Dropping rows with missing values

[NewBeie]

Hi,

I have this code below, I'm trying to drop rows with missing values, and I'm trying to use DataFrame.dropna(), But when I test below the rows were not dropped, please help. I have attached my data set as well.

import pandas as pd

recent_grads = pd.read_csv('recent-grads.csv')
print(recent_grads['Low_wage_jobs'].value_counts().sort_index().head())
print(len(recent_grads))

recent_grads = recent_grads.dropna()

print(recent_grads['Low_wage_jobs'].value_counts().sort_index().head())
print(len(recent_grads))

[scidam]

Are you sure that your data frame elements are nans? The following example shows that everything works fine:

>>> df = pd.DataFrame({'a': [pd.np.nan, 3, 4], 'b': [4, pd.np.nan, 8]})
>>> df

Output:
     a    b
0  NaN  4.0
1  3.0  NaN
2  4.0  8.0

>>> df.dropna()

Output:
     a    b
2  4.0  8.0

[NewBeie]

Are you sure that your data frame elements are nans? The following example shows that everything works fine:

>>> df = pd.DataFrame({'a': [pd.np.nan, 3, 4], 'b': [4, pd.np.nan, 8]})
>>> df

Output:
     a    b
0  NaN  4.0
1  3.0  NaN
2  4.0  8.0

>>> df.dropna()

Output:
     a    b
2  4.0  8.0

Thank you for this, I see where I made a mistake