如何转置 csv 文件中的数据集？

发布于 2024-10-15 12:51:56 字数 300 浏览 2 评论 0原文

例如，我想将：转换

Name,Time,Score
Dan,68,20
Suse,42,40
Tracy,50,38

为：

Name,Dan,Suse,Tracy
Time,68,42,50
Score,20,40,38

编辑： 原始问题错误地使用了术语“转置”。

原文

For example, i would like to transform:

Name,Time,Score
Dan,68,20
Suse,42,40
Tracy,50,38

Into:

Name,Dan,Suse,Tracy
Time,68,42,50
Score,20,40,38

Edit: The original question used the term "transpose" incorrectly.

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他不在意 2024-10-22 12:51:56

如果整个文件内容适合内存，您可以使用

import csv
from itertools import izip
a = izip(*csv.reader(open("input.csv", "rb")))
csv.writer(open("output.csv", "wb")).writerows(a)

您基本上可以将 zip() 和 izip() 视为转置操作：

a = [(1, 2, 3),
     (4, 5, 6),
     (7, 8, 9)]
zip(*a)
# [(1, 4, 7),
#  (2, 5, 8),
#  (3, 6, 9)]

izip() 避免立即复制数据，但基本上会做同样的事情。

If the whole file contents fits into memory, you can use

import csv
from itertools import izip
a = izip(*csv.reader(open("input.csv", "rb")))
csv.writer(open("output.csv", "wb")).writerows(a)

You can basically think of zip() and izip() as transpose operations:

a = [(1, 2, 3),
     (4, 5, 6),
     (7, 8, 9)]
zip(*a)
# [(1, 4, 7),
#  (2, 5, 8),
#  (3, 6, 9)]

izip() avoids the immediate copying of the data, but will basically do the same.

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小巷里的女流氓 2024-10-22 12:51:56

从 input.csv 传输到 output.csv。熊猫也能提供帮助。

import pandas as pd
pd.read_csv('input.csv', header=None).T.to_csv('output.csv', header=False, index=False)

Transfer from input.csv to output.csv. Pandas can also help.

import pandas as pd
pd.read_csv('input.csv', header=None).T.to_csv('output.csv', header=False, index=False)

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中性美 2024-10-22 12:51:56

nosklo 的答案相同（全部归功于他），但对于 python3：

from csv import reader, writer 
with open('source.csv') as f, open('destination.csv', 'w') as fw: 
    writer(fw, delimiter=',').writerows(zip(*reader(f, delimiter=',')))

Same answer of nosklo (all credits to him), but for python3:

from csv import reader, writer 
with open('source.csv') as f, open('destination.csv', 'w') as fw: 
    writer(fw, delimiter=',').writerows(zip(*reader(f, delimiter=',')))

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林空鹿饮溪 2024-10-22 12:51:56

from itertools import izip
from csv import reader, writer

with open('source.csv') as f, open('destination.csv', 'w') as fw:
    writer(fw, delimiter=',').writerows(izip(*reader(f, delimiter=',')))

from itertools import izip
from csv import reader, writer

with open('source.csv') as f, open('destination.csv', 'w') as fw:
    writer(fw, delimiter=',').writerows(izip(*reader(f, delimiter=',')))

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陪你到最终 2024-10-22 12:51:56

如果 lines 是原始文本列表，而不是应有的形式

for i in range(1,len(lines)):
    lines[i] = lines[i].split(',')

new_lines = []
for i in range(len(lines[0])):
    new_lines.append("%s,%s,%s" % (lines[0][i], lines[1][i], lines[2][i]))

，或者使用 csv Python 模块 - http://docs.python.org/library/csv.html

If lines is the list of your original text than it should be

for i in range(1,len(lines)):
    lines[i] = lines[i].split(',')

new_lines = []
for i in range(len(lines[0])):
    new_lines.append("%s,%s,%s" % (lines[0][i], lines[1][i], lines[2][i]))

or use csv Python module - http://docs.python.org/library/csv.html

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咋地 2024-10-22 12:51:56

最简单的方法是：

import numpy as np
import pandas as pd

_mat = pd.read_csv("test.csv")
_mat = _mat[_mat.columns[0:3]].values
_t_mat = np.transpose(_mat)

结果：

输入矩阵为：[[1 2 3] [4 5 6]]
输出为：[[1 4] [2 5] [3 6]]

The simplest way is:

import numpy as np
import pandas as pd

_mat = pd.read_csv("test.csv")
_mat = _mat[_mat.columns[0:3]].values
_t_mat = np.transpose(_mat)

Result:

Input matrix is : [[1 2 3] [4 5 6]]
the output is: [[1 4] [2 5] [3 6]]

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夏日落 2024-10-22 12:51:56

将 CSV 读入 pandas 数据框，pandas 内置了转置函数，可以按如下方式调用。

import pandas as pd

csv = pd.read_csv("test.csv", skiprows=1)
# use skiprows if you want to skip headers
df_csv = pd.DataFrame(data=csv)
transposed_csv = df_csv.T
print(transposed_csv)

Read the CSV into pandas data frame, pandas has build in function for transpose which can be invoked as below.

import pandas as pd

csv = pd.read_csv("test.csv", skiprows=1)
# use skiprows if you want to skip headers
df_csv = pd.DataFrame(data=csv)
transposed_csv = df_csv.T
print(transposed_csv)

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