数据预处理是数据科学管道的重要组成部分，需要找出数据中的各种不规则性，操作您的特征等。Pandas 是我们...
movies_df["rating_category"] = movies_df["rating"].apply(rating_function) movies_df.head(2) .apply()方法将rating列中的每个值都通过rating_function传递,然后返回一个新的Series。然后将此系列分配给一个新的列,称为“ rating_category”。您还可以使用匿名函数。此lambda函数可达到与rating_function相同的...
df = pd.DataFrame(np.random.random(4)**10, columns=['random']) #方法1: Rounding df.round(4) #方法2: Use apply to change format df.apply(lambda x: '%.4f' % x, axis=1) # or df.applymap(lambda x: '%.4f' % x) #方法3: Use set_option pd.set_option('display.float_format...
In [178]: df2 = df.copy() In [179]: df.apply(lambda x, y: x.where(x>0,y), y=df['A']) Out[179]: A B C D 2000-01-01 -2.104139 -2.104139 0.485855 0.245166 2000-01-02 -0.352480 0.390389 -0.352480 1.655824 2000-01-03 -0.864883 0.299674 -0.864883 0.281059 2000-01-04 0.846958...
[:-1] ...: return df ...: In [4]: timeseries = [ ...: make_timeseries(freq="1min", seed=i).rename(columns=lambda x: f"{x}_{i}") ...: for i in range(10) ...: ] ...: In [5]: ts_wide = pd.concat(timeseries, axis=1) In [6]: ts_wide.head() Out[6]:...
raise KeyError(key) from err KeyError: 'bearing' During handling of the above exception, another exception occurred: Traceback (most recent call last): File "transitflow.py", line 406, in <module> df['bearing'] = df.apply(lambda row: calc_bearing_between_points(row['start_lat'], row[...
(self, key)1189 maybe_callable = com.apply_if_callable(key, self.obj)1190 maybe_callable = self._check_deprecated_callable_usage(key, maybe_callable)-> 1191 return self._getitem_axis(maybe_callable, axis=axis)File ~/work/pandas/pandas/pandas/core/indexing.py:1411, in _LocIndexer._getitem...
File ~/work/pandas/pandas/pandas/core/indexes/base.py:3812,inIndex.get_loc(self, key)3807ifisinstance(casted_key,slice)or(3808isinstance(casted_key, abc.Iterable)3809andany(isinstance(x,slice)forxincasted_key)3810):3811raiseInvalidIndexError(key) ...
df['square']=df.select_dtypes(include='number').apply(lambda x:x**2,axis=0)# 或者更简洁地 df['square']=df[['col1','col2']].pow(2) 1. 2. 3. 4. 5. 小贴士:尽量利用Pandas提供的内置函数来进行数据处理,这样不仅代码更简洁,执行效率也会更高。避免使用显式的循环遍历每一行或每一列,...
importpandasaspddf=pd.DataFrame()df['test1']=df.apply(lambdax:x['test']+"_",axis=1) Issue Description I was expecting to seeKeyError 'test'as an error, but I get an error as follows: --- ValueError Traceback (most recent call last) Cell In[4], line 1 ---> 1 df['test1'] ...