KeyError when dropping rows from Pandas dataframe

Question

I'm trying to drop some rows from a Pandas dataframe because they'd be considered outliers in data. I'm getting a KeyError when trying to drop some rows using the method my professor taught me.

gdp_2019_outliers = np.where(df_gdp['2019'] > 6)
df_gdp.drop(gdp_2019_outliers[0], inplace=True)
gdp_2019_outliers_neg = np.where(df_gdp['2019'] < -3)
df_gdp.drop(gdp_2019_outliers_neg[0], inplace=True) # stacktrace points here as the cause

gdp_2020_outliers = np.where(df_gdp['2020'] > 3)
df_gdp.drop(gdp_2020_outliers[0], inplace=True)
gdp_2020_outliers_neg = np.where(df_gdp['2020'] < -15)
df_gdp.drop(gdp_2020_outliers_neg[0], inplace=True)

Answer 1

When you call drop<\/code> , you need to pass it row indexes or column names. You can pass it a mask, which is essentially what you're doing.

gdp_2019_outliers = np.where(df_gdp['2019'] > 6)
df_gdp.drop(gdp_2019_outliers[0], inplace=True)
gdp_2019_outliers_neg = np.where(df_gdp['2019'] < -3)
# Use this line instead:
df_gdp = df_gdp[~gdp_2019_outliers_neg[0]]


gdp_2020_outliers = np.where(df_gdp['2020'] > 3)
df_gdp.drop(gdp_2020_outliers[0], inplace=True)
gdp_2020_outliers_neg = np.where(df_gdp['2020'] < -15)
# Use this line instead as well:
df_gdp = [~gdp_2020_outliers_neg[0]]

Answer 2

Let's create the source DataFrame as:

   2019  2020
0     5     2
1     6     7
2     7   -15
3     8     8
4    -4     5
5    -3   -18
6    -2     7
7    -5    -3