How to deal with Mongodb Null values

Question

I have some sample data here. What the code is supposed to do is to remove any words inside. However, occasionally mongo throws in a Null value or an empty string.

import pandas as pd
import numpy as np

df = pd.DataFrame(np.array([[1],[4],[25],['asd123'],['asdf1']]),
                   columns=['account'])


df["account"] = (
            df["account"]
            .fillna((-1), inplace=False)).astype("str").str.replace(r"[^0-9]", "", regex=True).astype('int64')

I have tried replacing it with an integer below, but Python keeps throwing me an error ValueError: invalid literal for int() with base 10: ''

import pandas as pd
import numpy as np

df = pd.DataFrame(np.array([[1],[4],[25],['asd123'],['']]),
                   columns=['account'])
np.where(df.applymap(lambda x: x == ''))
df.replace('', '1')


df["account"] = (
            df["account"]
            .fillna((-1), inplace=False)).astype("str").str.replace(r"[^0-9]", "", regex=True).astype('int64')
df

I have also tried and it doesnt work too:

import pandas as pd
import numpy as np

df = pd.DataFrame(np.array([[1],[4],[25],['asd123'],['']]),
                   columns=['agent_account'])
np.where(df.applymap(lambda x: x == ''))
df.replace('','abc1',regex = True)

Any help is appreciated. Thanks!

Asked By: jonathan lim

||

Source

Answer 1

Because you’re trying to convert "" to an integer. Just delete the "" when getting the data, with this line df.drop(df[df.account == ""].index, inplace=True)

This would be your modified code

import pandas as pd
import numpy as np

df = pd.DataFrame(np.array([[1],[4],[25],['asd123'],['']]),
                   columns=['account'])
np.where(df.applymap(lambda x: x == ''))
df.drop(df[df.account == ""].index, inplace=True)


df["account"] = (
            df["account"]
            .fillna((-1), inplace=False)).astype("str").str.replace(r"[^0-9]", "", regex=True).astype('int64')

Answered By: Rodrigo Guzman

How to deal with Mongodb Null values

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