Python 将 CSV 加载到 Pandas MultiIndex DataFrame
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Load CSV to Pandas MultiIndex DataFrame
提问by Handloomweaver
I have a 719mb CSV file that looks like:
我有一个 719mb 的 CSV 文件，如下所示：
from, to, dep, freq, arr, code, mode (header row)
RGBOXFD,RGBPADTON,127,0,27,99999,2
RGBOXFD,RGBPADTON,127,0,33,99999,2
RGBOXFD,RGBRDLEY,127,0,1425,99999,2
RGBOXFD,RGBCHOLSEY,127,0,52,99999,2
RGBOXFD,RGBMDNHEAD,127,0,91,99999,2
RGBDIDCOTP,RGBPADTON,127,0,46,99999,2
RGBDIDCOTP,RGBPADTON,127,0,3,99999,2
RGBDIDCOTP,RGBCHOLSEY,127,0,61,99999,2
RGBDIDCOTP,RGBRDLEY,127,0,1430,99999,2
RGBDIDCOTP,RGBPADTON,127,0,115,99999,2
and so on...
I want to load in to a pandas DataFrame. Now I know there is a load from csv method:
我想加载到 Pandas DataFrame。现在我知道有来自 csv 方法的负载：
r = pd.DataFrame.from_csv('test_data2.csv')
But I specifically want to load it as a 'MultiIndex' DataFrame where from and to are the indexes:
但我特别想将它加载为“多索引”数据帧，其中 from 和 to 是索引：
So ending up with:
所以最终得到：
dep, freq, arr, code, mode
RGBOXFD RGBPADTON 127 0 27 99999 2
RGBRDLEY 127 0 33 99999 2
RGBCHOLSEY 127 0 1425 99999 2
RGBMDNHEAD 127 0 1525 99999 2
etc. I'm not sure how to do that?
等等。我不知道该怎么做？
采纳答案by DSM
You could use pd.read_csv:
你可以使用pd.read_csv：
>>> df = pd.read_csv("test_data2.csv", index_col=[0,1], skipinitialspace=True)
>>> df
dep freq arr code mode
from to
RGBOXFD RGBPADTON 127 0 27 99999 2
RGBPADTON 127 0 33 99999 2
RGBRDLEY 127 0 1425 99999 2
RGBCHOLSEY 127 0 52 99999 2
RGBMDNHEAD 127 0 91 99999 2
RGBDIDCOTP RGBPADTON 127 0 46 99999 2
RGBPADTON 127 0 3 99999 2
RGBCHOLSEY 127 0 61 99999 2
RGBRDLEY 127 0 1430 99999 2
RGBPADTON 127 0 115 99999 2
where I've used skipinitialspace=Trueto get rid of those annoying spaces in the header row.
我过去常常skipinitialspace=True在标题行中去掉那些烦人的空格。
回答by 7stud
from_csv() works similarly:
from_csv() 的工作原理类似：
import pandas as pd
df = pd.DataFrame.from_csv(
'data.txt',
index_col = [0, 1]
)
print df
--output:--
dep freq arr code mode
from to
RGBOXFD RGBPADTON 127 0 27 99999 2
RGBPADTON 127 0 33 99999 2
RGBRDLEY 127 0 1425 99999 2
RGBCHOLSEY 127 0 52 99999 2
RGBMDNHEAD 127 0 91 99999 2
RGBDIDCOTP RGBPADTON 127 0 46 99999 2
RGBPADTON 127 0 3 99999 2
RGBCHOLSEY 127 0 61 99999 2
RGBRDLEY 127 0 1430 99999 2
RGBPADTON 127 0 115 99999 2
From this discussion,
从这次讨论中，
https://github.com/pydata/pandas/issues/4916
https://github.com/pydata/pandas/issues/4916
it looks like read_csv() was implemented to allow you to set more options, which makes from_csv() superfluous.
看起来 read_csv() 的实现是为了让您设置更多选项，这使得 from_csv() 变得多余。
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