PYTHON

dataframe add row

# append row to dataframe without index

a_row = pd.Series([1, 2])
df = pd.DataFrame([[3, 4], [5, 6]])

row_df = pd.DataFrame([a_row])
df = pd.concat([row_df, df], ignore_index=True)

print(df)
# OUTPUT
#    0  1
# 0  1  2
# 1  3  4
# 2  5  6

# append row to dataframe with index

a_row = pd.Series([1, 2])
df = pd.DataFrame([[3, 4], [5, 6]], index = ["row1", "row2"])

row_df = pd.DataFrame([a_row], index = ["row3"])
df = pd.concat([row_df, df])

print(df)
# OUTPUT
#       0  1
# row3  1  2
# row1  3  4
# row2  5  6

insert row in any position pandas dataframe

line = DataFrame({"onset": 30.0, "length": 1.3}, index=[3])
df2 = concat([df.iloc[:2], line, df.iloc[2:]]).reset_index(drop=True)

insert row at given position in pandas dataframe

import pandas as pd
import numpy as np
x=pd.DataFrame([{'BOY':1,'GIRL':44},{'BOY':22,'GIRL':100}])
print(x)
x=x.T #TRANSPOSE IT AND MAKE IT AS COLUMN
x.insert(1,2,[44,56]) #INSERT A NEW COLUMN AT ANY POSITION
x=x.T # NOW TRANSPOSE IT AGAIN TO MAKE IT ROW AGAIN
x=x.reset_index(drop=True) # RESET INDEX 
print(x)

add new row to dataframe pandas

# Add a new row at index k with values provided in list
dfObj.loc['k'] = ['Smriti', 26, 'Bangalore', 'India']

add new row to dataframe pandas

>>> import pandas as pd
>>> from numpy.random import randint

>>> df = pd.DataFrame(columns=['lib', 'qty1', 'qty2'])
>>> for i in range(5):
>>>     df.loc[i] = ['name' + str(i)] + list(randint(10, size=2))

>>> df
     lib qty1 qty2
0  name0    3    3
1  name1    2    4
2  name2    2    8
3  name3    2    1
4  name4    9    6

add row to dataframe with index

In [99]: df = pd.DataFrame(np.random.randn(8, 4), columns=['A','B','C','D'])

In [100]: s = df.xs(3)

In [101]: s.name = 10

In [102]: df.append(s)
Out[102]: 
           A         B         C         D
0  -2.083321 -0.153749  0.174436  1.081056
1  -1.026692  1.495850 -0.025245 -0.171046
2   0.072272  1.218376  1.433281  0.747815
3  -0.940552  0.853073 -0.134842 -0.277135
4   0.478302 -0.599752 -0.080577  0.468618
5   2.609004 -1.679299 -1.593016  1.172298
6  -0.201605  0.406925  1.983177  0.012030
7   1.158530 -2.240124  0.851323 -0.240378
10 -0.940552  0.853073 -0.134842 -0.277135

python dataframe add row

# add dataframe-rows like this
df5 = pd.DataFrame([1], index=['a'])
df6 = pd.DataFrame([2], index=['a'])
pd.concat([df5, df6], verify_integrity=True)

add row to dataframe with index

In [99]: df = pd.DataFrame(np.random.randn(8, 4), columns=['A','B','C','D'])

In [100]: s = df.xs(3)

In [101]: s.name = 10

In [102]: df.append(s)
Out[102]: 
           A         B         C         D
0  -2.083321 -0.153749  0.174436  1.081056
1  -1.026692  1.495850 -0.025245 -0.171046
2   0.072272  1.218376  1.433281  0.747815
3  -0.940552  0.853073 -0.134842 -0.277135
4   0.478302 -0.599752 -0.080577  0.468618
5   2.609004 -1.679299 -1.593016  1.172298
6  -0.201605  0.406925  1.983177  0.012030
7   1.158530 -2.240124  0.851323 -0.240378
10 -0.940552  0.853073 -0.134842 -0.277135

add row to dataframe

mydataframe = mydataframe.append(new_row, ignore_index=True)

Add a row at a specific index pandas

df.loc[len(df.index)] = [value1, value2, value3, ...]