复制 In [116]: df = pd.DataFrame({"A": [1, 1, 2, 2], "B": [1, -1, 1, 2]}) In [117]: gb = df.groupby("A") In [118]: def replace(g): .....: mask = g < 0 .....: return g.where(~mask, g[~mask].mean()) .....: In [119]
fillna()方法允许我们用一个值替换空单元格: #Replace NULL values with the number 130 import pandas as pd df = pd.read_csv...要想只替换一列的空值,请指定DataFrame的列名。...('data.csv') df["Calories"].fillna(130, inplace = True) 用平均数、中位数或模式替换一个常见的替换空...
修复了使用非日期时间类型的 numpy 数组与pd.NaT进行(不)相等比较时返回标量而不是数组的回归问题 (GH 40722) 修复了DataFrame.where()在所有条件都为 True 的情况下未返回副本的回归问题 (GH 39595) 修复了当regex是多键字典时,DataFrame.replace()抛出IndexError的回归问题 (GH 39338) 修复了在object列中浮点...
# replace datetime with new date where select is true df.loc[(df['select'] == 1), ['date_time']] = df.loc[(df['select'] == 1), ['new_date']] print(df) # the second element of the date_time column is "NaT", but this is not the desired outcome. # the desired behaviour...
(Not a Number) #空值 None #缺失值 pd.NaT #时间格式的空值# 判断缺失值 isnull()/isna() #断Series或DataFrame中是否包含空值 notnull() #与isnull()结果互为取反 isin() #判断Series或DataFrame中是否包含某些值 dropna() #删除Series或DataFrame中的空值 fillna() #填充Series或DataFrame中的空值 ffill...
pandas.NaT 输入/输出 原文:pandas.pydata.org/docs/reference/io.html Pickling 平面文件 剪贴板 Excel JSON HTML XML Latex HDFStore: PyTables (HDF5) 警告 可以将DataFrame或Series的子类存储到 HDF5,但子类的类型在存储时会丢失。 Feather Parquet
最后,TimedeltaIndex与DatetimeIndex的组合允许进行某些保留 NaT 的组合操作: In [110]: tdi = pd.TimedeltaIndex(["1 days", pd.NaT, "2 days"])In [111]: tdi.to_list()Out[111]: [Timedelta('1 days 00:00:00'), NaT, Timedelta('2 days 00:00:00')]In [112]: dti = pd.date_range("...
When using DataFrame.replace() to replace specific pd.Timestamp values with np.nan, the resulting values become pd.NaT instead of np.nan. This behavior differs from pandas 1.1.5, where the replaced values were np.nan as expected. Output date 0 NaT 1 NaT 2 2025-01-03 Expected Behavior...
Easy handling of missing data (represented as NaN, NA, or NaT) in floating point as well as non-floating point data Size mutability: columns can be inserted and deleted from DataFrame and higher dimensional objects Automatic and explicit data alignment: objects can be explicitly aligned to a se...
在单值替换的基础上更进一步,就是进行多值替换,也就是把多个数据同时转化为指定的数据,需要同时使用到to_replace参数和value参数。把所有要替换的数据都放在列表中然后复制给to_replace参数,注意这里event字段是字符串数据类型,里面的0自然也是...