How to insert data from one dataframe into an index present in another?

Question

I have a folder with about 480 CSV files, only they don’t have an index and I created another CSV file to be their index (there are 119 columns in the index) When I enter using df.append the file becomes 238 columns, ie fold. I tried everything to insert this index as the first row before reading the files, as I do to insert the lines below the title of their columns?

I tried that:

df1= pd.read_csv('/home/user/TCC/2015/index.csv')
df2= pd.read_csv('/home/user/TCC/2015/data.csv')

df1 = df1.append(df2)

I tried that way too:

result = pd.concat([df1, df2], axis=1).reindex(df_index.index)

If you can help, thank you.

Answer 1

I figured it out, and I come back here to answer like I did. Within the function: pd.read_csv

has an attribute called name, just put the name I want and the columns receive them, example:

df1 = pd.read_csv('path/item.csv', name= {"Column1", "Column2"})

can also create an array with the names and pass it ex: array ={"column1","column2"} df1=pd.read_csv('path/item.csv', name=array)

Answer 2

Merge, reset the index and then do the new index:

new =  df1.join(df2)
new.reset_index(inplace = True)
new.set_index('index', inplace = True)

Just to clarify, df.append appends the databases. That is, it adds lines (vertical sum), keeping the number of variables counting, but increasing the number of observations. On the other hand, when someone needs to join banks by increasing the number of variables with the constant number of observations, the command df.Join and pd.concatenate is used..

Here is an elaborate presentation on this (in English): https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html