Pandas: Look if items are in a list in Series.series in a dataframe

Question

I have a Dataframe that look like this (small version):

    A   B   C
0   125 ADB [AF:12]
1   189 ACB [AF:78, AF:85, AF:98]
2   148 ADB []
3   789 ARF [AF:89, AF:85, AF:12]
4   789 BCD [AF:76, AF:25]

How can I see if some of the items in column "C" are in a list? knowing that when I do type(df.C) I get class 'pandas.core.series.Series'

if for example the list is:

['AF:12', 'AF25']

The expected output would be:

    A   B   C                        D
0   125 ADB [AF:12]                  True
1   189 ACB [AF:78, AF:85, AF:98]    False
2   148 ADB []                       False
3   789 ARF [AF:89, AF:85, AF:12]    True
4   789 BCD [AF:76, AF:25]           True

I have tried df['D'] = df['C'].isin(list) but get False everywhere probably because "C" is a list of list.

Is there a way to get around that?

Any help would be greatly appreciated

What is the type of df['C'] ? try type(df['C'][0]) .

Anand S Kumar
– Anand S Kumar

2015-10-07 04:47:01 +00:00
Commented Oct 7, 2015 at 4:47 — Anand S Kumar
– Anand S Kumar, Commented Oct 7, 2015 at 4:47

Anand S Kumar · Accepted Answer · 2015-10-07 06:14:29Z

4

If the type of elements of C column is list , then I believe one method to do this would be to use set intersection between your list and the elements of C column using Series.apply method . Example -

setlst = set(yourlist)
df['D'] = df['C'].apply(lambda x: bool(setlst.intersection(x)))

You can confirm that C is of type list, if type(df['C'][0]) is list .

Also please note using list as a variable name is not recommended as it would shadow the built in type list .

edited Oct 7, 2015 at 6:14

answered Oct 7, 2015 at 5:20

Anand S Kumar

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1 Comment

Jérémz Over a year ago

I will try that as well thanks. And keep in mind the advice.

Liam Foley · Accepted Answer · 2015-10-07 05:13:00Z

1

data = {'B':['ADB','ACB','ADB','ARF','BCD'],
        'A':[125,189,148,789,789],
        'C':[['AF:12'],['AF:78', 'AF:85', 'AF:98'],[],
        ['AF:89', 'AF:85', 'AF:12'],['AF:76', 'AF:25']]}

df = pd.DataFrame(data)

def in_list(list_to_search,terms_to_search):
    results = [item for item in list_to_search if item in terms_to_search]
    if len(results) > 0:
        return 'True'
    else:
        return 'False'

df['D'] = df['C'].apply(lambda x: in_list(x, ['AF:12', 'AF:25']))

Result:

     A    B                      C      D
0  125  ADB                [AF:12]   True
1  189  ACB  [AF:78, AF:85, AF:98]  False
2  148  ADB                     []  False
3  789  ARF  [AF:89, AF:85, AF:12]   True
4  789  BCD         [AF:76, AF:25]   True

answered Oct 7, 2015 at 5:13

Liam Foley

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1 Comment

Jérémz Over a year ago

Thanks, looks like working for me! This function is of great help to handle series of series

starkshang · Accepted Answer · 2015-10-07 04:56:54Z

0

def is_in_list():
    for ele in df['C']:
    if ele in list:
        return True
    return False;

Maybe this function can make it.

answered Oct 7, 2015 at 4:56

starkshang

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