PYTHON
add rows to dataframe pandas
df = df.append({'a':1, 'b':2}, ignore_index=True)
R add row to dataframe
library(tidyverse)
df %>% add_row(hello = "hola", goodbye = "ciao")
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
Appending rows to a DataFrame
s2 = pd.Series(["X0", "X1", "X2", "X3"], index=["A", "B", "C", "D"])
In [32]: result = pd.concat([df1, s2.to_frame().T], ignore_index=True)
add one row to DataFrame
import pandas as pd
df.loc[len(df.index)] = [column1, column2, column3]
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']
pandas insert row
df.loc[-1] = [2, 3, 4] # adding a row
df.index = df.index + 1 # shifting index
df = df.sort_index() # sorting by index
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
Appending rows to a DataFrame
s2 = pd.Series(["X0", "X1", "X2", "X3"], index=["A", "B", "C", "D"])
In [32]: result = pd.concat([df1, s2.to_frame().T], ignore_index=True)
Appending rows to a DataFrame
s2 = pd.Series(["X0", "X1", "X2", "X3"], index=["A", "B", "C", "D"])
In [32]: result = pd.concat([df1, s2.to_frame().T], ignore_index=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
insert row in dataframe pandas
df.loc[-1] = [2, 3, 4] # adding a row
df.index = df.index + 1 # shifting index
df = df.sort_index() # sorting by index
Appending rows to a DataFrame
s2 = pd.Series(["X0", "X1", "X2", "X3"], index=["A", "B", "C", "D"])
In [32]: result = pd.concat([df1, s2.to_frame().T], ignore_index=True)
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)
Appending rows to a DataFrame
s2 = pd.Series(["X0", "X1", "X2", "X3"], index=["A", "B", "C", "D"])
In [32]: result = pd.concat([df1, s2.to_frame().T], ignore_index=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
Appending rows to a DataFrame
s2 = pd.Series(["X0", "X1", "X2", "X3"], index=["A", "B", "C", "D"])
In [32]: result = pd.concat([df1, s2.to_frame().T], ignore_index=True)
add row to dataframe
mydataframe = mydataframe.append(new_row, ignore_index=True)
Appending rows to a DataFrame
s2 = pd.Series(["X0", "X1", "X2", "X3"], index=["A", "B", "C", "D"])
In [32]: result = pd.concat([df1, s2.to_frame().T], ignore_index=True)
Appending rows to a DataFrame
s2 = pd.Series(["X0", "X1", "X2", "X3"], index=["A", "B", "C", "D"])
In [32]: result = pd.concat([df1, s2.to_frame().T], ignore_index=True)