Create an empty data frame with index from another data frame

Question

I've got a data frame df1 with multiple columns and rows. Simple example:

    TIME T1  T2 
       1 10 100
       2 20 200
       3 30 300

I'd like to create an empty data frame df2 and later on, add new columns with the calculation results.

For this moment my code looks like this:

     df1=pd.read_csv("1.txt",index_col="TIME")

     df2=df1.copy()[[]] #copy df1 and erase all columns

...adding two new columns:

     df2["results1"],df2["results2"]=df1["T1"]*df["T2"]*3,df1["T2"]+100

Is there any better/safer/faster way to do this ? Is it possible to create an empty data frame df2 and only copy index from df1 ?

Answer 1

df2 = pd.DataFrame(index=df1.index)

This will create a DataFrame with no columns but just an index, and it will be the same index as in the df1.

Answer 2

It's better to set index as df1.index.copy()

df2 = pd.DataFrame(index=df1.index.copy())

You can use df1.index is df2.index to check whether they are the same object

Answer 3

You can also assign the index of a dataframe to another dataframe directly.

df2.index=df1.index

Answer 4

You can use this short code:

df2=df1[[]].copy()

Answer 5

To avoid geting all the NaN after the concat add the index to it.

df1 = pd.DataFrame(x1.toarray(),index=simpledf.index, columns=v.get_feature_names())

When defining the new dataframe with X transformed use the same index as the original dataframe.