In [1]: import numba In [2]: def double_every_value_nonumba(x): return x * 2 In [3]: @numba.vectorize def double_every_value_withnumba(x): return x * 2 # 不带numba的自定义函数: 797 us In [4]: %timeit df["col1_doubled"] = df["a"].apply(double_every_value_nonumba) ...
df_filtered=df.query('column > 10')df.eval('new_column = column1 + column2',inplace=True) 使用sort_values进行自定义排序:按照一个或多个列进行排序,并指定自定义排序顺序。 df_sorted=df.sort_values(by=['column1','column2'],ascending=[True,False]) 使用to_datetime进行高效日期解析:将字符串...
# 参数对应 行,列,值 outws.cell(row=count,column=1,value=str(count))outws.cell(row=count,column=2,value=str("第"+str(tv__name)+"集"))outws.cell(row=count,column=3,value=str(uid.childNodes[0].data))outws.cell(row=count,column=4,value=str(content.childNodes[0].data))outws.cel...
# Iterate over the files in the current "root"forfile_entryinfiles:# create the relative path to the filefile_path = os.path.join(root, file_entry)print(file_path) 我们也可以使用root + os.sep() + file_entry来实现相同的效果,但这不如我们使用的连接路径的方法那样符合 Python 的风格。使用...
,#喜欢数'comment_num':str(row2_nums[3].get_text()),#评论数'level':level_mes,#等级'visit_num':str(row1_nums[3].get_text()),#访问数'score':str(row2_nums[0].get_text()),#积分'rank':str(row1_nums[2].get_text()),#排名}df_info=pd.DataFrame([info.values()],columns=info...
processed_files = []fordollar_iindollar_i_files:# Interpret file metadatafile_attribs = read_dollar_i(dollar_i[2])iffile_attribsisNone:continue# Invalid $I filefile_attribs['dollar_i_file'] = os.path.join('/$Recycle.bin', dollar_i[1][1:]) ...
5. Set and Replace values for an entire Pandas column / Series. Let’s now assume that we would like to modify the num_candidates figure for all observations in our DataFrame. That’s fairly easy to accomplish. survey_df['num_candidates'] = 25 ...
def check_missing_data(df):# check for any missing data in the df (display in descending order) return df.isnull().sum().sort_values(ascending=False)删除列中的字符串 有时候，会有新的字符或者其他奇怪的符号出现在字符串列中，这可以使用df[‘col_1’].replace很简单地把它们处理掉。def re...
import pandas as pdimport datetime as dt# Convert to datetime and get today's dateusers['Birthday'] = pd.to_datetime(users['Birthday'])today = dt.date.today()# For each row in the Birthday column, calculate year diff...
replace resample reset_index rfloordiv rmod rmul rolling round rpow rsub rtruediv sample searchsorted sem set_axis set_flags shape shift size skew slice_shift sort_index sort_values sparse squeeze std str sub subtract sum swapaxes swaplevel tail take to_clipboard to_csv to_dict to_excel to_...