temp files

Author: eicchen

test.py

@@ -0,0 +1,60 @@
+# mypy: ignore-errors
+import numpy as np
+
+import pandas as pd
+import pandas._testing as tm
+
+
+def print_side_by_side(df1, df2):
+    # Convert to string and split into lines
+    df1_str = df1.to_string(index=False).split("\n")
+    df2_str = df2.to_string(index=False).split("\n")
+
+    # Pad lines to the same length for alignment
+    max_len_1 = max(len(line) for line in df1_str)
+    padded_df1 = [line.ljust(max_len_1) for line in df1_str]
+
+    # Print side-by-side
+    print("Result".ljust(max_len_1) + "  |  Expected")
+    for line1, line2 in zip(padded_df1, df2_str):
+        print(f"{line1}  |  {line2}")
+
+
+# data = np.arange(50).reshape(10, 5)
+# fill_val = 5
+
+# data = pd.array(np.random.choice([True, False], size=(10, 5)), dtype="boolean")
+# fill_val = True
+
+data = np.arange(50).reshape(10, 5)
+# data_mult = pd.array([i for i in range(10)], dtype=tm.SIGNED_INT_NUMPY_DTYPES[0])
+data_mult = pd.array(list(range(10)), dtype=tm.SIGNED_INT_EA_DTYPES[0])
+fill_val = 5
+
+# print(tm.ALL_INT_DTYPES)
+# print(tm.SIGNED_INT_EA_DTYPES)
+# tm.SIGNED_INT_NUMPY_DTYPES[0]
+print(type(data_mult))
+
+# TODO masking not working with EA with dim > 1
+# NOTE currently trying to get EA testing set up
+
+columns = list("ABCDE")
+df_base = pd.DataFrame(data, columns=columns)
+for i in range(5):
+    df_base.iat[i, i] = np.nan
+    df_base.iat[i + 1, i] = np.nan
+    df_base.iat[i + 4, i] = np.nan
+
+mask = df_base.isna().values
+
+data_mult_re = data_mult.reshape(10, 1)
+mask = mask[:, :-1] & data_mult_re
+
+df_result = df_base.mul(data_mult, axis=0, fill_value=fill_val)
+print(df_result)
+# df_expected = (df_base.fillna(fill_val).mul(data_mult.fillna(fill_val),
+# axis=0)).mask(mask, np.nan)
+
+# print_side_by_side(df_result, df_expected)
+# # tm.assert_frame_equal(df_result, df_expected)

test2.py

@@ -0,0 +1,52 @@
+# mypy: ignore-errors
+import numpy as np
+
+import pandas as pd
+
+
+def print_side_by_side(df1, df2):
+    # Convert to string and split into lines
+    df1_str = df1.to_string(index=False).split("\n")
+    df2_str = df2.to_string(index=False).split("\n")
+
+    # Pad lines to the same length for alignment
+    max_len_1 = max(len(line) for line in df1_str)
+    padded_df1 = [line.ljust(max_len_1) for line in df1_str]
+
+    # Print side-by-side
+    print("Result".ljust(max_len_1) + "  |  Expected")
+    for line1, line2 in zip(padded_df1, df2_str):
+        print(f"{line1}  |  {line2}")
+
+
+data = np.arange(50).reshape(10, 5)
+fill_val = 5
+
+# data = pd.array(np.random.choice([True, False], size=(10, 5)), dtype="boolean")
+# fill_val = True
+
+# data = pd.array([i for i in range(50)], dtype="int")
+# fill_val = 5
+
+print(type(data))
+
+columns = list("ABCDE")
+df = pd.DataFrame(data, columns=columns)
+for i in range(5):
+    df.iat[i, i] = np.nan
+    df.iat[i + 1, i] = np.nan
+    df.iat[i + 4, i] = np.nan
+
+df_base = df.iloc[:, :-1]
+df_mult = df.iloc[:, [-1]]
+
+mask = df.isna().values
+mask = mask[:, :-1] & mask[:, [-1]]
+
+df_result = df_base.mul(df_mult, axis=0, fill_value=fill_val)
+df_expected = (df_base.fillna(fill_val).mul(df_mult.fillna(fill_val), axis=0)).mask(
+    mask, np.nan
+)
+
+print_side_by_side(df_result, df_expected)
+# tm.assert_frame_equal(df_result, df_expected)