Setting column to true/false based on comparison of two other columns in pandas?

user_640558 0
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I have the following dataframe and I want to compare column value and predicted, if they match then I want to set the value of a column "provided" to False. I'm having difficulty doing this.

Here's my data:

    ticker  periodDate  value   predicted
0   ibm     2017    150079.080  150079.080
1   ibm     2016    49799.140   49799.140
2   ibm     2015    459.016     45949.016

I want a new column to just have a True/False if value and predicted match. I tried this but to no avail:

def provideOrPredicted(df):
  if df['value'] == df['predicted']:
    df['provided'] = False
  elif df['value'] != df['predicted']:
    df['provided'] = False
  print(df)

provideOrPredicted(MergedDF)

I get this error:

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
pandas python
2 Answers

Basically, below line will check each row and boolean result will be assigned into the new column of provided as:

 df['provided'] = df['value'] == df['predicted']
user_19532500
user_2022290
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