How to create new columns in a dataframe and assign them all with 0?

Question

Im using this syntax to preallocate columns and assign 0 to all of them:

data['Base'] = 0
data['Base_Chg'] = 0
data['Base_5D_Chg'] = 0
data['Year_Low'] = 0
data['Year_High'] = 0
data['Market_Cap'] = 0
data['PE_Ratio'] = 0
data['SMA_50'] = 0
data['SMA_100'] = 0
data['SMA_200'] = 0
data['RSI'] = 0
data['ADX'] = 0
data['ATR'] = 0
data['STDEV'] = 0

Is there any way of doing the same thing with fewer lines of code?

Using pandas in python.

Thx!

Answer 1

At the very least, you still have to write out all the new columns' names.

You can use a loop:

columns=['Base', 'Base_Chg', 'Base_5D_Chg', 'Year_Low', 'Year_High', 'Market_Cap', 'PE_Ratio', 'SMA_50', 'SMA_100', 'SMA_200', 'RSI', 'ADX', 'ATR', 'STDEV']
for col in columns:
    df[col] = 0

Or pd.concat:

columns=['Base', 'Base_Chg', 'Base_5D_Chg', 'Year_Low', 'Year_High', 'Market_Cap', 'PE_Ratio', 'SMA_50', 'SMA_100', 'SMA_200', 'RSI', 'ADX', 'ATR', 'STDEV']
new_df = pd.DataFrame(0, columns=columns, index=df.index)
df = pd.concat([df, new_df], axis=1)

Test to see which one is faster for your use case.