I have a list. Mostly obituary related.

```
Leonard Wilson 1867 - 1936
Mark Jonson 1892 - 1961
Alex Jean Kinshaw 1951 - 1993
Elizabeth Mae Martin 1934 - 1998

```

The data needs to be analysed for a study and it needs to be arranged in 'csv' format, with a timeline(delimited by "," and using "-" for null values) starting from 1850 upto 2015.

```
Leonard Wilson,-,-,-,-,-,-,-,-,-,-,-,-,-,-,1867,1868,1869......1934,1935,1936,-,-,-,-,-,-,-,-,-,-,-,-
Mark Jonson,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,1892,1893,1894,1895,1896,1897......,1958,1959,1960,1961,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
....

# All years in the middle needs to be populated please

```

In the above data you can see that the years before the person was born is marked by '-' and also the years after death(till 2015) with the same. All the years in between, needs to be populated.

The python/pandas code needs to detect the year of start and end, and

1. fill the before null values
2. in-middle years and
3. ending null values

Is there anyway this can be achieved, as I have a data of over 30k rows?