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Tag: apply

Mutiple style for one DataFrame issues

I would like to understand how “style” works in python, I always have the same error : AttributeError: ‘Styler’ object has no attribute …. for now, I manage to have : the first row in yellow but not the conditional formatting (df_x0) and the conditional formatting blue and orange cells but the first row disappear because I am obligate to

Pandas apply function to each row by calculating multiple columns

I have been stacked by an easy question, and my question title might be inappropriate. I want to calculate (df.amount * df.con)/df.groupby(‘name’).agg({‘amount’:’sum’}).reset_index().loc(df.name==i).amount) (Sorry, this line will return error, but what I want is to calculate total concentration (under each name) based on each ingredient amount and ingredient con. Here is my code: output: Any short-cut for this calculation? Thanks ahead.

How to use pandas apply to replace iterrows?

I am calculating the sentiment value on every row in the dataset based on news headline. I used iterrows to achieve this: However, the processing time is taking too long (>30 minutes runtime and it is not done yet). I have 16.6k rows in my dataset. This is a small section of the dataset: I have read that iterrows is

add random elemnt from list to existing dataframe string

I have a dataframe. df[‘Skill’]=python, sql, java. Now for each string I want to add random element (high, low, medium). For Eg: df[‘Skill’]=python:high, sql:low, java:medium. I have tried one code but it adds score[‘low’, ‘high’, ‘medium’] at the end of the string. Can someone please suggest how can i do it. Output: But i want is python: low, java: high,

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