How to check if a column contains list

user_9760424 0
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import pandas as pd

df = pd.DataFrame({"col1": ["a", "b", "c", ["a", "b"]]})

I have a dataframe like this, and I want to find the rows that contains list in that column. I tried value_counts() but it tooks so long and throws error at the end. Here is the error:

TypeError                                 Traceback (most recent call last)
pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.map_locations()

TypeError: unhashable type: 'list'
Exception ignored in: 'pandas._libs.index.IndexEngine._call_map_locations'
Traceback (most recent call last):
  File "pandas/_libs/hashtable_class_helper.pxi", line 1709, in pandas._libs.hashtable.PyObjectHashTable.map_locations
TypeError: unhashable type: 'list'
c         1
a         1
[a, b]    1
b         1
Name: col1, dtype: int64

For bigger dataframes this tooks forever.

Here is how the desired output look like:

col1
c       1
b       1
[a,b]   1
dtype: int64
pandas python
2 Answers

Iterate on rows and check type of obj in column by this condition: type(obj) == list

import pandas as pd

df = pd.DataFrame({"col1": ["a", "b", "c", ["a", "b"]]})

for ind in df.index:
   print (type(df['col1'][ind]) == list)

And here is the result:

False
False
False
True
user_131183270

Lists are mutable, they cannot be compared, so you can neither count the values nor set them as index. You would need to convert to tuple or set (thanks @CameronRiddell) to be able to count:

df['col1'].apply(lambda x: tuple(x) if isinstance(x, list) else x).value_counts()

Output:

c         1
b         1
a         1
(a, b)    1
Name: col1, dtype: int64
user_42384080
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