Clean up

Author: Jaspvr

pandas/io/formats/csvs.py

@@ -19,6 +19,7 @@
 )
 
 import numpy as np
+import json
 
 from pandas._libs import writers as libwriters
 from pandas._typing import SequenceNotStr
@@ -100,12 +101,7 @@ def __init__(
         self.cols = self._initialize_columns(cols)
         self.chunksize = self._initialize_chunksize(chunksize)
 
-        print("output preserve var: ", self.preserve_complex)
         if self.preserve_complex:
-            print("here1")
-            import json
-            import numpy as np
-
             for col in self.obj.columns:
                 if self.obj[col].dtype == "O":
                     first_val = self.obj[col].iloc[0]

pandas/io/parsers/readers.py

@@ -863,22 +863,19 @@ def read_csv(
 
 def _restore_complex_arrays(df: DataFrame) -> None:
     """
-    Loop over each column of df, check if it contains bracketed JSON strings
-    like "[0.1, 0.2, 0.3]", and parse them back into NumPy arrays.
+    Converted bracketed JSON strings in df back to NumPy arrays.
+    eg. "[0.1, 0.2, 0.3]" --> parse into NumPy array.
     """
     def looks_like_json_array(x: str) -> bool:
         return x.startswith("[") and x.endswith("]")
 
     for col in df.columns:
-        # Only parse object columns
         if df[col].dtype == "object":
-            # skip null
             nonnull = df[col].dropna()
             if (
                 len(nonnull) > 0
                 and nonnull.apply(lambda x: isinstance(x, str) and looks_like_json_array(x)).all()
             ):
-                # parse
                 df[col] = df[col].apply(lambda x: np.array(json.loads(x)) if pd.notnull(x) else x)