('text_0_4', 'text_1_4', 'text_2_4', 'text_3_4', 'text_4_4', 'text_5_4', 'text_6_4', 'text_7_4', 'text_8_4', 'text_9_4')]

---

您可以使用csv模块：

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

创建10个文件：

filenames = []
for i in range(10):
    filenames.append(f"file_{i}.txt")
    with open(filenames[-1],"w") as f:
        f.write(f"Header{i}\n")
        for row in range(5):
            f.write(f"text_{i}_{row}\n")

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

读取所有文件：

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

检查是否正常：

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

with open("joined.txt") as j:
    print(j.read())

输出：

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

Header0,Header1,Header2,Header3,Header4,Header5,Header6,Header7,Header8,Header9
text_0_0,text_1_0,text_2_0,text_3_0,text_4_0,text_5_0,text_6_0,text_7_0,text_8_0,text_9_0
text_0_1,text_1_1,text_2_1,text_3_1,text_4_1,text_5_1,text_6_1,text_7_1,text_8_1,text_9_1
text_0_2,text_1_2,text_2_2,text_3_2,text_4_2,text_5_2,text_6_2,text_7_2,text_8_2,text_9_2
text_0_3,text_1_3,text_2_3,text_3_3,text_4_3,text_5_3,text_6_3,text_7_3,text_8_3,text_9_3
text_0_4,text_1_4,text_2_4,text_3_4,text_4_4,text_5_4,text_6_4,text_7_4,text_8_4,text_9_4

---

数据

如下所示：

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

[['Header0', 'text_0_0', 'text_0_1', 'text_0_2', 'text_0_3', 'text_0_4'], # one files data
 ['Header1', 'text_1_0', 'text_1_1', 'text_1_2', 'text_1_3', 'text_1_4'], 
 ['Header2', 'text_2_0', 'text_2_1', 'text_2_2', 'text_2_3', 'text_2_4'], 
 ['Header3', 'text_3_0', 'text_3_1', 'text_3_2', 'text_3_3', 'text_3_4'], 
 ['Header4', 'text_4_0', 'text_4_1', 'text_4_2', 'text_4_3', 'text_4_4'], 
 ['Header5', 'text_5_0', 'text_5_1', 'text_5_2', 'text_5_3', 'text_5_4'], 
 ['Header6', 'text_6_0', 'text_6_1', 'text_6_2', 'text_6_3', 'text_6_4'], 
 ['Header7', 'text_7_0', 'text_7_1', 'text_7_2', 'text_7_3', 'text_7_4'], 
 ['Header8', 'text_8_0', 'text_8_1', 'text_8_2', 'text_8_3', 'text_8_4'], 
 ['Header9', 'text_9_0', 'text_9_1', 'text_9_2', 'text_9_3', 'text_9_4']]

它看起来像：

First    Second
a        a2
b        b2
c        c2

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

[('Header0', 'Header1', 'Header2', 'Header3', 'Header4', 'Header5', 'Header6', 'Header7', 'Header8', 'Header9'), 
 ('text_0_0', 'text_1_0', 'text_2_0', 'text_3_0', 'text_4_0', 'text_5_0', 'text_6_0', 'text_7_0', 'text_8_0', 'text_9_0'), 
 ('text_0_1', 'text_1_1', 'text_2_1', 'text_3_1', 'text_4_1', 'text_5_1', 'text_6_1', 'text_7_1', 'text_8_1', 'text_9_1'), 
 ('text_0_2', 'text_1_2', 'text_2_2', 'text_3_2', 'text_4_2', 'text_5_2', 'text_6_2', 'text_7_2', 'text_8_2', 'text_9_2'), 
 ('text_0_3', 'text_1_3', 'text_2_3', 'text_3_3', 'text_4_3', 'text_5_3', 'text_6_3', 'text_7_3', 'text_8_3', 'text_9_3'), 
 ('text_0_4', 'text_1_4', 'text_2_4', 'text_3_4', 'text_4_4', 'text_5_4', 'text_6_4', 'text_7_4', 'text_8_4', 'text_9_4')]

---

我确信有更多的python方法，但这会起作用（只要所有文件的行数相同）

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

---

我确信有更多的python方法，但这会起作用（只要所有文件的行数相同）

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

---

如果您正在寻找纯python解决方案，最好是

csv.DictReader

和

csv.DictWriter

，这样您就可以更好地控制数据的格式化方式。此外，所有内容都是动态“生成”的，因此对于非常大的文件，它的内存效率会更高

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

import csv

with open('csv1.csv') as csv1, open('csv2.csv') as csv2:
    r1 = csv.DictReader(csv1)
    r2 = csv.DictReader(csv2)
    with open('csv3.csv', 'w') as csv3:
        writer = csv.DictWriter(csv3, 
            fieldnames=["First", "Second"],
            lineterminator='\n'
        )
        writer.writeheader()
        writer.writerows({**x, **y} for x, y in zip(r1, r2))

---

如果您正在寻找纯python解决方案，最好是

csv.DictReader

和

csv.DictWriter

，这样您就可以更好地控制数据的格式化方式。此外，所有内容都是动态“生成”的，因此对于非常大的文件，它的内存效率会更高

data = []
for f in filenames:       # filled when creating files, you can use os.walk to fill yours
    with open(f) as r:
        data.append([x.strip() for x in r])

# data is a list of columns, we need a list of list of columns, so we transpose the data:
transpose = zip(*data)

# write the joined file
import csv
with open("joined.txt","w", newline="") as j:
    w = csv.writer(j)
    w.writerows(transpose)

import csv

with open('csv1.csv') as csv1, open('csv2.csv') as csv2:
    r1 = csv.DictReader(csv1)
    r2 = csv.DictReader(csv2)
    with open('csv3.csv', 'w') as csv3:
        writer = csv.DictWriter(csv3, 
            fieldnames=["First", "Second"],
            lineterminator='\n'
        )
        writer.writeheader()
        writer.writerows({**x, **y} for x, y in zip(r1, r2))

---

您以前使用过熊猫吗？您尝试过任何东西吗？如果您没有大小问题（例如每个文件有一百万行或每列有非常大的值）。。。只需加载所有文件并将其写入新文件。查看模块

csv

，以便于编写。或者使用pandas。@mad_u当可以使用

csv

模块和列表单独完成时，没有理由为此默认返回pandasfast@roganjosh你是怪物吗？为什么你不爱熊猫。他们很可爱！您以前使用过熊猫吗？您尝试过任何东西吗？如果您没有大小问题（例如每个文件有一百万行或每列有非常大的值）。。。只需加载所有文件并将其写入新文件。查看模块

csv

，以便于编写。或者使用pandas。@mad_u当可以使用

csv

模块和列表单独完成时，没有理由为此默认返回pandasfast@roganjosh你是怪物吗？为什么你不爱熊猫。他们很可爱！我用csv做这个，转置（transpose=zip（*data））似乎不起作用。@yalpsideman它在我发布的代码中起作用。zip（）生成一个只能使用一次的生成器—如果您先打印它，然后在您要写入文件时将其清空。使用

transpose=list（zip（*data））

从转置的值创建一个列表，这样您就可以多次使用它们进行打印和文件写入。我正在使用csv进行此操作，而转置（transpose=zip（*data））似乎不起作用。@yalpsideman它在我发布的代码中起作用。zip（）生成一个只能使用一次的生成器—如果您先打印它，然后在您要写入文件时将其清空。使用

transpose=list（zip（*data））

从转置的值创建一个列表，以便可以多次使用它们进行打印和文件写入