I would like to see if a particular string exists in a particular column within my dataframe.
I\'m getting the error
ValueError: The truth v
it seems that the OP meant to find out whether the string 'Mel' exists in a particular column, not contained in a column, therefore the use of contains is not needed, and is not efficient. A simple equals-to is enough:
(a['Names']=='Mel').any()
Pandas seem to be recommending df.to_numpy since
the other methods still raise a FutureWarning
: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_numpy.html#pandas.DataFrame.to_numpy
So, an alternative that would work int this case is:
b=a['Names']
c = b.to_numpy().tolist()
if 'Mel' in c:
print("Mel is in the dataframe column Names")
a['Names'].str.contains('Mel')
will return an indicator vector of boolean values of size len(BabyDataSet)
Therefore, you can use
mel_count=a['Names'].str.contains('Mel').sum()
if mel_count>0:
print ("There are {m} Mels".format(m=mel_count))
Or any()
, if you don't care how many records match your query
if a['Names'].str.contains('Mel').any():
print ("Mel is there")
You should use any()
In [98]: a['Names'].str.contains('Mel').any()
Out[98]: True
In [99]: if a['Names'].str.contains('Mel').any():
....: print "Mel is there"
....:
Mel is there
a['Names'].str.contains('Mel')
gives you a series of bool values
In [100]: a['Names'].str.contains('Mel')
Out[100]:
0 False
1 False
2 False
3 False
4 True
Name: Names, dtype: bool
You should check the value of your line of code like adding checking length of it.
if(len(a['Names'].str.contains('Mel'))>0):
print("Name Present")
If there is any chance that you will need to search for empty strings,
a['Names'].str.contains('')
will NOT work, as it will always return True.
Instead, use
if '' in a["Names"].values
to accurately reflect whether or not a string is in a Series, including the edge case of searching for an empty string.