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您如何将数据从数据框架复制到另一个

发布于 2025-01-29 23:00:41 字数 4816 浏览 3 评论 0原文

我很难将正确的数据从参考CSV文件获取正确的数据到我正在处理的文件。

我有一个CSV文件，其中有超过600万行和19列。我看起来像这样：在此处输入图像描述

对于每一行，都有一个品牌和一个汽车模型，包括其他信息。我想将每100公里旅行的燃油和所使用的燃料类型添加到此文件中。

我还有另一个CSV文件，它具有每种看起来像这样的汽车模型的燃料消耗：输入图像描述这里

我最终要做的是将g，h，i和j列的匹配值从第二个文件添加到第一个文件。

由于文件的大小，我想知道除了“ for”或“ a”循环之外，还有其他方法可以做其他方法吗？

编辑：

例如... 第一个DF看起来像这个

ID	品牌	模型	其他_COLUMNS	fuel_consu_1	fuel_consu_2
1	Toyota	Rav4	A	C	Nan
Nan	Nan	Nan	Nan	Nan	Nan
Nan	Nan Nan Nan Nan Nan Nan Nan Nan Nan Nan Nan Nan Nan Nan 3 Gmc	Nan	Nan	Nan	Nan Nan Nan Nan Nan Nan
Nan	Sierra	Nan	d	Nan Nan	nan d nan

d nan nan spect this

Id id	far fall ful_consu_consu_consu_consu_consu_consu_consu_consu_consu_consu_conu_consu_cod_consu_conu_consu_conu_consu_11	nan	d	Fuel_consu_2
1	Toyota	Corrola	100	120
2	Toyota	Rav4	80	84
3	GMC	Sierra	91	105
4	Honda	Civic	112	125

The output should be :

ID	Brand	Model	Other_columns	Fuel_consu_1	Fuel_consu_2
1	Toyota	Rav4	a	80	84
2	Honda	Civic	b	112	125
3	GMC	Sierra	c	91	105
4	Toyota	Rav4	D	80	84

第一个DF可能具有与不同ID相同的品牌和型号。订单是完全随机的。

原文

I am having a difficult time getting the correct data from a reference csv file to the one I am working on.

I have a csv file that has over 6 million rows and 19 columns. I looks something like this :
enter image description here

For each row there is a brand and a model of a car amongst other information.
I want to add to this file the fuel consumption per 100km traveled and the type of fuel that is used.

I have another csv file that has the fuel consumption of every model of car that looks something like this : enter image description here

What I want to ultimately do is add the matching values of G,H, I and J columns from the second file to the first one.

Because of the size of the file I was wondering if there is another way to do it other than with a "for" or a "while" loop?

EDIT :

For example...
The first df would look something like this

ID	Brand	Model	Other_columns	Fuel_consu_1	Fuel_consu_2
1	Toyota	Rav4	a	NaN	NaN
2	Honda	Civic	b	NaN	NaN
3	GMC	Sierra	c	NaN	NaN
4	Toyota	Rav4	d	NaN	NaN

The second df would be something like this

ID	Brand	Model	Fuel_consu_1	Fuel_consu_2
1	Toyota	Corrola	100	120
2	Toyota	Rav4	80	84
3	GMC	Sierra	91	105
4	Honda	Civic	112	125

The output should be :

ID	Brand	Model	Other_columns	Fuel_consu_1	Fuel_consu_2
1	Toyota	Rav4	a	80	84
2	Honda	Civic	b	112	125
3	GMC	Sierra	c	91	105
4	Toyota	Rav4	d	80	84

The first df may have many times the same brand and model for different ID's. The order is completely random.

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日暮斜阳 2025-02-05 23:00:42

感谢您提供更新，我能够将一些应该能够帮助您的东西放在一起

#You drop these two columns because you won't need them once you join them to df1 (which is your 2nd table provided)
df.drop(['Fuel_consu_1', 'Fuel_consu_2'], axis = 1 , inplace = True)
#This will join your first and second column to each other on the Brand and Model columns 
df_merge = pd.merge(df, df1, on=['Brand', 'Model'])

Thank you for providing updates I was able to put something together that should be able to help you

#You drop these two columns because you won't need them once you join them to df1 (which is your 2nd table provided)
df.drop(['Fuel_consu_1', 'Fuel_consu_2'], axis = 1 , inplace = True)
#This will join your first and second column to each other on the Brand and Model columns 
df_merge = pd.merge(df, df1, on=['Brand', 'Model'])

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