Getting error when adding a new row to my existing dataframe in pandas

Question

I have the below data frame.

df3=pd.DataFrame(columns=["Devices","months"])

I am getting row value from a loop row, print(data)

    Devices     months
1  Powerbank  Feb month

When I am adding this data row to my df3 I am getting an error.

  df3.loc[len(df3)]=data

ValueError: cannot set a row with mismatched columns

Possible duplicate of [Add one row to pandas DataFrame](https://stackoverflow.com/questions/10715965/add-one-row-to-pandas-dataframe) — Santhosh Dhaipule Chandrakanth, Sep 05 '19 at 06:30

muon · Accepted Answer · 2017-07-14T14:13:33.510

20

use

df3 = pd.concat([df3, data], axis=0)

or as suggested by @Wen use

df3 = df3.append(data)

edited Jul 14 '17 at 14:13

answered Jul 14 '17 at 14:11

muon

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`axis=0` is a default value and can be omitted – VMAtm Jun 25 '18 at 05:09
If you do not use the `ignore_index` then maybe will appear a error. `df3 = df3.append(data, ignore_index=True )` – asantz96 Aug 06 '20 at 06:24

JoaoMVR · Answer 2 · 2018-03-26T10:25:14.837

From https://pandas.pydata.org/pandas-docs/stable/merging.html:

It is worth noting however, that concat (and therefore append) makes a full copy of the data, and that constantly reusing this function can create a significant performance hit. If you need to use the operation over several datasets, use a list comprehension.

You should use loc, like you were trying to do, and with a dictionary where the keys are the column names and the values are the data of the row being added.

import pandas as pd

df3 = pd.DataFrame(columns=["Devices","months"])
new_entry = {'Devices': 'device1', 'months': 'month1'}

df3.loc[len(df3)] = new_entry

how to append a dataframe to an existing dataframe using the above technique? — Nathan, Aug 04 '19 at 12:57

score 1 · Answer 3 · answered Jul 20 '18 at 08:23

If someone is looking to append new row which is in dictionary format, below will help.

Existing DataFrame

In [6]: df
Out[6]: 
     Devices     months
0  Powerbank  Feb month

In [7]:

Below snippet adds another row to existing DataFrame.

In [7]: dictionary_row = {"Devices":"Laptop","months":"Mar month"}

In [8]: df = df.append(dictionary_row, ignore_index=True)

In [9]: df
Out[9]: 
     Devices     months
0  Powerbank  Feb month
1     Laptop  Mar month

In [10]:

Hope that helps.

score 0 · Answer 4 · answered Sep 04 '19 at 08:44

As the error suggests the number of columns should of the data being inserted into the dataframe must match the number of columns of the dataframe

>>> df3=pd.DataFrame(columns=["Devices","months"])
>>> df3.loc[len(df3)] = ['Powerbank','Feb']
>>> df3
     Devices months
0  Powerbank    Feb
>>> data = ['powerbank','feb']
>>> df3.loc[len(df3)] = data
>>> df3
     Devices months
0  Powerbank    Feb
1  powerbank    feb

Getting error when adding a new row to my existing dataframe in pandas

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