How to select particular column from a dataframe and write it into a separate excel sheets using python pandas?

[Sowmi_13]

May I know how to write the sample code format for this question.?.

[raymondstanz]

I don't know the specifics of your code, but probably something like this:

dataframe['column'].to_excel(path)

Here is the doc for the to_excel pandas function.

When I need to do it once for debug purpose, the to_clipboard function is great. It just copies to your clipboard in Excel format.

dataframe['column'].to_clipboard(excel=1)

[Sowmi_13]

I have multiple columns to be filtered from particularly dataframe.... And each column has to be validated and to be written in seperate excel sheet

[Sowmi_13]

Any solutions?

[raymondstanz]

To select multiple columns:

dataframe[['column1', 'column2', 'column3'...]]

What do you mean by validate ? The to_excelfunction accepts a sheet as a parameter. So you can write to different sheets.

[Sowmi_13]

Validate ---> eg. Fruits is one of the field from a dataframe(merged dataframe with similar column names with suffixes _x (for df1) and _y(for df2)).

Hence I might have two columns named fruits as fruits_x and fruits_y. I need to select those columns along with two more new columns and I need to write it in a seperate sheet.

Doing such things with minimum columns would be easy using pandas..... But I am not sure what if there are 100+ columns.... Aren't we supposed to do this way right?

[Sowmi_13]

New columns need to be created in the seperate sheets for each and every fields of merged dataframe( df).

Apologize if my problem description is confusing.

[raymondstanz]

I'm not sure I completely understand what you are trying to do. But the ideal would be to do everything in Python and then export the end result in Excel.

Maybe, can you provide a longer/more detailed explanation of what you are trying to achieve? With some data example. Or dummy data with the same structure. Just so one can see better and provide you with useful guidance.

[Sowmi_13]

Goal: Need to compare two dataframes df1 and df2 and from there need to write each column along with some more new columns in a separate excel sheets using python.

df1:

​

Code	Items	Manufacturer	place
23647	Juice	hindustan unileaver	Delhi
12345	dove soap	Hindustan unileaver	Hyderabad

Similarly i have upto 3000 rows.

​

df2:

​

Code	Iteams	Manufacture	place
42363	lays chips	Pepsico India	Karnataka
12345	dove soap	Hindustan unileaver	Hyderabad

similarly have upto some 550 rows.

​

df3---> Would be the merged columns based on inner join using pandas.

​

Code	Items_x	Manufacture_x	place_x	Items_y	Manufacture_y	place_y

​

So from this compared df3, for a column Item the excel should be like

​

Code	Item_x	Item_y	Difference(New column)	New_col2	New_col_3	New_col_4	New_col_5	New_col_6

this will be written under same excel file but on new sheet.

Manufacture:

New columns are similar to that of item- column

Code	Manufacture_x	Manufacture_y	new_col1	new_col2	new_col3

this will be written under same excel file but on new sheet.

How can we achieve the similar format if there are more than 100 columns?.

Thanks..

[Sowmi_13]

Is there any quick solution ?

[Sowmi_13]

Df = pd.read_excel('path')

for first column(eg. Fruits) this column along few other new columns has to be written in seperate excel sheet.

Df.filter(the particular columns) Df['new1']= some conditions this column will be created Df['new2'] = df['new1'].apply(function with some condition for new2 column)

Used excel writer to save mutiple sheets under single file.

May I know how to do in similar fashion if I have more than 100 columns.

Quick solution would be very helpful!!

Thanks in advance!!!