Attributeerror: 'dataframe' object has no attribute append ( steps )

Attributeerror: ‘dataframe’ object has no attribute append error occurs because append() attribute is removed in Pandas 2.0.0 version. We can we concat() attribute to achieve similar functionality. In this article we will fix this attributeerror step by step. We will start from replication of the error. We will also explore the other alternative to fix this issue. So lets start.

Attributeerror: ‘dataframe’ object has no attribute append ( Solution) –

As the first step we will replicate this error. To go into the depth.

Step 1: Error Replication & root cause Analysis –

In this step, we will create two dummy dataframe and then perform the append() function.

Now for the latest version of pandas, it will throw the Attributeerror like above.
For the lower version to 2.0.0, It will throw the warning of deplication like below.

Attributeerror 'dataframe' object has no attribute append error replication — ‘dataframe’ object has no attribute append error replication

Step 2: Using concat() Attribute –

The replacement for append() attribute is concat() attribute. Lets try to ingest this function in the above code. I will resolve the error.

import pandas as pd
df1 = pd.DataFrame({'col1': [3,4], 'col2': [5,6]})
df2 = pd.DataFrame({'col1': [8], 'col2': [11]})
final = pd.concat([df1, df2])
final.head()

Lets run this code with concat() function or attribute and see the output.

Attributeerror 'dataframe' object has no attribute append error resolved using concat attribute — Attributeerror ‘dataframe’ object has no attribute append error resolved using concat attribute

Other Solutions :

There are many other ways also to fix this error. Lets explore them one by one. But I will recommend to opt concat() in the place of below solution.

Alternative Solution 1 : Use second dataframe as dict –

In this approach we want to use append() attribute then we need to first convert the second dataframe and then we will append().

import pandas as pd
df1 = pd.DataFrame({'col1': [3,4], 'col2': [5,6]})
df2 = pd.DataFrame({'col1': [8], 'col2':[11] })
## Data Frame to dict conversion 
mydict=df2.to_dict('dict')
df = df.append(mydict, ignore_index=True)
df.head()

Alternative Solution 2 : Use second dataframe as series –

Here we will use the second dataframe as series.

df1 = pd.DataFrame({'col1': [3,4], 'col2': [5,6]})
ser = pd.Series({'col1': 11, 'col2': 19})
final_df= df1.append(ser, ignore_index=True)
final_df.head()