Check if certain value is contained in a dataframe column in pandas [duplicate]

Question

I am trying to check if a certain value is contained in a python column. I'm using df.date.isin(['07311954']), which I do not doubt to be a good tool. The problem is that I have over 350K rows and the output won't show all of them so that I can see if the value is actually contained. Put simply, I just want to know (Y/N) whether or not a specific value is contained in a column. My code follows:

import numpy as np import pandas as pd import glob   df = (pd.read_csv('/home/jayaramdas/anaconda3/Thesis/FEC_data/itpas2_data/itpas214.txt',\     sep='|', header=None, low_memory=False, names=['1', '2', '3', '4', '5', '6', '7', \     '8', '9', '10', '11', '12', '13', 'date', '15', '16', '17', '18', '19', '20', \     '21', '22']))  df.date.isin(['07311954']) 

Answer 1

You can simply use this:

'07311954' in df.date.values which returns True or False

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Here is the further explanation:

In pandas, using in check directly with DataFrame and Series (e.g. val in df or val in series ) will check whether the val is contained in the Index.

BUT you can still use in check for their values too (instead of Index)! Just using val in df.col_name.values or val in series.values. In this way, you are actually checking the val with a Numpy array.

And .isin(vals) is the other way around, it checks whether the DataFrame/Series values are in the vals. Here vals must be set or list-like. So this is not the natural way to go for the question.