There are pandas.DataFrame :

  Game Genre PvP Rating_Hype 0 4Story MMORPG Yes 7.32 1 8BitMMO MMORPG Yes Req.Votes 2 9Dragons MMORPG Yes 7.38 3 A Tale in the Desert MMORPG Yes 7.43 4 A3 MMORPG Yes 6.50

you need to delete the rows in which in the last column of Req.Votes, and convert the remaining data into a number, who will help the inexperienced?

    1 answer 1

    Example:

    Source DataFrame:

     In [109]: df Out[109]: Game Genre PvP Rating_Hype 0 4Story MMORPG Yes 7.32 1 8BitMMO MMORPG Yes Req.Votes 2 9Dragons MMORPG Yes 7.38 3 A Tale in the Desert MMORPG Yes 7.43 4 A3 MMORPG Yes 6.50

    Decision:

     In [110]: df.Rating_Hype = pd.to_numeric(df.Rating_Hype, errors='coerse') In [111]: df Out[111]: Game Genre PvP Rating_Hype 0 4Story MMORPG Yes 7.32 1 8BitMMO MMORPG Yes NaN 2 9Dragons MMORPG Yes 7.38 3 A Tale in the Desert MMORPG Yes 7.43 4 A3 MMORPG Yes 6.50

    We get rid of the lines in which it was not possible to convert the rating into a number:

     In [112]: df = df[df.Rating_Hype.notnull()] In [113]: df Out[113]: Game Genre PvP Rating_Hype 0 4Story MMORPG Yes 7.32 2 9Dragons MMORPG Yes 7.38 3 A Tale in the Desert MMORPG Yes 7.43 4 A3 MMORPG Yes 6.50

    All the same one team:

     In [117]: df = df.assign(Rating_Hype=pd.to_numeric(df.Rating_Hype, errors='coerse')) \ .query("Rating_Hype == Rating_Hype") In [118]: df Out[118]: Game Genre PvP Rating_Hype 0 4Story MMORPG Yes 7.32 2 9Dragons MMORPG Yes 7.38 3 A Tale in the Desert MMORPG Yes 7.43 4 A3 MMORPG Yes 6.50 In [119]: df.dtypes Out[119]: Game object Genre object PvP object Rating_Hype float64 # <----------------- dtype: object