df = df.append({'a':1, 'b':2}, ignore_index=True)
# 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
# Add a new row at index k with values provided in list
dfObj.loc['k'] = ['Smriti', 26, 'Bangalore', 'India']
df.loc[-1] = [2, 3, 4] # adding a row
df.index = df.index + 1 # shifting index
df = df.sort_index() # sorting by index
>>> 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
df.loc[-1] = [2, 3, 4] # adding a row
df.index = df.index + 1 # shifting index
df = df.sort_index() # sorting by index
# add dataframe-rows like this
df5 = pd.DataFrame([1], index=['a'])
df6 = pd.DataFrame([2], index=['a'])
pd.concat([df5, df6], verify_integrity=True)
mydataframe = mydataframe.append(new_row, ignore_index=True)