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How to filter a pandas dataframe using multiple partial strings?


How to filter a pandas dataframe using multiple partial strings?

By : Hello
Date : November 29 2020, 12:01 PM
this will help Use str.contains with | for multiple search elements:
code :
mask = df['Answers'].str.contains(regex_pattern)
final_df = df[mask]
strings_to_find = ["not in","not on","not have"]
regex_pattern = '|'.join(strings_to_find)
regex_pattern 
'not in|not on|not have'


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How to filter pandas dataframe columns by partial label

How to filter pandas dataframe columns by partial label


By : Welty Visser
Date : March 29 2020, 07:55 AM
hop of those help? I am trying to filter pandas dataframe columns (with type pandas.core.index.Index) by a partial label. , possible solutions:
code :
df.filter(regex='partial_lab.*')
idx = df.columns.to_series().str.startswith('partial_lab')
df.loc[:,idx]
Filter pandas (python) dataframe based on partial strings in a list

Filter pandas (python) dataframe based on partial strings in a list


By : Foolish Frog
Date : March 29 2020, 07:55 AM
around this issue The pandas str.contains accepts regular expressions, which let's you test for any item in a list. Loop through each column and use str.contains:
code :
startstrings = ['one', 'two']
pattern = '|'.join(startstrings)

for col in df:
    if all(df[col].apply(type) == str):
        #Set any values to 0 if they don't contain value
        df.ix[~df[col].str.contains(pattern), col] = 0        
    else:
        #Column is not all strings
        df[col] = 0
      A     B  C  D
0     0  one1  0  0
1     0  one1  0  0
2  one1  two1  0  0
3     0     0  0  0
4     0  two1  0  0
5  one1  two1  0  0
6     0  one1  0  0
7     0     0  0  0
How to filter Pandas dataframe by a partial label

How to filter Pandas dataframe by a partial label


By : K. Nevin
Date : March 29 2020, 07:55 AM
it should still fix some issue Create a boolean mask, and filter accordingly, using boolean indexing/loc/isin/query/eval.
code :
m = m = df.user_id.eq('101') & df.label.eq('1')

i = df[m].head(3)
j = df[~m]

df = pd.concat([i, j]).sort_index()
df

  user_id         comment label
0     100   First comment     0
1     101      Buy viagra     1
2     102  Second comment     0
3     101   Third comment     0
4     103  Fourth comment     0
5     101       Buy drugs     1
6     104   Fifth comment     0
7     101    Buy icecream     1
8     105   Sixth comment     0
Filter a pandas dataframe on multiple columns for partial string match, using values from a dict

Filter a pandas dataframe on multiple columns for partial string match, using values from a dict


By : Said Fannane
Date : March 29 2020, 07:55 AM
Hope that helps One solution can be using pd.Series.str.starstwith to find strings matching the ones in filters.
You can create a mask for those rows this way:
code :
mask =  df.astype(str).apply(lambda x: x.str.lower()
        ).apply(lambda x: x.str.startswith(filters[x.name].lower()),
                axis=0).all(axis=1)
df[mask]

        country  year         pop continent  lifeExp   gdpPercap
11  Afghanistan  2007  31889923.0      Asia   43.828  974.580338
Filter Pandas Dataframe Columns by header containing multiple strings

Filter Pandas Dataframe Columns by header containing multiple strings


By : user2181055
Date : November 09 2020, 04:01 AM
it should still fix some issue I have a dataframe and want to only show columns with headers containing a particular string(s). , Use:
code :
L = ['BB','TP']
df.loc[:, df.columns.str.contains('|'.join(L)] 
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