diff --git a/README.md b/README.md index 890afb1..736cd2c 100644 --- a/README.md +++ b/README.md @@ -3185,7 +3185,7 @@ Name: a, dtype: int64 ``` ```python - = .head/describe/copy/sort_values() # Also .unique/value_counts/round/dropna(). + = .head/describe/sort_values() # Also .unique/value_counts/round/dropna(). = .str.strip/lower/contains/replace() # Also split().str[] and split().explode(). = .dt.year/month/day/hour # Use pd.to_datetime() to get S of dates. ``` @@ -3193,6 +3193,7 @@ Name: a, dtype: int64 ```python .plot.line/area/bar/pie/hist() # Generates a plot. `plt.show()` displays it. ``` +* **Also: `'pd.cut(, bins=)'`, `'.quantile()'`.** * **Indexing objects can't be tuples because `'obj[x, y]'` is converted to `'obj[(x, y)]'`.** * **Pandas uses NumPy types like `'np.int64'`. Series is converted to `'float64'` if we assign np.nan to any item. Use `'.astype()'` to get converted Series.** * **Series will silently overflow if we run `'pd.Series([100], dtype="int8") + 100'`!** @@ -3222,7 +3223,6 @@ Name: a, dtype: int64 | | y 2.0 | y 2.0 | y 2.0 | +--------------+-------------+-------------+---------------+ ``` -* **Methods sort_values(), dropna(), ffill(), interpolate() and fillna() accept `'inplace=True'`.** * **Agg() and transform() pass a Series to a function if it raises Type/Val/AttrError on a scalar.** * **Last result has a multi-index. Use `'[key_1, key_2]'` to get its values.** diff --git a/index.html b/index.html index 3da7b50..5ff18a3 100644 --- a/index.html +++ b/index.html @@ -2594,13 +2594,14 @@ Name: a, dtype: int64
<S>  = <S> > <el/S>                            # Returns S of bools. For logic use &, |, ~.
 <S>  = <S> + <el/S>                            # Items with non-matching keys get value NaN.
 
-
<S>  = <S>.head/describe/copy/sort_values()    # Also <S>.unique/value_counts/round/dropna().
+
<S>  = <S>.head/describe/sort_values()         # Also <S>.unique/value_counts/round/dropna().
 <S>  = <S>.str.strip/lower/contains/replace()  # Also split().str[<int>] and split().explode().
 <S>  = <S>.dt.year/month/day/hour              # Use pd.to_datetime(<S>) to get S of dates.
 
<S>.plot.line/area/bar/pie/hist()              # Generates a plot. `plt.show()` displays it.
 
    +
  • Also: 'pd.cut(<S>, bins=<int/coll>)', '<S>.quantile(<float/coll>)'.
  • Indexing objects can't be tuples because 'obj[x, y]' is converted to 'obj[(x, y)]'.
  • Pandas uses NumPy types like 'np.int64'. Series is converted to 'float64' if we assign np.nan to any item. Use '<S>.astype(<str/type>)' to get converted Series.
  • Series will silently overflow if we run 'pd.Series([100], dtype="int8") + 100'!
  • @@ -2627,7 +2628,6 @@ Name: a, dtype: int64
    -
  • Methods sort_values(), dropna(), ffill(), interpolate() and fillna() accept 'inplace=True'.
  • Agg() and transform() pass a Series to a function if it raises Type/Val/AttrError on a scalar.
  • Last result has a multi-index. Use '<S>[key_1, key_2]' to get its values.