Hello there,

I am quite new to dask and have a question on using apply on a dask dataframe. I found the following code does not give the expected result:

```
import pandas as pd
import dask.dataframe as dd
numbers = range(0,4)
ddf = dd.from_pandas(pd.DataFrame({'x': [0,1,2,3]}), npartitions=1)
for i in numbers:
ddf[str(i)] = ddf.x.apply(lambda x: x if x == i else 99, meta=(str(i), 'int64'))
```

This gives as answer on compute() this:

```
x 0 1 2 3
0 0 99 99 99 99
1 1 99 99 99 99
2 2 99 99 99 99
3 3 3 3 3 3
```

However, if I do this outside of a loop, like so:

```
ddf[str(0)] = ddf.x.apply(lambda x: x if x == numbers[0] else 99, meta=(str(0), 'int64'))
ddf[str(1)] = ddf.x.apply(lambda x: x if x == numbers[1] else 99, meta=(str(1), 'int64'))
ddf[str(2)] = ddf.x.apply(lambda x: x if x == numbers[2] else 99, meta=(str(2), 'int64'))
ddf[str(3)] = ddf.x.apply(lambda x: x if x == numbers[3] else 99, meta=(str(3), 'int64'))
```

This gives the answer I would expect when doing ddf.compute():

```
x 0 1 2 3
0 0 0 99 99 99
1 1 99 1 99 99
2 2 99 99 2 99
3 3 99 99 99 3
```

Interestingly, if I do the same using a pure pandas dataframe, I do not have this issues:

```
pdf = pd.DataFrame({'x': [0,1,2,3]})
for i in range(0,4):
pdf[str(i)] = pdf.x.apply(lambda x: x if x == i else 99)
```

gives the expected result and pdf at the end is

```
x 0 1 2 3
0 0 0 99 99 99
1 1 99 1 99 99
2 2 99 99 2 99
3 3 99 99 99 3
```

Can anyone explain to me what is going on here? To be clear, this example is a minimal example I made, the actual situation in my code is more complex so I can not avoid using apply and simply use column assignment.

I feel that I am missing something fundamental here about how dask does lazy evaluations or something similar. Any help/explanations would be very much appreciated indeed!