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pandas column filter

filter = df['column']!= 0
df = df[filter]
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pd df filter columns by name

# select columns by name
df.filter(items=['col1', 'col2'])
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pandas filter column with or

alldata_balance = alldata[(alldata[IBRD] !=0) | (alldata[IMF] !=0)]
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pandas filter columns with IN

#To select rows whose column value is in list 
years = [1952, 2007]
gapminder.year.isin(years)
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