Compare data between Pandas series and Python list

Question

I have one Information csv , I used below to filter some specific name(Rony) from a column(Names) like below. Need help where marked in bold.

df= pd.read_csv('Info.csv',index_col=False)
App_=df[df['Names']=='Rony']
df_address=[]
address=App['Address']
df_address.append(address)

# This is printing result with index, I do not want to see index .Can index be avoided to print or remove in df_address ?

print(df_address)
dct=next(os.walk('.'))[1]

#Below is not working , Need help to fix this.How it can work with pandas.Need to check if directories name are available in df_address

for i in df_address:        
    if i in dct:
        #Do Some operation

Programs\Python\Python36-32\lib\site-packages\pandas\core\generic.py", line 1121, in __nonzero__ .format(self.__class__.__name__)) ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all(). — steveJ
– steveJ, Commented May 30, 2018 at 18:22

jpp · Accepted Answer · 2018-05-30 18:20:49Z

1

You do not need to append to a new list explicitly. There is functionality within pandas to convert a series to a list directly:

df_address = App['Address'].tolist()

Moreover, you can chain operations to make your logic more readable. For example, you can filter by row and column simultaneously:

df_address = df.loc[df['Names'] == 'Rony', 'Address']\
               .tolist()

answered May 30, 2018 at 18:20

jpp

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3 Comments

steveJ Over a year ago

Thanks for letting me about tolist() it fixed the entire issue :)

steveJ Over a year ago

os.walk - how it can be done recursively for directory? I have to write this but it seems long - for i in directories: print(i) l=next(os.walk(i))[1] for k in l: print(k)

jpp Over a year ago

I'm not sure. You may need to ask a separate question.

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