add zero_is_nan

pixelsoup42 · Oct 1, 2023 · c450242 · c450242
1 parent f074274
commit c450242
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Showing 2 changed files with 20 additions and 18 deletions.
diff --git a/src/cardano_account_pandas_dumper/__main__.py b/src/cardano_account_pandas_dumper/__main__.py
@@ -6,7 +6,6 @@
 from json import JSONDecodeError
 
 import jstyleson
-import numpy as np
 import pandas as pd
 from blockfrost import ApiError, BlockFrostApi
 from openpyxl.cell.cell import ILLEGAL_CHARACTERS_RE
@@ -199,7 +198,8 @@ def main():
                 transactions,
                 detail_level=args.detail_level,
                 with_rewards=not args.no_rewards,
-            ).replace(np.float64(0), pd.NA).to_csv(args.csv_output, index=False)
+                zero_is_nan=True,
+            ).to_csv(args.csv_output, index=False)
         except OSError as exception:
             warnings.warn(f"Failed to write CSV file: {exception}")
     if args.xlsx_output:
@@ -208,13 +208,14 @@ def main():
                 transactions,
                 detail_level=args.detail_level,
                 with_rewards=not args.no_rewards,
+                zero_is_nan=True,
                 text_cleaner=lambda x: ILLEGAL_CHARACTERS_RE.sub(
                     lambda y: "".join(
                         ["\\x0" + hex(ord(y.group(0))).removeprefix("0x")]
                     ),
                     x,
                 ),
-            ).replace(np.float64(0), pd.NA).reset_index(drop=True).to_excel(
+            ).reset_index(drop=True).to_excel(
                 args.xlsx_output,
                 index=True,
                 sheet_name=f"Transactions to block {args.to_block}",

diff --git a/src/cardano_account_pandas_dumper/cardano_account_pandas_dumper.py b/src/cardano_account_pandas_dumper/cardano_account_pandas_dumper.py
@@ -444,38 +444,32 @@ def make_balance_frame(self, transactions: pd.Series, detail_level: int):
             np.float_power(10, np.negative(self.asset_decimals[c[0]]))
             for c in balance.columns
         ]
-
         return balance
 
     def make_transaction_frame(
         self,
         transactions: pd.Series,
         detail_level: int,
+        zero_is_nan: bool,
         with_rewards: bool,
-        with_tx_hash: bool = True,
-        with_tx_message: bool = True,
         with_total: bool = True,
         text_cleaner: Callable = lambda x: x,
     ) -> pd.DataFrame:
         """Build a transaction spreadsheet."""
 
         columns = [transactions.rename("timestamp").map(self._extract_timestamp)]
-        total: List[Any] = [columns[0].max() + self.TRANSACTION_OFFSET]
-        if with_tx_hash:
-            columns.append(transactions.rename("hash").map(lambda x: x.hash))
-            total.append("" if (with_tx_message or with_rewards) else "Total")
+        columns.append(transactions.rename("hash").map(lambda x: x.hash))
         if with_rewards:
             columns.append(
-                transactions.rename("reward").map(lambda x: bool(x.reward_amount))
-            )
-            total.append("" if with_tx_message else "Total")
-        if with_tx_message:
-            columns.append(
-                transactions.rename("message").map(
-                    lambda x: text_cleaner(self._format_message(x))
+                transactions.rename("reward").map(
+                    lambda x: "True" if x.reward_amount else "False"
                 )
             )
-            total.append("Total")
+        columns.append(
+            transactions.rename("message").map(
+                lambda x: text_cleaner(self._format_message(x))
+            )
+        )
         balance = self.make_balance_frame(transactions, detail_level)
         if not self.raw_values:
             balance.columns = pd.MultiIndex.from_tuples(
@@ -493,9 +487,16 @@ def make_transaction_frame(
         frame.sort_values(by=frame.columns[0], inplace=True)
         # Add total line at the bottom
         if with_total:
+            total = (
+                [columns[0].max() + self.TRANSACTION_OFFSET, ""]
+                + ([""] if with_rewards else [])
+                + ["Total"]
+            )
             for column in balance.columns:
                 total.append(balance[column].sum())
             frame = pd.concat(
                 [frame, pd.DataFrame(data=[total], columns=frame.columns)]
             )
+        if zero_is_nan:
+            frame.replace(np.float64(0), pd.NA, inplace=True)
         return frame