CODEWITHSUNDEEP
pythonpandasnumpy
Dinesh
Dinesh

Reputation: 16428

Retrieve dataframe row based on list from a cell value

I am trying to retrieve a row from a pandas dataframe where the cell value is a list. I have tried isin, but it looks like it is performing OR operation, not AND operation. 

>>> import pandas as pd
>>> df = pd.DataFrame([['100', 'RB','stacked'], [['101','102'], 'CC','tagged'], ['102', 'S+C','tagged']],
    columns=['vlan_id', 'mode' ,    'tag_mode'],index=['dinesh','vj','mani'])

>>> df
           vlan_id  mode  tag_mode
dinesh         100   RB  stacked
vj      [101, 102]   CC   tagged
mani           102  S+C   tagged

>>> df.loc[df['vlan_id'] == '102']; # Fetching string value match
      vlan_id mode tag_mode
mani     102  S+C   tagged

>>> df.loc[df['vlan_id'].isin(['100','102'])]; # Fetching if contains either 100 or 102

       vlan_id mode tag_mode
dinesh     100   RB  stacked
mani       102  S+C   tagged
>>> df.loc[df['vlan_id'] == ['101','102']]; # Fails ? 
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Python27\lib\site-packages\pandas\core\ops.py", line 1283, in wrapper
    res = na_op(values, other)
  File "C:\Python27\lib\site-packages\pandas\core\ops.py", line 1143, in na_op
    result = _comp_method_OBJECT_ARRAY(op, x, y)
  File "C:\Python27\lib\site-packages\pandas\core\ops.py", line 1120, in _comp_method_OBJECT_ARRAY
    result = libops.vec_compare(x, y, op)
  File "pandas\_libs\ops.pyx", line 128, in pandas._libs.ops.vec_compare
ValueError: Arrays were different lengths: 3 vs 2

I can get the values to a list and compare it. Instead, Is there any way available where we can check it against a list value using .loc method itself?

Upvotes: 0

Views: 98

Answers (3)

dvitsios
dvitsios

Reputation: 458

Another workaround would be to transform your vlan_id columns so that it can be queried as a string. You can do that by joining your vlan_id list values into comma-separated strings.

df['proxy'] = df['vlan_id'].apply(lambda x: ','.join(x) if type(x) is list else ','.join([x]) )

l = ','.join(['101', '102'])
print(df.loc[df['proxy'] == l])

Upvotes: 0

Mohit Motwani
Mohit Motwani

Reputation: 4792

To find a list you can iterate over the values of vlan_id and compare each value using np.array_equal:

df.loc[[np.array_equal(x, ['101','102']) for x in df.vlan_id.values]]


     vlan_id    mode    tag_mode
vj  [101, 102]  CC       tagged

Although, it's advised to avoid using lists as cell values in a dataframe.

DataFrame.loc can use a list of labels or a Boolean array to access rows and columns. The list comprehension above contructs a Boolean array.

Upvotes: 2

gmds
gmds

Reputation: 19885

I am not sure if this is the best way to do this, or if there is a good way to do this, since as far as I know pandas doesn't really support storing lists in Series. Still:

l = ['101', '102']

df.loc[pd.concat([df['vlan_id'].str[i] == l[i] for i in range(len(l))], axis=1).all(axis=1)]

Output:

       vlan_id mode tag_mode
vj  [101, 102]   CC   tagged

Upvotes: 0

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