我应该如何从 python 中的 dataframe 中删除 nan 值？

Question

I've got an excel file and I created lists from its columns. The problem is the rows of the columns is not equal. Therefore, I have multiple 'nan' values at ends of the lists. I tried to delete them with dropna() method but there are still the 'nan' values. Here is my code:

import pandas as pd

excel_name = r'file_name.xlsx'
df = pd.read_excel(excel_name, engine='openpyxl')
df.dropna()

clomun_1 = list(df['clomun1'])
clomun_2 = list(df['clomun2'])
clomun_3 = list(df['clomun3'])
print(clomun_1)
print(clomun_2)
print(clomun_3)

output:

clomun_1 = ['value1', 'value2', 'value3', 'value4', 'nan', 'nan', 'nan', 'nan']
clomun_2 = ['value1', 'value2', 'value3', 'value4', 'value5', 'value6', 'nan', 'nan']
clomun_3 = ['value1', 'value2', 'nan', 'nan', 'nan', 'nan', 'nan', 'nan']

I want to keep only values. I must delete "nan" elements.

Answer 1

Try this:

df = pd.read_excel(excel_name, engine='openpyxl', na_values=['nan']) #add na_values

clomun_1 = df['clomun1'].dropna().tolist()

print(clomun_1)

['value1', 'value2', 'value3', 'value4']

Answer 2

You can use a lambda function to achieve this.

clomun_1_new= [x for x in clomun_1 if x!='nan']

repeat the same for other two lists.