How to add new data to existing dataframe-CodePudding

I've created empty dataframe that I have to fill.

d = {'A': [], 'B': [], 'C': []}
dataframe = pd.DataFrame(data=d)

Then I am assigning data like this:

dataframe['A'] = some_list_1a
dataframe['B'] = some_list_1b
dataframe['C'] = some_list_1c

So my dataframe is filled like this:

 A      B     C
----------------
val1  val1  val1
val1  val1  val1
val1  val1  val1

Then I have to add new values from list but the previous way is not working: dataframe['A'] = some_list_2a etc.

That's what I want:

 A      B     C
----------------
val1  val1  val1
val1  val1  val1
val1  val1  val1
val2  val2  val2
val2  val1  val2
val2  val2  val2

(val1 - values from first lists, val2 - values from second lists)

I know I can make second dataframe and use concat method, but is there another way of doing it?

CodePudding user response：

Create dictionary with all joined lists first and then call DataFrame is fastest and recommended way, check this:

d = {'A': some_list_1a   some_list_2a, 
     'B': some_list_1b   some_list_2b,
     'C': some_list_1c   some_list_2c}
dataframe = pd.DataFrame(data=d)

If need append dict of list in loop:

from collections import defaultdict

d = defaultdict(list)

#some loop
for x in iter:
    d[col_name].append(sublist)
    
dataframe = pd.DataFrame(data=d)

CodePudding user response：

append() function is used to append rows of other dataframe to the end of the given dataframe, returning a new dataframe object. Columns not in the original dataframes are added as new columns and the new cells are populated with NONE value.