Appending a list or series to a pandas DataFrame as a row?
PythonPandasAppendDataframePython Problem Overview
So I have initialized an empty pandas DataFrame and I would like to iteratively append lists (or Series) as rows in this DataFrame. What is the best way of doing this?
Python Solutions
Solution 1 - Python
Sometimes it's easier to do all the appending outside of pandas, then, just create the DataFrame in one shot.
>>> import pandas as pd
>>> simple_list=[['a','b']]
>>> simple_list.append(['e','f'])
>>> df=pd.DataFrame(simple_list,columns=['col1','col2'])
col1 col2
0 a b
1 e f
Solution 2 - Python
df = pd.DataFrame(columns=list("ABC"))
df.loc[len(df)] = [1,2,3]
Solution 3 - Python
Here's a simple and dumb solution:
>>> import pandas as pd
>>> df = pd.DataFrame()
>>> df = df.append({'foo':1, 'bar':2}, ignore_index=True)
Solution 4 - Python
Could you do something like this?
>>> import pandas as pd
>>> df = pd.DataFrame(columns=['col1', 'col2'])
>>> df = df.append(pd.Series(['a', 'b'], index=['col1','col2']), ignore_index=True)
>>> df = df.append(pd.Series(['d', 'e'], index=['col1','col2']), ignore_index=True)
>>> df
col1 col2
0 a b
1 d e
Does anyone have a more elegant solution?
Solution 5 - Python
Following onto Mike Chirico's answer... if you want to append a list after the dataframe is already populated...
>>> list = [['f','g']]
>>> df = df.append(pd.DataFrame(list, columns=['col1','col2']),ignore_index=True)
>>> df
col1 col2
0 a b
1 d e
2 f g
Solution 6 - Python
There are several ways to append a list to a Pandas Dataframe in Python. Let's consider the following dataframe and list:
import pandas as pd
# Dataframe
df = pd.DataFrame([[1, 2], [3, 4]], columns = ["col1", "col2"])
# List to append
list = [5, 6]
Option 1: append the list at the end of the dataframe with pandas.DataFrame.loc
.
df.loc[len(df)] = list
Option 2: convert the list to dataframe and append with pandas.DataFrame.append()
.
df = df.append(pd.DataFrame([list], columns=df.columns), ignore_index=True)
Option 3: convert the list to series and append with pandas.DataFrame.append()
.
df = df.append(pd.Series(list, index = df.columns), ignore_index=True)
Each of the above options should output something like:
>>> print (df)
col1 col2
0 1 2
1 3 4
2 5 6
Reference : How to append a list as a row to a Pandas DataFrame in Python?
Solution 7 - Python
Converting the list to a data frame within the append function works, also when applied in a loop
import pandas as pd
mylist = [1,2,3]
df = pd.DataFrame()
df = df.append(pd.DataFrame(data[mylist]))
Solution 8 - Python
Here's a function that, given an already created dataframe, will append a list as a new row. This should probably have error catchers thrown in, but if you know exactly what you're adding then it shouldn't be an issue.
import pandas as pd
import numpy as np
def addRow(df,ls):
"""
Given a dataframe and a list, append the list as a new row to the dataframe.
:param df: <DataFrame> The original dataframe
:param ls: <list> The new row to be added
:return: <DataFrame> The dataframe with the newly appended row
"""
numEl = len(ls)
newRow = pd.DataFrame(np.array(ls).reshape(1,numEl), columns = list(df.columns))
df = df.append(newRow, ignore_index=True)
return df
Solution 9 - Python
If you want to add a Series and use the Series' index as columns of the DataFrame, you only need to append the Series between brackets:
In [1]: import pandas as pd
In [2]: df = pd.DataFrame()
In [3]: row=pd.Series([1,2,3],["A","B","C"])
In [4]: row
Out[4]:
A 1
B 2
C 3
dtype: int64
In [5]: df.append([row],ignore_index=True)
Out[5]:
A B C
0 1 2 3
[1 rows x 3 columns]
Whitout the ignore_index=True
you don't get proper index.
Solution 10 - Python
simply use loc:
>>> df
A B C
one 1 2 3
>>> df.loc["two"] = [4,5,6]
>>> df
A B C
one 1 2 3
two 4 5 6
Solution 11 - Python
As mentioned here - https://kite.com/python/answers/how-to-append-a-list-as-a-row-to-a-pandas-dataframe-in-python, you'll need to first convert the list to a series then append the series to dataframe.
df = pd.DataFrame([[1, 2], [3, 4]], columns = ["a", "b"])
to_append = [5, 6]
a_series = pd.Series(to_append, index = df.columns)
df = df.append(a_series, ignore_index=True)
Solution 12 - Python
Consider an array A of N x 2 dimensions. To add one more row, use the following.
A.loc[A.shape[0]] = [3,4]
Solution 13 - Python
The simplest way:
my_list = [1,2,3,4,5]
df['new_column'] = pd.Series(my_list).values
Edit:
Don't forget that the length of the new list should be the same of the corresponding Dataframe.