How to add multiple columns to pandas dataframe in one assignment Ask Question Asked 7 years, 4 months ago Modified 9 months ago Viewed 469k times 291 I'm trying to figure out how to add multiple columns to pandas simultaneously with Pandas. I would like to do this in one step rather than multiple repeated steps. There are multiple ways to add columns to pandas dataframe. Add multiple columns to a DataFrame using Lists Python3 import pandas as pd students = [ ['jackma', 34, 'Sydeny', 'Australia'], ['Ritika', 30, 'Delhi', 'India'], ['Vansh', 31, 'Delhi', 'India'], ['Nany', 32, 'Tokyo', 'Japan'], ['May', 16, 'New York', 'US'],
How to Group by Two & Multiple Columns of pandas DataFrame in Python
You can use the following methods to add multiple columns to a pandas DataFrame: Method 1: Add Multiple Columns that Each Contain One Value df [ ['new1', 'new2', 'new3']] = pd.DataFrame( [ [4, 'hey', np.nan]], index=df.index) Method 2: Add Multiple Columns that Each Contain Multiple Values Parameters: otherscalar, sequence, Series, dict or DataFrame Any single or multiple element data structure, or list-like object. axis{0 or 'index', 1 or 'columns'} Whether to compare by the index (0 or 'index') or columns. (1 or 'columns'). For Series input, axis to match Series index on. levelint or label In this example, I'll demonstrate how to combine multiple new columns with an existing pandas DataFrame in one line of code. Consider the following python syntax: data_new = data. copy ( ) # Create copy of DataFrame data_new [ "new1" ] , data_new [ "new2" ] = [ new1 , new2 ] # Add multiple columns print ( data_new ) # Print updated pandas DataFrame Let's see how we can add up values across rows in Pandas: # Adding up dataframe rows using .sum () dataframe_sum = df. sum (axis= 1, numeric_only= True ) print (dataframe_sum) # Returns: # 0 285 # 1 285 # 2 200 # 3 233 # 4 200 # 5 220 # 6 255 # dtype: int64. You may be wondering why we apply the numeric_only=True argument here.
Add Multiple Columns to pandas DataFrame in Python Append & Merge
A simple way to add a new column to a Pandas DataFrame is to assign a list to a new column. This allows you to directly assign a new column based on existing or new data. Let's take a look at how to add a new column from a list: python - Add Multiple Columns to Pandas Dataframe from Function - Stack Overflow Add Multiple Columns to Pandas Dataframe from Function Ask Question Asked 8 years, 7 months ago Modified 4 years, 9 months ago Viewed 61k times 44 I have a pandas data frame mydf that has two columns,and both columns are datetime datatypes: mydate and mytime. This means all values in the given column are multiplied by the value 1.882 at once. You do not need to use a loop to iterate each of the rows! I want to check the ratio of the values in Paris versus Antwerp and save the result in a new column. 8 Answers Sorted by: 123 You could use df.reindex to add new columns: In [18]: df = pd.DataFrame (np.random.randint (10, size= (5,1)), columns= ['A']) In [19]: df Out [19]: A 0 4 1 7 2 0 3 7 4 6 In [20]: df.reindex (columns=list ('ABCD')) Out [20]: A B C D 0 4 NaN NaN NaN 1 7 NaN NaN NaN 2 0 NaN NaN NaN 3 7 NaN NaN NaN 4 6 NaN NaN NaN
Pandas Plotting Multiple Columns Across Rows In A Dataframe Stack Images
In pandas you can add/append multiple columns to the existing DataFrame using assign () function, this function updates the existing DataFrame with new multiple columns. DataFrame.insert () is also used to insert multiple columns however, this function returns a new Dataframe after adding columns. We can select individual columns by column names using [] operator and then we can add values in those columns using + operator. For example, Copy to clipboard # Add two columns together to make a new series
The straightforward answer is df ['e'] = e, but that doesn't work if the indexes don't match, but the indexes only don't match because OP created it like that ( e = Series (
) ), but that was removed from the question in revision 5. - wjandrea Dec 23, 2021 at 0:40 Add a comment 33 Answers Sorted by: 1 2 Next 1307 Edit 2017 Add multiple columns. To add multiple columns in the same time, a solution is to use pandas.concat: data = np.random.randint (10, size= (5,2)) columns = ['Score E','Score F'] df_add = pd.DataFrame (data=data,columns=columns) print (df) df = pd.concat ( [df,df_add], axis=1) print (df) returns. Score A Score B Score C Score D Score E Score F 0 1. 
Add Multiple Columns to pandas DataFrame in Python Append & Merge
This is a complementary method to MultiIndex.to_frame (). In [10]: df = pd.DataFrame(..: [ ["bar", "one"], ["bar", "two"], ["foo", "one"], ["foo", "two"]],..: columns=["first", "second"],..: )..: There are multiple ways to add a new Column to an Existing DataFrame in Pandas in Python: Creating a Sample Dataframe By using Dataframe.insert () method By using Dataframe.assign () method Using Dictionary Using List Using .loc () Adding More than One columns in Existing Dataframe Creating a Sample Dataframe
