Add a row at top in pandas DataFrame

Adding a row at the top of a Pandas DataFrame is a common operation when you need to insert headers, summary rows, or new data at the beginning. There are several methods to achieve this − using pd.concat(), loc[] with index manipulation, or iloc slicing.

Create a Sample DataFrame

import pandas as pd

df = pd.DataFrame({
    'Name': ['Alice', 'Bob', 'Charlie'],
    'Age': [25, 30, 35],
    'City': ['Delhi', 'Mumbai', 'Pune']
})
print("Original DataFrame:")
print(df)

Original DataFrame:
      Name  Age    City
0    Alice   25   Delhi
1      Bob   30  Mumbai
2  Charlie   35    Pune

Method 1: Using pd.concat()

Create the new row as a DataFrame and concatenate it at the top ?

import pandas as pd

df = pd.DataFrame({
    'Name': ['Alice', 'Bob', 'Charlie'],
    'Age': [25, 30, 35],
    'City': ['Delhi', 'Mumbai', 'Pune']
})

# New row as a DataFrame
new_row = pd.DataFrame({'Name': ['Dave'], 'Age': [28], 'City': ['Hyderabad']})

# Concat at top and reset index
df = pd.concat([new_row, df], ignore_index=True)
print(df)

      Name  Age       City
0     Dave   28  Hyderabad
1    Alice   25      Delhi
2      Bob   30     Mumbai
3  Charlie   35       Pune

Method 2: Using loc[] with Index Shift

Assign a new index position and sort to place the row at the top ?

import pandas as pd

df = pd.DataFrame({
    'Name': ['Alice', 'Bob', 'Charlie'],
    'Age': [25, 30, 35],
    'City': ['Delhi', 'Mumbai', 'Pune']
})

# Shift existing index by 1
df.index = df.index + 1

# Insert at index 0
df.loc[0] = ['Dave', 28, 'Hyderabad']

# Sort by index to bring row 0 to top
df = df.sort_index()
print(df)

      Name  Age       City
0     Dave   28  Hyderabad
1    Alice   25      Delhi
2      Bob   30     Mumbai
3  Charlie   35       Pune

Method 3: Using _append() with Dictionary

Prepend by reversing concat order with a dictionary converted to DataFrame ?

import pandas as pd

df = pd.DataFrame({
    'Name': ['Alice', 'Bob', 'Charlie'],
    'Age': [25, 30, 35],
    'City': ['Delhi', 'Mumbai', 'Pune']
})

# Create row from dictionary
new_row = pd.DataFrame([{'Name': 'Dave', 'Age': 28, 'City': 'Hyderabad'}])

df = pd.concat([new_row, df]).reset_index(drop=True)
print(df)

      Name  Age       City
0     Dave   28  Hyderabad
1    Alice   25      Delhi
2      Bob   30     Mumbai
3  Charlie   35       Pune

Comparison

Conclusion

Use pd.concat([new_row, df], ignore_index=True) as the most straightforward method to add a row at the top of a DataFrame. The index shift method works for in-place modification. Always use ignore_index=True or reset_index(drop=True) to maintain clean sequential indexing.