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.
Python3
# importing pandas as pdimport pandas as pd# Let's create the dataframedf = 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 dataframeprint(df) |
Output :
Now we will write a customized function to insert a row at any given position in the dataframe.
Python3
# Function to insert row in the dataframedef 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 insertrow_number = 2row_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.
Python3
# importing pandas as pdimport pandas as pd# Let's create the dataframedf = 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 dataframeprint(df) |
Output :
A customized function to insert a row at any given position in the dataframe.
Python3
# Function to insert row in the dataframedef 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 insertrow_number = 2row_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 :
