add rows to dataframe pandas
df = df.append({'a':1, 'b':2}, ignore_index=True)
add rows to dataframe pandas
df = df.append({'a':1, 'b':2}, ignore_index=True)
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
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 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
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