Merge pull request #78 from martinRenou/nat_support_from_df

Add NaT support in from_dataframe

examples/pandas.ipynb

@@ -30,6 +30,8 @@
     "                    'E': pd.Categorical([\"test\", \"train\", \"test\", \"train\"]),\n",
     "                    'F': 'foo'})\n",
     "\n",
+    "df2.loc[[0, 2], ['B']] = np.nan\n",
+    "\n",
     "sheet2 = from_dataframe(df2)\n",
     "sheet2"
    ]
@@ -61,7 +63,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.2"
+   "version": "3.6.7"
   }
  },
  "nbformat": 4,

ipysheet/pandas_loader.py

@@ -26,8 +26,10 @@ def _format_date(date):
 
 
 def _get_cell_value(arr):
+    import pandas as pd
+
     if (arr.dtype.kind == 'M'):
-        return [_format_date(date) for date in arr]
+        return [_format_date(date) if not pd.isna(date) else None for date in arr]
     else:
         return arr.tolist()
 

ipysheet/test_all.py

@@ -436,12 +436,14 @@ def test_from_dataframe():
         'S': pd.Categorical(["test", "train", "test", "train"]),
         'T': 'foo'})
 
+    df.loc[[0, 2], ['B']] = np.nan
+
     sheet = ipysheet.from_dataframe(df)
     assert len(sheet.cells) == 6
     assert sheet.column_headers == ['A', 'B', 'C', 'D', 'S', 'T']
     assert sheet.cells[0].value == [1., 1., 1., 1.]
     assert sheet.cells[0].type == 'numeric'
-    assert sheet.cells[1].value == ['2013/01/02', '2013/01/02', '2013/01/02', '2013/01/02']
+    assert sheet.cells[1].value == [None, '2013/01/02', None, '2013/01/02']
     assert sheet.cells[1].type == 'date'
     assert sheet.cells[2].value == [1., 1., 1., 1.]
     assert sheet.cells[2].type == 'numeric'
@@ -453,6 +455,25 @@ def test_from_dataframe():
     assert sheet.cells[5].type == 'text'
 
 
+def test_from_to_dataframe():
+    df = pd.DataFrame({
+        'A': 1.,
+        'B': pd.Timestamp('20130102'),
+        'C': pd.Series(1, index=list(range(4)), dtype='float32'),
+        'D': np.array([False, True, False, False], dtype='bool'),
+        'S': pd.Categorical(["test", "train", "test", "train"]),
+        'T': 'foo'})
+
+    df.loc[[0, 2], ['B']] = np.nan
+
+    sheet = ipysheet.from_dataframe(df)
+    df2 = ipysheet.to_dataframe(sheet)
+
+    a = np.array(df.values)
+    b = np.array(df2.values)
+    assert ((a == b) | (pd.isna(a) & pd.isna(b))).all()
+
+
 def test_to_array():
     sheet = ipysheet.sheet(rows=5, columns=4)
     ipysheet.cell(0, 0, value=True)