I would like to select rows using condition on columns like "sex" = "male". I normally used loc function on DataFrame.
import pandas as pd
dane = pd.read_csv('insurance.csv')
dane.info()
the result is:
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 1338 entries, 0 to 1337
Data columns (total 7 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 age 1338 non-null int64
1 sex 1338 non-null object
2 bmi 1338 non-null float64
3 children 1338 non-null int64
4 smoker 1338 non-null object
5 region 1338 non-null object
6 charges 1338 non-null float64
dtypes: float64(2), int64(2), object(3)
memory usage: 73.3+ KB
a = dane.loc(dane["sex"] == "male")
And after this calling this cells i have this error
TypeError Traceback (most recent call last)
<ipython-input-9-18dd4823c7e4> in <module>()
----> 1 a = dane.loc(dane["sex"] == "male")
1 frames
/usr/local/lib/python3.7/dist-packages/pandas/core/generic.py in _get_axis_number(cls, axis)
544 def _get_axis_number(cls, axis: Axis) -> int:
545 try:
--> 546 return cls._AXIS_TO_AXIS_NUMBER[axis]
547 except KeyError:
548 raise ValueError(f"No axis named {axis} for object type {cls.__name__}")
TypeError: unhashable type: 'Series'
If i did example from the Internet everything is good:
boxes = {'Color': ['Green','Green','Green','Blue','Blue','Red','Red','Red'],
'Shape': ['Rectangle','Rectangle','Square','Rectangle','Square','Square','Square','Rectangle'],
'Price': [10,15,5,5,10,15,15,5]
}
df = pd.DataFrame(boxes, columns= ['Color','Shape','Price'])
df.info()
select_color = df.loc[df['Color'] == 'Green']
print (select_color)
The result is:
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 8 entries, 0 to 7
Data columns (total 3 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 Color 8 non-null object
1 Shape 8 non-null object
2 Price 8 non-null int64
dtypes: int64(1), object(2)
memory usage: 320.0+ bytes
Color Shape Price
0 Green Rectangle 10
1 Green Rectangle 15
2 Green Square 5
What is reason of problem with my situation. This is normall csv file, the same format of data etc.
