Reputation: 377
I have a dataframe, something like:
| | a | b |
|---|---|------------------|
| 0 | a | {'d': 1, 'e': 2} |
| 1 | b | {'d': 3, 'e': 4} |
| 2 | c | NaN |
| 3 | d | {'f': 5} |
How can make something like this:
| | a | b | d | e | f |
|---|---|------------------|---|---|---|
| 0 | a | {'d': 1, 'e': 2} | 1 | 2 |nan|
| 1 | b | {'d': 3, 'e': 4} | 3 | 4 |nan|
| 2 | c | NaN |nan|nan|nan|
| 3 | d | {'f': 5} |nan|nan| 5 |
I tried doing this Split / Explode a column of dictionaries into separate columns with pandas but due to null values present, it is throwing an error.
'float' object has no attribute 'items'
Upvotes: 0
Views: 913
Reputation: 16866
Replace NaN with None and then proceed
df = pd.DataFrame({'a':['a','b','c','d'],
'b':[{'d': 1, 'e': 2},
{'d': 3, 'e': 4},
np.nan,
{'f': 5}]
})
df = df.where(pd.notnull(df), None)
pd.concat([df, df['b'].apply(pd.Series)], axis=1)
Output:
a b d e f
0 a {'d': 1, 'e': 2} 1.0 2.0 NaN
1 b {'d': 3, 'e': 4} 3.0 4.0 NaN
2 c None NaN NaN NaN
3 d {'f': 5} NaN NaN 5.0
Upvotes: 0
Reputation: 15872
You can try the following:
>>> df
a b
0 a {'d': 1, 'e': 2}
1 b {'d': 3, 'e': 4}
2 c NaN
3 d {'f': 5}
>>> df.join(pd.DataFrame.from_records(df['b'].mask(df.b.isna(), {}).tolist()))
a b d e f
0 a {'d': 1, 'e': 2} 1.0 2.0 NaN
1 b {'d': 3, 'e': 4} 3.0 4.0 NaN
2 c NaN NaN NaN NaN
3 d {'f': 5} NaN NaN 5.0
Upvotes: 1