add one row in a pandas.DataFrame

Question

I understand that pandas is designed to load fully populated DataFrame but I need to create an empty DataFrame then add rows, one by one. What is the best way to do this ?

I successfully created an empty DataFrame with :

res = DataFrame(columns=('lib', 'qty1', 'qty2'))

Then I can add a new row and fill a field with :

res = res.set_value(len(res), 'qty1', 10.0)

It works but seems very odd :-/ (it fails for adding string value)

How can I add a new row to my DataFrame (with different columns type) ?

Answer 1

Make it simple. By taking list as input which will be appended as row in data-frame:-

import pandas as pd  
res = pd.DataFrame(columns=('lib', 'qty1', 'qty2'))  
for i in range(5):  
    res_list = list(map(int, input().split()))  
    res = res.append(pd.Series(res_list,index=['lib','qty1','qty2']), ignore_index=True)

Answer 2

Here is the way to add/append a row in pandas DataFrame

def add_row(df, row):
    df.loc[-1] = row
    df.index = df.index + 1  
    return df.sort_index()

add_row(df, [1,2,3]) 

It can be used to insert/append a row in empty or populated pandas DataFrame

Answer 3

You can append a single row as a dictionary using the ignore_index option.

>>> f = pandas.DataFrame(data = {'Animal':['cow','horse'], 'Color':['blue', 'red']})
>>> f
  Animal Color
0    cow  blue
1  horse   red
>>> f.append({'Animal':'mouse', 'Color':'black'}, ignore_index=True)
  Animal  Color
0    cow   blue
1  horse    red
2  mouse  black

Answer 4

You could use pandas.concat() or DataFrame.append(). For details and examples, see Merge, join, and concatenate.

Answer 5

import pandas as pd 
t1=pd.DataFrame()
for i in range(len(the number of rows)):
    #add rows as columns
    t1[i]=list(rows)
t1=t1.transpose()
t1.columns=list(columns)

Answer 6

In case you can get all data for the data frame upfront, there is a much faster approach than appending to a data frame:

1. Create a list of dictionaries in which each dictionary corresponds to an input data row.
2. Create a data frame from this list.

I had a similar task for which appending to a data frame row by row took 30 min, and creating a data frame from a list of dictionaries completed within seconds.

rows_list = []
for row in input_rows:

        dict1 = {}
        # get input row in dictionary format
        # key = col_name
        dict1.update(blah..) 

        rows_list.append(dict1)

df = pd.DataFrame(rows_list)