extract values from nested dictionary in pandas dataframe column

Question

I have pandas column, one sample value looks like this

 colName1 {'key1': {'key2': {'ke3': {'label': '3 minutes, 16 seconds'}}, 'simpleText': '3:16'}, 'style': 'DEFAULT'}

tried this but din't work.

df1['XYZ'] = df1['colName1'].apply(lambda x: x['key1']['key2']['simpleText'])

How can I retrieve the value of 'simpleText' which equals to 3:16

this nested json is the input for 1 dataframe with 1 row{'key1': {'key2': {'ke3': {'label': '3 minutes, 16 seconds'}}, 'simpleText': '3:16'}, 'style': 'DEFAULT'} — ista120
– ista120, Commented Aug 31, 2022 at 12:27

Ynjxsjmh · Accepted Answer · 2022-08-31 12:45:19Z

1

Let's try

df1['XYZ'] = df1['colName1'].str['key1'].str['simpleText']

answered Aug 31, 2022 at 12:45

Ynjxsjmh

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Vladimir Fokow · Accepted Answer · 2022-08-31 12:16:04Z

0

Use

x['key1']['simpleText']

key2 is redundant.

answered Aug 31, 2022 at 12:16

Vladimir Fokow

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4 Comments

ista120 Over a year ago

its giving me error TypeError: 'float' object is not subscriptable

Vladimir Fokow Over a year ago

Then probably some value of your colName1 is not in the format that you've provided here

ista120 Over a year ago

thecolName1 is showing object as datatype.

Vladimir Fokow Over a year ago

df['colName1'] contains many values (yes, objects)

Askari Zaidi · Accepted Answer · 2022-08-31 13:24:02Z

0

#Try this:

val['XYZ'] = val['key1']['simpleText']
print(val['XYZ'])

#output: 3:16

edited Aug 31, 2022 at 13:24

answered Aug 31, 2022 at 13:22

Askari Zaidi

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1 Comment

LinFelix Over a year ago

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