nan

来源： https://stackoverflow.com/questions/63814507/how-to-modify-inf-into-an-index

问题 I have table x : website 0 http://www.google.com/ 1 http://www.yahoo.com 2 None I want to replace python None with pandas NaN. I tried: x.replace(to_replace=None, value=np.nan) But I got: TypeError: 'regex' must be a string or a compiled regular expression or a list or dict of strings or regular expressions, you passed a 'bool' How should I go about it? 回答1: You can use DataFrame.fillna or Series.fillna which will replace the Python object None , not the string 'None' . import pandas as pd

问题 I have table x : website 0 http://www.google.com/ 1 http://www.yahoo.com 2 None I want to replace python None with pandas NaN. I tried: x.replace(to_replace=None, value=np.nan) But I got: TypeError: 'regex' must be a string or a compiled regular expression or a list or dict of strings or regular expressions, you passed a 'bool' How should I go about it? 回答1: You can use DataFrame.fillna or Series.fillna which will replace the Python object None , not the string 'None' . import pandas as pd

问题 I want to create in jquery a web page with two text boxes, a button and a div with dummy text. After clicking the button, the height and width of the div is set with the values entered in text boxes. Make a submitted values a number using the parseInt function. Then check whether the entered value is actually a number. If not, you will see an error message under the division. My question is, how can i use function parseInt and also function isNaN in this case and get error message ? Thanks

问题 I want to create in jquery a web page with two text boxes, a button and a div with dummy text. After clicking the button, the height and width of the div is set with the values entered in text boxes. Make a submitted values a number using the parseInt function. Then check whether the entered value is actually a number. If not, you will see an error message under the division. My question is, how can i use function parseInt and also function isNaN in this case and get error message ? Thanks

问题 My dataframe contains both NaT and NaN values Date/Time_entry Entry Date/Time_exit Exit 0 2015-11-11 10:52:00 19.9900 2015-11-11 11:30:00 20.350 1 2015-11-11 11:36:00 20.4300 2015-11-11 11:38:00 20.565 2 2015-11-11 11:44:00 21.0000 NaT NaN 3 2009-04-20 10:28:00 13.7788 2009-04-20 10:46:00 13.700 I want to fill NaT with dates and NaN with numbers. Fillna(4) method replaces both NaT and NaN with 4. Is it possible to differentiate between NaT and NaN somehow? My current workaround is to df

问题 I am trying to compare two different lists to see if they are equal, and was going to remove NaNs, only to discover that my list comparisons still work, despite NaN == NaN -> False . Could someone explain why the following evaluate True or False , as I am finding this behavior unexpected. Thanks, I have read the following which don't seem to resolve the issue: Why in numpy nan == nan is False while nan in [nan] is True? Why is NaN not equal to NaN? [duplicate] (Python 2.7.3, numpy-1.9.2) I

问题 I have difficulties to understand how to correctly use HandleScope and EscapableHandleScope. For example, from this Node example: MyObject::MyObject(const Napi::CallbackInfo& info) : Napi::ObjectWrap<MyObject>(info) { Napi::Env env = info.Env(); Napi::HandleScope scope(env); this->val_ = info[0].As<Napi::Number>().DoubleValue(); }; Why do we need to create a new HandleScope in this case? And from this other example: Napi::Object CreateObject(const Napi::CallbackInfo& info) { Napi::Env env =

问题 I have a column ( lets call it Column X) containing around 16000 NaN values. The column has two possible values, 1 or 0 ( so like a binary ) I want to fill the NaN values in column X, but i don't want to use a single value for ALL the NaN entries. say for instance that; i want to fill 50% of the NaN values with '1' and the other 50% with '0'. I have read the ' fillna() ' documentation but i have not found any such relevant information which could satisfy this functionality. I have literally

问题 I want to fill the value of the nan in the given value as following: df = pd.DataFrame({'A' : ['aa', 'bb', 'cc', 'aa'], 'B': ['xx', 'yy', 'zz','xx'], 'C': ['2', '3','8', np.nan]}) print (df) A B C aa xx 2 bb yy 3 cc zz 8 aa xx NaN Expected Output: A B C aa xx 2 bb yy 3 cc zz 8 aa xx 2 Since column A and B have value 2 in the third column, therefore last row should also have 2 in the C column. 回答1: Use GroupBy.ffill with DataFrame.sort_values and DataFrame.sort_index for NaN s to end of groups