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pythonpandas
Robert Prine
Robert Prine

Reputation: 2753

Python Pandas returning rows with multiple conditions - TypeError: unsupported operand type(s) for &: 'str' and 'str'

I am new to python and pandas in general, but I am having trouble where I want to change a column in all rows that meet a list of conditions. The code that I am currently using is as follows:

raw_table.loc[raw_table[raw_table['id'] > id_] & raw_table[raw_table['type name'].str.replace(' ', '') == tableName] & raw_table[raw_table['ordinal'] > ordinal_], 'type name'] = newTableName

The variables are what I need them to be and when I print() the conditions out in the console they are working individually, but when I try to do a grouping of them together I get the error:

ipdb> print ((raw_table[raw_table['id'] > id_]) & (raw_table[raw_table['type name'].str.replace(' ', '') == tableName]))
*** TypeError: unsupported operand type(s) for &: 'str' and 'str'

Is there a better way to do this that I haven't found yet or is my syntax just off? Thank you in advance for any help!

Upvotes: 1

Views: 339

Answers (1)

rahlf23
rahlf23

Reputation: 9019

IIUC, you need to wrap your conditions in parenthesis when applying multiple conditional filters to your dataframe:

raw_table[(raw_table['id'] > id_) & (raw_table['type name'].str.replace(' ', '') == tableName) & (raw_table['ordinal'] > ordinal_)]['type name'] = newTableName

Or more legibly:

cond1 = raw_table['id'] > id_
cond2 = raw_table['type name'].str.replace(' ', '') == tableName
cond3 = raw_table['ordinal'] > ordinal_

raw_table[(cond1) & (cond2) & (cond3)]['type name'] = newTableName

Upvotes: 4

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