| @@ -6896,21 +6896,21 @@ def count(self, axis=0, level=None, numeric_only=False): |
|
|
| 6896 |
6896 |
Constructing DataFrame from a dictionary: |
| 6897 |
6897 |
|
| 6898 |
6898 |
>>> df = pd.DataFrame({"Person": |
| 6899 |
|
- ... ["John", "Myla", None, "John", "Myla"], |
|
6899 |
+ ... ["John", "Myla", "Lewis", "John", "Myla"], |
| 6900 |
6900 |
... "Age": [24., np.nan, 21., 33, 26], |
| 6901 |
6901 |
... "Single": [False, True, True, True, False]}) |
| 6902 |
6902 |
>>> df |
| 6903 |
6903 |
Person Age Single |
| 6904 |
6904 |
0 John 24.0 False |
| 6905 |
6905 |
1 Myla NaN True |
| 6906 |
|
- 2 None 21.0 True |
|
6906 |
+ 2 Lewis 21.0 True |
| 6907 |
6907 |
3 John 33.0 True |
| 6908 |
6908 |
4 Myla 26.0 False |
| 6909 |
6909 |
|
| 6910 |
6910 |
Notice the uncounted NA values: |
| 6911 |
6911 |
|
| 6912 |
6912 |
>>> df.count() |
| 6913 |
|
- Person 4 |
|
6913 |
+ Person 5 |
| 6914 |
6914 |
Age 4 |
| 6915 |
6915 |
Single 5 |
| 6916 |
6916 |
dtype: int64 |
| @@ -6920,7 +6920,7 @@ def count(self, axis=0, level=None, numeric_only=False): |
|
|
| 6920 |
6920 |
>>> df.count(axis='columns') |
| 6921 |
6921 |
0 3 |
| 6922 |
6922 |
1 2 |
| 6923 |
|
- 2 2 |
|
6923 |
+ 2 3 |
| 6924 |
6924 |
3 3 |
| 6925 |
6925 |
4 3 |
| 6926 |
6926 |
dtype: int64 |
| @@ -6931,7 +6931,9 @@ def count(self, axis=0, level=None, numeric_only=False): |
|
|
| 6931 |
6931 |
Age |
| 6932 |
6932 |
Person |
| 6933 |
6933 |
John 2 |
|
6934 |
+ Lewis 1 |
| 6934 |
6935 |
Myla 1 |
|
6936 |
+ |
| 6935 |
6937 |
""" |
| 6936 |
6938 |
axis = self._get_axis_number(axis) |
| 6937 |
6939 |
if level is not None: |