This should do the trick
'g' in df.index
Pregunta
I am sure there is an obvious way to do this but cant think of anything slick right now.
Basically instead of raising exception I would like to get True
or False
to see if a value exists in pandas df
index.
import pandas as pd
df = pd.DataFrame({'test':[1,2,3,4]}, index=['a','b','c','d'])
df.loc['g'] # (should give False)
What I have working now is the following
sum(df.index == 'g')
Solución
This should do the trick
'g' in df.index
Otros consejos
Multi index works a little different from single index. Here are some methods for multi-indexed dataframe.
df = pd.DataFrame({'col1': ['a', 'b','c', 'd'], 'col2': ['X','X','Y', 'Y'], 'col3': [1, 2, 3, 4]}, columns=['col1', 'col2', 'col3'])
df = df.set_index(['col1', 'col2'])
in df.index
works for the first level only when checking single index value.
'a' in df.index # True
'X' in df.index # False
Check df.index.levels
for other levels.
'a' in df.index.levels[0] # True
'X' in df.index.levels[1] # True
Check in df.index
for an index combination tuple.
('a', 'X') in df.index # True
('a', 'Y') in df.index # False
Just for reference as it was something I was looking for, you can test for presence within the values or the index by appending the ".values" method, e.g.
g in df.<your selected field>.values
g in df.index.values
I find that adding the ".values" to get a simple list or ndarray out makes exist or "in" checks run more smoothly with the other python tools. Just thought I'd toss that out there for people.
Code below does not print boolean, but allows for dataframe subsetting by index... I understand this is likely not the most efficient way to solve the problem, but I (1) like the way this reads and (2) you can easily subset where df1 index exists in df2:
df3 = df1[df1.index.isin(df2.index)]
or where df1 index does not exist in df2...
df3 = df1[~df1.index.isin(df2.index)]
with DataFrame: df_data
>>> df_data
id name value
0 a ampha 1
1 b beta 2
2 c ce 3
I tried:
>>> getattr(df_data, 'value').isin([1]).any()
True
>>> getattr(df_data, 'value').isin(['1']).any()
True
but:
>>> 1 in getattr(df_data, 'value')
True
>>> '1' in getattr(df_data, 'value')
False
So fun :D
df = pandas.DataFrame({'g':[1]}, index=['isStop'])
#df.loc['g']
if 'g' in df.index:
print("find g")
if 'isStop' in df.index:
print("find a")
I like to use:
if 'value' in df.index.get_level_values(0):
print(True)
get_level_values method is good because it allows you to get the value in the indexes no matter if your index is simple or composite.
Use 0 (zero) if you have a single index in your dataframe [or you want to check the first index in multiple index levels]. Use 1 for the second index, and so on...