Python Pandas dataframe find missing values

Question

I'm trying to find missing values and then drop off missing values. Tried looking for the data online but can't seem to find the answer.

Extracted Dataframe:

In the df, for 1981 and 1982, it should be '-', i.e. missing values. I would like to find the missing values then drop off the missing values.

Exported Dataframe using isnull:

I used df.isnull() but in 1981 and 1982, it's detected as 'False' which means there's data. But it should be '-', therefore considered as missing values.

I had pasted my code below. What am I missing out?

import pandas as pd

mydf = pd.read_excel('abc.xlsx', sep='\t')

df1 = mydf.set_index('Variables')
df = df1[0:10]
print(df)
print(df.isnull())

Answer 1

The question has two points: finding which columns have missing values and drop those values.

To find the missing values on a dataframe df

missing = df.isnull().sum()
print(missing)

To drop those missing values, apart from @jezrael's consideration, if that doesn't help, I suggest you to use dropna:

Drop the rows where all elements are missing.

df.dropna(how='all')

Drop the columns where at least one element is missing.

df.dropna(axis='columns')