Why does transposing a DataFrame with strings and timedeltas convert the dtype?

A dataframe should be thought of in columns. Each column must have a single data type. When you transpose, you are changing which cells are now associated with each other in the new columns. Prior to transpose, you had an string column and a timedelta column. After transpose, each column had a string and a timedelta. Pandas has to decide how to cast the new columns. It decided to go with timedelta. It is my opinion that this is a goofy choice.

You can change this behavior by changing the dtype on a newly constructed dataframe.

pd.DataFrame(df.values.T, df.columns, df.index, dtype=object)

                     0                  1                   2
id               00115              01222               32333
val  365 days 05:49:12  426 days 02:47:24  5174 days 06:27:00