inja - 8 days ago 4

Python Question

I know following error

`ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().`

However, I am trying to create a basic function and return a new column with

`df[busy']`

`1`

`0`

`def hour_bus(df):`

if df[(df['hour'] >= '14:00:00') & (df['hour'] <= '23:00:00')&\

(df['week_day'] != 'Saturday') & (df['week_day'] != 'Sunday')]:

return df['busy'] == 1

else:

return df['busy'] == 0

I can execute the function, but when I call it with the dataframe, I get the error mentioned above. I followed the following thread and another thread to create that function. I used

`&`

`and`

`if`

Anyhow,when I do the following, I am getting my desired output.

`df['busy'] = np.where((df['hour'] >= '14:00:00') & (df['hour'] <= '23:00:00') & \`

(df['week_day'] != 'Saturday') & (df['week_day'] != 'Sunday'),'1','0')

Any ideas on what mistake am I making in my

`hour_bus`

Answer

The

```
(df['hour'] >= '14:00:00') & (df['hour'] <= '23:00:00')& (df['week_day'] != 'Saturday') & (df['week_day'] != 'Sunday')
```

gives a boolean array, and when you index your `df`

with that you'll get a (probably) smaller part of your `df`

.

Just to illustrate what I mean:

```
import pandas as pd
df = pd.DataFrame({'a': [1,2,3,4]})
mask = df['a'] > 2
print(mask)
# 0 False
# 1 False
# 2 True
# 3 True
# Name: a, dtype: bool
indexed_df = df[mask]
print(indexed_df)
# a
# 2 3
# 3 4
```

However it's still a `DataFrame`

so it's ambiguous to use it as expression that requires a truth value (in your case an `if`

).

```
bool(indexed_df)
# ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
```

You could use the `np.where`

you used - or equivalently:

```
def hour_bus(df):
mask = (df['hour'] >= '14:00:00') & (df['hour'] <= '23:00:00')& (df['week_day'] != 'Saturday') & (df['week_day'] != 'Sunday')
res = df['busy'] == 0
res[mask] = (df['busy'] == 1)[mask] # replace the values where the mask is True
return res
```

However the `np.where`

will be the better solution (it's more readable and probably faster).

Source (Stackoverflow)