Insert row at given position in Pandas Dataframe
Inserting a row in Pandas DataFrame is a very straight forward process and we have already discussed approaches in how insert rows at the start of the Dataframe. Now, let's discuss the ways in which we can insert a row at any position in the dataframe having integer based index.
Solution #1 : There does not exist any in-built function in pandas which will help us to insert a row at any specific position in the given dataframe. So, we are going to write our own customized function to achieve the result.
Note : Inserting rows in-between the rows in Pandas Dataframe is an inefficient operation and the user should avoid it.
# importing pandas as pd
import pandas as pd
# Let's create the dataframe
df = pd.DataFrame({'Date':['10/2/2011', '12/2/2011', '13/2/2011', '14/2/2011'],
'Event':['Music', 'Poetry', 'Theatre', 'Comedy'],
'Cost':[10000, 5000, 15000, 2000]})
# Let's visualize the dataframe
print(df)
Output :

Now we will write a customized function to insert a row at any given position in the dataframe.
# Function to insert row in the dataframe
def Insert_row(row_number, df, row_value):
# Starting value of upper half
start_upper = 0
# End value of upper half
end_upper = row_number
# Start value of lower half
start_lower = row_number
# End value of lower half
end_lower = df.shape[0]
# Create a list of upper_half index
upper_half = [*range(start_upper, end_upper, 1)]
# Create a list of lower_half index
lower_half = [*range(start_lower, end_lower, 1)]
# Increment the value of lower half by 1
lower_half = [x.__add__(1) for x in lower_half]
# Combine the two lists
index_ = upper_half + lower_half
# Update the index of the dataframe
df.index = index_
# Insert a row at the end
df.loc[row_number] = row_value
# Sort the index labels
df = df.sort_index()
# return the dataframe
return df
# Let's create a row which we want to insert
row_number = 2
row_value = ['11/2/2011', 'Wrestling', 12000]
if row_number > df.index.max()+1:
print("Invalid row_number")
else:
# Let's call the function and insert the row
# at the second position
df = Insert_row(row_number, df, row_value)
# Print the updated dataframe
print(df)
Output :

In case the given row_number is invalid, say total number of rows in dataframe are 100 then maximum value of row_number can be 101, i.e. adding row at the last of dataframe. Any number greater than 101 will given an error message.
Example #2: Another customized function which will use Pandas.concat() function to insert a row at any given position in the dataframe.
# importing pandas as pd
import pandas as pd
# Let's create the dataframe
df = pd.DataFrame({'Date':['10/2/2011', '12/2/2011', '13/2/2011', '14/2/2011'],
'Event':['Music', 'Poetry', 'Theatre', 'Comedy'],
'Cost':[10000, 5000, 15000, 2000]})
# Let's visualize the dataframe
print(df)
Output :

A customized function to insert a row at any given position in the dataframe.
# Function to insert row in the dataframe
def Insert_row_(row_number, df, row_value):
# Slice the upper half of the dataframe
df1 = df[0:row_number]
# Store the result of lower half of the dataframe
df2 = df[row_number:]
# Insert the row in the upper half dataframe
df1.loc[row_number]=row_value
# Concat the two dataframes
df_result = pd.concat([df1, df2])
# Reassign the index labels
df_result.index = [*range(df_result.shape[0])]
# Return the updated dataframe
return df_result
# Let's create a row which we want to insert
row_number = 2
row_value = ['11/2/2011', 'Wrestling', 12000]
if row_number > df.index.max()+1:
print("Invalid row_number")
else:
# Let's call the function and insert the row
# at the second position
df = Insert_row_(2, df, row_value)
# Print the updated dataframe
print(df)
Output :
