从CSV文件PYTHON中读取列块

Question

With the file structure:

A   B    C    D
1   x    y    z
2   x    y    z
3   x    y    z
4   x    y    z
5   i    j    k
6   i    j    k
7   .......etc.

I want to skip the headings, then the first elements of each row.

The real juicy data is the x,y,z,i,j,k values.

These values are ADC values and need to be arranged into a list of lists.

my_list = [0] [x,x,x,x]
          [1] [y,y,y,y]
          [2] [z,z,z,z]
          [3] [i,i,i,i] etc.

I can easily iterate out a full column, but the tricky part is iterating out certain rows of each column.

I tried so far:

def readin(myfile):

import csv
with open(myfile, 'r') as f:  # Open Results File

    next(f) # skip headings

    data = csv.reader(f, delimiter="\t")
    temp = []
    temp2=[]
    my_list=[]

    for i in range(13): #my_list will be 12 lists long
       print i
       for x in range(1,4):
        for row in data:
         temp.append(row[x])
    return my_list

I just get one column iterated out. And I have no idea how to easily slice the columns (for separate x's, i's etc.

Answer 1

transpose the data and slice:

 from itertools import izip
 data = csv.reader(f, delimiter="\t")
 trans = izip(*data)
 A = next(trans) # skip first col

Answer 2

This is the code, as you can see i use pandas to manipulate my data.

import pandas as pd

df = pd.read_csv("te.txt")
df.drop(df.columns[[0]], axis=1, inplace=True) # delete the first column as you wished
li = []
for col in df.columns:
    li.append(list(df[col]))
print li

Output:

[['x', 'x', 'x', 'x', 'i', 'i'],
 ['y', 'y', 'y', 'y', 'j', 'j'],
 ['z', 'z', 'z', 'z', 'k', 'k']]

This is the csv file "te.txt":

A,B,C,D
1,x,y,z
2,x,y,z
3,x,y,z
4,x,y,z
5,i,j,k
6,i,j,k

Answer 3

An approach without external modules but csv :

import csv

with open('blocks.csv') as infile:
    reader = csv.reader(infile)
    out_list = []

    # skip first line
    next(reader)

    while True:
        block = []
        try:
            # read four lines
            for i in range(4):
                block.append(next(reader))
        except StopIteration:
            break

        # transpose the block and skip the index column
        transposed_block = zip(*block)[1:]
        out_list += transposed_block

This produces the following out_list :

>>> out_list
[('x', 'x', 'x', 'x'),
 ('y', 'y', 'y', 'y'),
 ('z', 'z', 'z', 'z'),
 ('i', 'i', 'i', 'i'),
 ('j', 'j', 'j', 'j'),
 ('k', 'k', 'k', 'k')]

Answer 4

Use pandas as belows:

from pandas import DataFrame as df

d = df.read_csv("text.txt")

d.drop(d.columns[[0]], axis=1, inplace=True)
k_list = [d.loc[:3,k].tolist() for k in d.columns()]

print k_list

Output:

[['x', 'x', 'x', 'x'], 
 ['y', 'y', 'y', 'y'],
 ['z', 'z', 'z', 'z']]

Answer 5

The following will give you the results you have asked for. It uses a slightly alternative method for reading four rows at a time, and also removes the first column:

import csv

def readin(myfile):
    my_list = []

    with open(myfile, 'r') as f:        # Open Results File
        csv_input = csv.reader(f, delimiter=" ", skipinitialspace=True)
        headings = next(csv_input)      # Skip headings

        try:
            while True:
                my_list.extend(zip(next(csv_input), next(csv_input), next(csv_input), next(csv_input))[1:])
        except StopIteration:
            pass

    return my_list

result = readin("results_file.csv")

print result[0]
print result

The output is:

('x', 'x', 'x', 'x')

[('x', 'x', 'x', 'x'), ('y', 'y', 'y', 'y'), ('z', 'z', 'z', 'z'), ('i', 'i', 'i', 'i'), ('j', 'j', 'j', 'j'), ('k', 'k', 'k', 'k')]