Count number of rows when row contains certain text

Question

Probably a simple question but I could not find a simple answer. Let's for example take the following column Status within a dataframe df1:

**Status**
Planned
Unplanned
Missing
Corrected

I would like to count the rows when a cell contains, Planned and Missing. I tried the following:

test1 = df1['Status'].str.contains('Planned|Missing').value_counts()

The column Status is from the type: object. What's wrong with my line of code?

Answer 1

You can just filter the df with your boolean condition and then call len:

In [155]:
len(df[df['Status'].str.contains('Planned|Missing')])

Out[155]:
2

Or use the index True from your value_counts:

In [158]:   
df['Status'].str.contains('Planned|Missing').value_counts()[True]

Out[158]:
2

Answer 2

pd.Series.str.contains when coupled with na=False guarantees you have a Boolean series. Note also True / False act like 1 / 0 with numeric computations. You can now use pd.Series.sum directly:

count = df['Status'].str.contains('Planned|Missing', na=False).sum()

This avoids unnecessary and expensive dataframe indexing operations.