I would like to read several `yaml` files from a directory into pandas `dataframe` and concatenate them into one big DataFrame. The directory consists of **7470** files.

```
%%time
import pandas as pd
import glob

path = r'../input/cricsheet-a-retrosheet-for-cricket/all' # use your path
all_files = glob.glob(path + "/*.yaml")

li = []

for filename in all_files:
    with open(filename,'r') as fh:
        df = pd.json_normalize(yaml.load(fh.read()))
    li.append(df)

frame = pd.concat(li, axis=0, ignore_index=True)

```

```
CPU times: user 1h 15min 38s, sys: 8.8 s, total: 1h 15min 47s
Wall time: 1h 16min 44s

```

The runtime of the code exceeds more than an hour

Is there a way to read bulk `yaml` files into a pandas `dataframe` more efficiently?

[Sample Dataset Zipped](https://cricsheet.org/downloads/all.zip)

[Sample Dataset](https://www.kaggle.com/veeralakrishna/cricsheet-a-retrosheet-for-cricket)