How to Append Two pandas DataFrames

There are multiple ways to append two pandas DataFrames, In this article, I will explain how to append two or more pandas DataFrames by using several functions with examples.

In order to append two DataFrames you can use DataFrame.append() method. When you are appending two or more DataFrames, pass all DataFrames as a list to this method.

Alternatively, you can also use pandas.DataFrame.concat() to concatenate DataFrames which can also be used to append two DataFrames.

1. Quick Examples of Append Two DataFrames

If you are in a hurry, below are some quick examples of how to append two DataFrames in pandas.

# Below are some quick examples

# Append two DataFrames of same column
df3 = df1.append(df2)

# Append two DataFrames of different columns
df2 = df.append(df1)

# Using append() with ignore_index
df2 = df.append(df1, ignore_index=True)

# Appending three DataFrames
df3 = df.append([df1, df2], ignore_index=True)

2. Append Two DataFrames With the Same Columns

Let’s create a pandas DataFrame from Dict to explore this with an example.

# Create two DataFrames with same columns
import pandas as pd

df1 = pd.DataFrame({'Courses': ["Spark","PySpark","Python","pandas"],
                    'Fee' : [20000,25000,22000,24000]})
print("First DataFrame:\n", df1)

df2 = pd.DataFrame({'Courses': ["Pandas","Hadoop","Hyperion","Java"],
                    'Fee': [25000,25200,24500,24900],
                    'Duration': ['30days','35days','40days','45days']})
print("Second DataFrame:\n", df2)

Yields below output.

To append two DataFrames with the same columns in Padas, you can use the concat() function. It appends the column with NaN on the result for rows where the same column does not exist.

# Append two DataFrames of same columns
# using append() function
df3 = df1.append(df2)
print("After appending DataFrames:\n", df3)

Using this method you can also append list as a row to the DataFrame.

3. Append Two DataFrames With the Different Columns

To append two DataFrames with different columns in Pandas, you can use the concat() function. This function allows you to combine DataFrames along a specified axis (rows or columns), and it handles the alignment of columns with different names.

# Craete DataFrames of different columns
import pandas as pd
df1 = pd.DataFrame({'Courses': ["Spark","PySpark","Python","pandas"],
                    'Fee' : [20000,25000,22000,24000]})
print("First DataFrame:\n", df1)

df2 = pd.DataFrame({'discount': [2500,2520,2450,2490],
                    'Duration': ['30days','35days','40days','45days']})
print("Second DataFrame:\n", df2)

# Append two DataFrames of different columns
# using append() function
df3 = df1.append(df2)
print("After appending DataFrames:\n", df3)

Yields below output.

# Output:
First DataFrame:
    Courses    Fee
0    Spark  20000
1  PySpark  25000
2   Python  22000
3   pandas  24000
Second DataFrame:
    discount Duration
0      2500   30days
1      2520   35days
2      2450   40days
3      2490   45days

After appending DataFrames:
    Courses      Fee  discount Duration
0    Spark  20000.0       NaN      NaN
1  PySpark  25000.0       NaN      NaN
2   Python  22000.0       NaN      NaN
3   pandas  24000.0       NaN      NaN
0      NaN      NaN    2500.0   30days
1      NaN      NaN    2520.0   35days
2      NaN      NaN    2450.0   40days
3      NaN      NaN    2490.0   45days

4. Pandas Append Two DataFrames Ignore Index

Append by default merges all rows including indices. if you want to ignore the index on DataFrames, you can set the new index on the pandas DataFrame by using ignore_index=True param.

# Using append() with ignore_index
df3 = df1.append(df2, ignore_index=True)
print(df2)

Yields below output.

# Output:
    Courses    Fee Duration
0     Spark  20000      NaN
1   PySpark  25000      NaN
2    Python  22000      NaN
3    pandas  24000      NaN
4    Pandas  25000   30days
5    Hadoop  25200   35days
6  Hyperion  24500   40days
7      Java  24900   45days

5. Append Three DataFrames

Similarly, If you have three DataFrames pass all these as a list to the append() method. Use ingore_index=True param to reset the index on pandas DataFrame to start from zero.

# Create third DataFrame  
df2 = pd.DataFrame({'Courses':['PHP','GO'],
                    'Duration':['30day','40days'],
                    'Fee':[10000,23000]})
  
# Appending multiple DataFrame
df3 = df.append([df1, df2], ignore_index=True)
print(df3)

Yields below output

# Output:
    Courses    Fee Duration
    Courses    Fee Duration
0     Spark  20000      NaN
1   PySpark  25000      NaN
2    Python  22000      NaN
3    pandas  24000      NaN
4    Pandas  25000   30days
5    Hadoop  25200   35days
6  Hyperion  24500   40days
7      Java  24900   45days
8       PHP  10000    30day
9        GO  23000   40days

6. Complete Example of Append Two DataFrames

import pandas as pd
# Complete Example of Append Two DataFrames
df = pd.DataFrame({'Courses': ["Spark","PySpark","Python","pandas"],
                    'Fee' : [20000,25000,22000,24000]})

df1 = pd.DataFrame({'Courses': ["Pandas","Hadoop","Hyperion","Java"],
                    'Fee': [25000,25200,24500,24900],
                    'Duration': ['30days','35days','40days','45days']})

# Using append() method
df3 = df1.append(df2)
print(df3)

# Using append() with ignore_index
df3 = df1.append(df2, ignore_index=True)
print(df2)

# Create third DataFrame  
df2 = pd.DataFrame({'Courses':['PHP','GO'],
                    'Duration':['30day','40days'],
                    'Fee':[10000,23000]})
  
# Appending multiple DataFrame
df3 = df.append([df1, df2], ignore_index=True)
print(df3)

Conclusion

In this article, you have learned how to append two DataFrames by examples. Also learned how to append even three DataFrame by passing all DF’s you wanted to append as a list.

Related Articles

• Pandas Concat Two DataFrames Explained
• Pandas Combine Two DataFrames With Examples
• Pandas – Append a List as a Row to DataFrame
• How to Combine Two Series into pandas DataFrame
• How to Append Row to pandas DataFrame
• Pandas Append Rows & Columns to Empty DataFrame
• Pandas append() Usage by Examples
• How to Append Pandas Series?
• Append Pandas DataFrames Using for Loop
• How to Merge Series into Pandas DataFrame
• Pandas Merge DataFrames on Index
• Pandas Merge Two DataFrames
• Pandas Merge DataFrames Explained Examples
• Pandas join two DataFrames
• Split the column of DataFrame into two columns
• Split Pandas DataFrame by column value
• Split pandas DataFrame

References

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