diff --git a/parrot/data_stats.py b/parrot/data_stats.py
deleted file mode 100644
index 1530a25..0000000
--- a/parrot/data_stats.py
+++ /dev/null
@@ -1,96 +0,0 @@
-import xarray as xr
-import matplotlib.pyplot as plt
-import numpy as np
-import yaml
-import pathlib
-import io
-import base64
-
-
-def get_stats(data):
-    return {
-        "min": float(np.nanmin(data)),
-        "max": float(np.nanmax(data)),
-        "mean": float(np.nanmean(data)),
-        "std": float(np.nanstd(data)),
-    }
-
-
-class DataStats(object):
-    def __init__(self, output_dir):
-        if isinstance(output_dir, pathlib.Path):
-            self.output_dir = output_dir
-        else:
-            self.output_dir = pathlib.Path(output_dir)
-        self.info = None
-        self.histogram = None
-
-    def gen_data_stats(self, filename, var, nbins=100):
-        ds = xr.open_dataset(filename)
-
-        vstats = get_stats(ds[var].values)
-        bins = np.linspace(vstats["min"], vstats["max"], num=nbins + 1)
-
-        ntime, nlon, nlat = ds[var].shape
-        mratio = np.zeros(ntime)
-        hist = np.zeros((ntime, nbins))
-        for i in range(ntime):
-            a = ds[var].values[i]
-            idx = ~np.isnan(a)
-            mratio[i] = idx.sum()
-            a = np.histogram(a[idx], bins=bins)[0]
-            hist[i] = a / max(a)
-
-        mratio = 1 - mratio / (nlon * nlat)
-
-        # TODO: It would be great to store the distribution graph in a database
-        if True:
-            plt.close()
-            plt.imshow(
-                hist,
-                aspect="auto",
-                origin="lower",
-                extent=[vstats["min"], vstats["max"], 0, ntime],
-                cmap="gist_ncar",
-            )
-            ax = plt.gca()
-            ax.grid(color="gray", linestyle="-.", linewidth=1)
-            plt.xlabel(var)
-            plt.ylabel("Timesteps")
-            # outfile = self.output_dir / "histogram.png"
-            # print(f"histogram: {outfile}")
-            # plt.savefig(outfile.as_posix(), dpi=50)
-            # store as base64
-            # Save the plot to a BytesIO object
-            buffer = io.BytesIO()
-            plt.savefig(buffer, format="png")
-            buffer.seek(0)
-
-            # Encode the BytesIO object as base64
-            base64_encoded_plot = base64.b64encode(buffer.read()).decode("utf-8")
-            # print(f"{base64_encoded_plot}")
-            self.histogram = base64_encoded_plot
-            # close plot
-            plt.close()
-
-        # The following information should be stored in a database
-        attrs = {}
-        orig_attrs = dict(ds.attrs)
-        for key in orig_attrs:
-            value = orig_attrs[key]
-            if isinstance(value, str):
-                attrs[key] = value
-
-        self.info = {}
-        self.info["Attrs"] = attrs
-        self.info["Dims"] = dict(ds.dims)
-        self.info["Vars"] = list(dict(ds.variables).keys())
-        self.info["Vstats"] = vstats
-        self.info["Mstats"] = get_stats(mratio)
-        # print(self.info)
-
-    def write_json(self):
-        outfile = self.output_dir / "info.txt"
-        with open(outfile.as_posix(), "w") as f:
-            yaml.dump(self.info, f)
-        return outfile