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)
pandas sum rows
# Basic syntax:
df.sum(axis=1)
# Create new column consisting of row sums across specific columns:
df['sums'] = df.iloc[:, 6:23].sum(axis=1)
# Where:
# - iloc allows you to specify the rows and columns with slicing. Here
# I select all rows and sum over columns 6-22
# - df['sums'] is how you assign a new column named 'sums' to the df
# Example usage:
import pandas as pd
import numpy as np
# Create dataframe:
df = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),
columns=['a', 'b', 'c'])
print(df)
a b c
0 1 2 3
1 4 5 6
2 7 8 9
# Sum columns 1-2:
df['sums'] = df.iloc[:, 1:3].sum(axis=1)
print(df)
a b c sums
0 1 2 3 5
1 4 5 6 11
2 7 8 9 17
python how to add columns to a pandas dataframe
# Basic syntax:
pandas_dataframe['new_column_name'] = ['list', 'of', 'column', 'values']
# Note, the list of column values must have length equal to the number
# of rows in the pandas dataframe you are adding it to.
# Add column in which all rows will be value:
pandas_dataframe['new_column_name'] = value
# Where value can be a string, an int, a float, and etc
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