There are several ways to append a list to a Pandas Dataframe in Python.

Option 1: append the list at the end of the dataframe with pandas.DataFrame.loc:

df.loc[len(df)] = row

Option 2: convert the list to dataframe and concatenate it with pd.concat to append a row:

row_df = pd.DataFrame([row], columns=df.columns)
df = pd.concat([df, row_df], ignore_index=True)

To append a list as a row to a Pandas DataFrame in Python, you can use the loc method, the append method (though deprecated in newer versions of Pandas), or convert the list to a DataFrame and concatenate it with the existing DataFrame. Below are the different methods:

1. Using loc to Append a Row

If your DataFrame already exists and you want to append a row to it, you can use the loc method.

import pandas as pd

# Create a DataFrame
df = pd.DataFrame(columns=["A", "B", "C"])

# List to append
row = [1, 2, 3]

# Append the list as a new row
df.loc[len(df)] = row

print(df)

2. Using pd.concat to Append a Row

You can convert the list to a DataFrame and then concatenate it to the existing DataFrame.

import pandas as pd

# Create a DataFrame
df = pd.DataFrame(columns=["A", "B", "C"])

# List to append
row = [1, 2, 3]

# Convert list to DataFrame
row_df = pd.DataFrame([row], columns=df.columns)

# Append the new row
df = pd.concat([df, row_df], ignore_index=True)

print(df)

3. Using the append method (deprecated since version 1.4.0)

The append method was commonly used to add a row to a DataFrame, but it is deprecated since version 1.4.0.

import pandas as pd

# Create a DataFrame
df = pd.DataFrame(columns=["A", "B", "C"])

# List to append
row = [1, 2, 3]

# Append the list as a new row
df = df.append(pd.Series(row, index=df.columns), ignore_index=True)

print(df)

Examples

Let's consider the following dataframe and list:

import pandas as pd
# Dataframe
df = pd.DataFrame([[1, 2], [3, 4]], columns = ["col1", "col2"])
# List to append
list = [5, 6]

Using loc:

>>> df.loc[len(df)] = list
>>> df
   col1  col2
0     1     2
1     3     4
2     5     6

Using pd.concat:

>>> row_df = pd.DataFrame([list], columns=df.columns)
>>> df = pd.concat([df, row_df], ignore_index=True)
>>> df
   col1  col2
0     1     2
1     3     4
2     5     6

Using pd.append:

>>> df = df.append(pd.Series(list, index=df.columns), ignore_index=True)
<stdin>:1: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
>>> df
   col1  col2
0     1     2
1     3     4
2     5     6

Summary

• loc method: Suitable for directly adding rows based on the index.
• pd.concat method: More flexible and suitable for larger DataFrames or when working with DataFrames.
• append method: Deprecated, so prefer loc or pd.concat in newer code.

The loc and pd.concat methods are the recommended ways to append rows to a DataFrame in Pandas 2.0 and later.