data.columns.str.contains("\d{2}$",regex=True)array([False,False,True,False])正则表达式"\d{...
df_filtered = df[df['column_name'].str.contains("your_string", regex=False)]```2.空值(NaN...
pandas 如果列包含字符串，则将其重命名为特定值(使用.replace & regex)如https://stackoverflow.com/...
get_dummies()Split strings on the delimiter returning DataFrame of dummy variables contains()Return boolean array if each string contains pattern/regex replace()Replace occurrences of pattern/regex/string with some other string or the return value of a callable given the occurrence repeat()Duplicate ...
regex:表示使用正则 ge函数 进行比较的一个函数:ge表示greater equal hist函数 pandas内置的绘制直方图的函数 df4 = pd.DataFrame({ 'length': [1.5,0.5,1.2,0.9,3], 'width': [0.7,0.2,0.15,0.2,1.1] }, index=['pig','rabbit','duck','chicken','horse']) ...
contains(r'some.regex.*pattern')] 复杂的lambda函数过滤 代码语言:python 代码运行次数:0 运行 AI代码解释 """creating complex filters using functions on rows: http://goo.gl/r57b1""" df[df.apply(lambda x: x['b'] > x['c'], axis=1)] 替换操作 代码语言:python 代码运行次数:0 运行 AI...
先转成str格式再用contains筛选 1 df_fintech = df_text[df_text['业务一级分类'].str.contains("金融科技")] 3、筛选出列值属于某个范围内的行,用isin 1 df.loc[df['column_name'].isin(some_values)] # some_values是可迭代对象 4、多种条件限制时使用&,&的优先级高于>=或<=,所以要注意括号的...
并讲解了一些简单的示例。通过将表达式赋值给一个新列（例如df['new column']=expression），可以在大...
# iterates through all strings within list in dataframe column: for strings in text: # determines the two words to search (iterates through word_list) word1, word2 = i[0], i[1] # use regex to find both words: p = re.compile('.*?'.join((word1, word2))) ...
列索引:column:区分不同的列,axis=1 1、创建 Dateframe 表格的几种方式: importpandas'''通过列表创建'''#一、默认方式df = pandas.DataFrame([['xiaomi',3999],['huawei',4999]])#二、list(dict) 方式df = pandas.DataFrame([{'xiaomi':3999,'huawei':4999},{'xiaomi':2999,'huawei':5999}])#三...