combine multiple columns in single data frames from single dataframe

Question

I have single data frame which consist of multiple columns name such as "Load_Node_Values,Load_KV_Values,Load_Node_Values,Load_KV_Values,Load_P_ST_Values,Load_ST_Values,G_Node_Values,G_KV_Values,G_P_ST_Values,G_ST_Values,Line_Node_Values,Line_KV_Values,Line_P_ST_Values,Line_ST_Values,T_Node_Values,T_KV_Values,T_P_ST_Values,T_ST_Values,Load_P_ST_Values,Load_ST_Values,G_Node_Values G_KV_Values,G_P_ST_Values,G_ST_Values,Line_Node_Values,Line_KV_Values,Line_P_ST_Values,Line_ST_Values,T_Node_Values,T_KV_Values". All these columns have have numeric as well as string values. I want to combine all the values of Load_Node_values, G_Node_values, Line_Node_values and T_Node_Values into one one single column "new name" and similarly, other column as well into another new column name.

I used frames and put all the columns that want to combine. In the code I showed that frame_node, frame_KV, frame_P, frame_ST and put all the columns names in these frames as shown in the code.

frame_KV=[df1['Load_KV_Values'],df2['G_KV_Values'],df3['Line_KV_Values'],df4['T_KV_Values']]
frame_P=[df1['Load_P_ST_Values'],df2['G_P_ST_Values'],df3['Line_P_ST_Values'],df4['T_P_ST_Values']]
frame_ST=[df1['Load_ST_Values'],df2['G_ST_Values'],df3['Line_ST_Values'],df4['T_ST_Values']]

frames=[frame_node,frame_KV,frame_P,frame_ST]

result_nodes=pd.concat(frames)

This is error I got from the text. "TypeError: cannot concatenate object of type ""; only pd.Series, pd.DataFrame, and pd.Panel (deprecated) objs are valid"

Shubh · Accepted Answer · 2019-08-16 09:16:04Z

1

frame_1=df1[['Load_KV_Values','Load_P_ST_Values','Load_ST_Values']]
frame_2= df2[['G_P_ST_Values','G_KV_Values','G_ST_Values']]
frame_3=df3[['Line_KV_Values','Line_ST_Values','Line_P_ST_Values']
frame_4 = df4[['T_KV_Values','T_P_ST_Values','T_ST_Values']
result_nodes = pd.concat([frame_1, frame_2, frame_3, frame_4], axis =1)

Please check by following method anlso please verify wether all four dataframes have same number of rows. --Do upvote

answered Aug 16, 2019 at 9:16

Shubh

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2 Comments

anmol Over a year ago

No, these data frames does not have same number of rows. and it shows the same result as it was previous. I need to combine all the Node values in the same column, similarly,all KV Values and ST Values in the same column

Shubh Over a year ago

If you dont have same number of rows in all dataframes, then you cant combine(concatenate) .

jezrael · Accepted Answer · 2019-08-16 07:34:30Z

0

There is list of list of Series, so flatten it for list of Series:

result_nodes=pd.concat([y for x in frames for y in x])

Or maybe need first concat by axis=1 fr eacj list and then by default axis=0 (should be omit):

result_nodes=pd.concat(pd.concat([x for x in frames], axis=1))

edited Aug 16, 2019 at 7:34

answered Aug 16, 2019 at 7:27

jezrael

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2 Comments

anmol Over a year ago

frame_KV=[df1['Load_KV_Values'],df2['G_KV_Values'],df3['Line_KV_Values'],df4['T_KV_Values']] Is this code right for combine these multiple column as row wise becuause I didn't fetch the right result

jezrael Over a year ago

@anmol - I think yes, only need same index values in all DataFrames, so try df1 = df1.reset_index(drop=True), df2 = df2.reset_index(drop=True), df3 = df3.reset_index(drop=True), df4 = df4.reset_index(drop=True) befoire your solution.

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