By using Python for loop you can append rows or columns to Pandas DataFrames. You can append rows to DataFrame by using append(), pandas.concat(), and loc[]. In this article, I will explain how to append rows or columns to pandas DataFrame using a for loop and with the help of the above functions.
1. Quick Examples of Append to DataFrame Using For Loop
If you are in a hurry, below are some quick examples of appending pandas DataFrames using Python for loop.
# Below are some quick examples.
# Example 1: Append rows within a for loop
for i in range(1,4):
df.loc[len(df)] = i *1
# Example 2: Append values to DataFrame
for i in range(1,4):
df[i] = i *1
# Example 3: Append rows within for loop
# Create empty DataFrame
df = pd.DataFrame(columns = ['c1', 'c2', 'c3'])
for i in range(5):
df.loc[len(df)] = i * 5
# Example 4: Append DataFrame using for loop
# Create a List
list1 = ['Python','PySpark', 'Pandas', 'NumPy']
# Create an empty list
list2 = []
# Create new values using for loop
for value in list1:
df_values = value
# Append df_values to llist2
list2.append(df_values)
# create DataFrame using for loop
df = pd.DataFrame(list2, columns=['Course'],index=['I1','I2','I3','I4'])
# Example 5: Append DataFrames using Dictionary
# Create a DataFrame
df = pd.DataFrame({'Squares':[4, 9, 16, 25 ],
'Cubes':[8, 27, 64, 125]})
for i in range(6,10):
df=df.append({'Squares': i**2, 'Cubes': i**3}, ignore_index=True)
Let’s create a pandas DataFrame from Python Dictionary with a few rows and columns and execute some examples to learn how to insert rows. Our DataFrame contains column names Courses, Fee, Duration, and Discount.
# Create DataFrame
import pandas as pd
technologies = ({
'Courses':["Spark","Hadoop","pandas","Java","PySpark"],
'Fee' :[20000,25000,30000,22000,26000],
'Duration':['30days','40days','35days','60days','50days'],
'Discount':[1000,2500,1500,1200,3000]
})
df = pd.DataFrame(technologies)
print("Create DataFrame:\n", df)
Yields below output.
2. Append Pandas DataFrames using For Loop
You can use a for loop to append a range of values at the end of our DataFrame. The following example shows how to add the row with the same values to DataFrame for each iteration. Let’s append rows to a pandas DataFrame within a loop.
# Append rows within for loop
for i in range(1,4):
df.loc[len(df)] = i *1
print("After appending the rows to DataFrame:\n", df)
Yields below output.
Alternatively, using a for loop we can add a range of values as a column of DataFrame. We will get the values of the new columns at each iteration.
# Append values to DataFrame
for i in range(1,4):
df[i] = i *1
print("After appending the columns to DataFrame:\n", df)
Yields below output.
# Output:
# After appending the columns to DataFrame:
Courses Fee Duration Discount 1 2 3
0 Spark 20000 30days 1000 1 2 3
1 Hadoop 25000 40days 2500 1 2 3
2 pandas 30000 35days 1500 1 2 3
3 Java 22000 60days 1200 1 2 3
4 PySpark 26000 50days 3000 1 2 3
4. Append Rows to Empty DataFrame in a For Loop
Let’s see how to append rows to an empty DataFrame using a for loop, first let’s create an empty DataFrame.
# Create empty DataFrame
df = pd.DataFrame(columns = ['c1', 'c2', 'c3'])
print(df)
# Output:
# Empty DataFrame
# Columns: [c1, c2, c3]
# Index: []
Use a for loop to append new rows to our empty DataFrame.
# Append rows within for loop
for i in range(5):
df.loc[len(df)] = i * 5
print(df)
Yields below output.
# Output:
c1 c2 c3
0 0 0 0
1 5 5 5
2 10 10 10
3 15 15 15
4 20 20 20
5. Another way to Append DataFrame within a for loop
This is another way in which I want to append DataFrames within a loop. To append first create a DataFrame, using a dictionary and concatenate them into a single DataFrame within a for a loop. This process is faster than appending new rows to the DataFrame after each step, as you are not constructing a new DataFrame on every iteration.
# Create a DataFrame
df = pd.DataFrame({'Squares':[4, 9, 16, 25 ],
'Cubes':[8, 27, 64, 125]})
for i in range(6, 10):
df=df.append({'Squares': i**2, 'Cubes': i**3}, ignore_index=True)
print(df)
Yields below output.
# Output:
Squares Cubes
0 4 8
1 9 27
2 16 64
3 25 125
4 36 216
5 49 343
6 64 512
7 81 729
6. Conclusion
In this article, I have explained how to append pandas DataFrames by using for loop with the help of append() function.
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