Ignoring Nans with Str. Contains
I Want to Find Rows That Contain a String, Like So: Df[Df. Col. Str. Contains("Foo")] However, This Fails Because Some Elements Are Nan: Valueerror: Cannot...
I want to find rows that contain a string, like so:
DF[DF.col.str.contains("foo")]
However, this fails because some elements are NaN:
ValueError: cannot index with vector containing NA / NaN values
So I resort to the obfuscated
DF[DF.col.notnull()][DF.col.dropna().str.contains("foo")]
Is there a better way?
6 Answers
There's a flag for that:
In [11]: df = pd.DataFrame([["foo1"], ["foo2"], ["bar"], [np.nan]], columns=['a'])
In [12]: df.a.str.contains("foo")
Out[12]:
0 True
1 True
2 False
3 NaN
Name: a, dtype: object
In [13]: df.a.str.contains("foo", na=False)
Out[13]:
0 True
1 True
2 False
3 False
Name: a, dtype: bool
See the str.replace docs:
na : default NaN, fill value for missing values.
So you can do the following:
In [21]: df.loc[df.a.str.contains("foo", na=False)]
Out[21]:
a
0 foo1
1 foo2
In addition to the above answers, I would say for columns having no single word name, you may use:-
df[df['Product ID'].str.contains("foo") == True]
Hope this helps.
df[df.col.str.contains("foo").fillna(False)]
I'm not 100% on why (actually came here to search for the answer), but this also works, and doesn't require replacing all nan values.
import pandas as pd
import numpy as np
df = pd.DataFrame([["foo1"], ["foo2"], ["bar"], [np.nan]], columns=['a'])
newdf = df.loc[df['a'].str.contains('foo') == True]
Works with or without .loc.
I have no idea why this works, as I understand it when you're indexing with brackets pandas evaluates whatever's inside the bracket as either True or False. I can't tell why making the phrase inside the brackets 'extra boolean' has any effect at all.
You can also use query method to query the columns of a DataFrame with a boolean expression as follows:
df.query('a.str.contains("foo", na=False)')
Note you might not get performance improvement, but it is more readable (arguably).
You can also patern :
DF[DF.col.str.contains(pat = '(foo)', regex = True) ]
James Sterling reports on renewable energy developments, climate policy, ecological conservation, and green tech innovations around the globe.
