series

df.append() is not appending to the DataFrame

由 ♀尐吖头ヾ 提交于 2019-12-09 01:02:22
问题 I formulated this question about adding rows WITH index, but it is not yet clear to me how/why this happens when there are no indexes: columnsList=['A','B','C','D'] df8=pd.DataFrame(columns=columnsList) L=['value aa','value bb','value cc','value dd'] s = pd.Series(dict(zip(df8.columns, L))) df8.append(s,ignore_index=True) df8.append(s,ignore_index=True) I EXPECT HERE A 2X4 DATAFRAME. nevertheless no values where added, nor an error occurred. print(df8.shape) #>>> (0,4) Why is the series not

Group by groups to Pandas Series/Dataframe

由 主宰稳场 提交于 2019-12-08 20:48:26
Apologies in advance if this question is naive. I am new to Python. I am trying to perform a t-test on two columns of my dataframe. It only makes sense to do the t-test after having grouped the columns by another column in the same dataframe. I am dealing with something like this: rand_array = np.random.randint(low=10, high=30, size=9) rand_array2 = np.random.randint(low=10, high=30, size=9) d = {'key1':[0,0,1,0,1,1,1,0,1], 'key2': rand_array, 'key3': rand_array2} df1 = pd.DataFrame(d) print df1 The output I get is: key1 key2 key3 0 0 20 18 1 0 22 16 2 1 21 26 3 0 21 13 4 1 11 21 5 1 23 10 6 1

pandas: How to get the most frequent item in pandas series?

由 你离开我真会死。 提交于 2019-12-08 19:06:28
问题 How can I get the most frequent item in a pandas series? Consider the series s s = pd.Series("1 5 3 3 3 5 2 1 8 10 2 3 3 3".split()).astype(int) The returned value should be 3 回答1: You can just use pd.Series.mode and extract the first value: res = s.mode().iloc[0] This not necessarily inefficient. As always, test with your data to see what suits. import numpy as np, pandas as pd from scipy.stats.mstats import mode from collections import Counter np.random.seed(0) s = pd.Series(np.random

Excel: In which ways can one create ChartGroups?

由 微笑、不失礼 提交于 2019-12-08 17:02:36
I have a Chart containing two ChartGroup s. I never did this intentionally, so I cannot guess what caused this. Can anyone give all options (either VBA or else)? If I know which are the possible actions that may have led to this, I can be aware of and control/avoid them. PS: The downside of this is that I have quite a bit of code that uses the PlotOrder for identifying Series . When there is more than one ChartGroup , PlotOrder is not a unique identifier of a Series in a Chart (it is unique within a ChartGroup ). In the long run, I Will have to adapt my code, anyway. But for the time being, I

Finding the length of the longest ascending sub-series in an array using recursion and no loops

由 六月ゝ 毕业季﹏ 提交于 2019-12-08 07:14:25
问题 i've been stuck for hours trying to figure how can i write a function that gets and array of integers, and finds the length of the longest ascending sub-series in the array using recursion and no loops at all. im only allowed to use another 1 recursive function for example, for the following array: {45,1,21,3,3,6,53,9,18} the outpot should be 5, because the longest sub-series is {1,3,6,9,18}. So, basicly, a function that gets an array and its size, and needs to print the length of the longest

Display/Print one column from a DataFrame of Series in Pandas

由 北慕城南 提交于 2019-12-08 06:03:50
问题 I created the following Series and DataFrame: import pandas as pd Series_1 = pd.Series({'Name': 'Adam','Item': 'Sweet','Cost': 1}) Series_2 = pd.Series({'Name': 'Bob','Item': 'Candy','Cost': 2}) Series_3 = pd.Series({'Name': 'Cathy','Item': 'Chocolate','Cost': 3})` df = pd.DataFrame([Series_1,Series_2,Series_3], index=['Store 1', 'Store 2', 'Store 3']) I want to display/print out just one column from the DataFrame (with or without the header row): Either Adam Bob Cathy Or: Sweet Candy

Excel: In which ways can one create ChartGroups?

由 半城伤御伤魂 提交于 2019-12-08 05:01:15
问题 I have a Chart containing two ChartGroup s. I never did this intentionally, so I cannot guess what caused this. Can anyone give all options (either VBA or else)? If I know which are the possible actions that may have led to this, I can be aware of and control/avoid them. PS: The downside of this is that I have quite a bit of code that uses the PlotOrder for identifying Series . When there is more than one ChartGroup , PlotOrder is not a unique identifier of a Series in a Chart (it is unique

python pandas: Rename a series within a dataframe?

由 我与影子孤独终老i 提交于 2019-12-08 04:50:34
问题 I'm using python pandas for data analysis and I want to change the name of a series in a dataframe. This works, but it seems very inefficient: AA = pandas.DataFrame( A ) for series in A: AA[A_prefix+series] = A[series] del A[series] Is there a way to change the series name in place? 回答1: Sure, you can use the rename method: In [11]: df = DataFrame({"A": [1,2], "B": [3,4]}) In [12]: df.rename(columns={"A": "series formerly known as A"}) Out[12]: series formerly known as A B 0 1 3 1 2 4 This

python, how to convert a pandas series into a pandas DataFrame?

由 那年仲夏 提交于 2019-12-08 04:43:28
I have a pandas series sf: email email1@email.com [1.0, 0.0, 0.0] email2@email.com [2.0, 0.0, 0.0] email3@email.com [1.0, 0.0, 0.0] email4@email.com [4.0, 0.0, 0.0] email5@email.com [1.0, 0.0, 3.0] email6@email.com [1.0, 5.0, 0.0] How can I convert it to this following pandas DataFrame: index | email ________________________ 0 | email1@email.com 1 | email2@email.com 2 | email3@email.com 3 | email4@email.com 4 | email5@email.com 5 | email6@email.com Thanks for your help! >>> s = p.Series(data=[[1.0, 0.0, 0.0],[2.0, 0.0, 0.0]], index=['email1@email.com','email2@email.com']) >>> s email1@email

Group by groups to Pandas Series/Dataframe

由 こ雲淡風輕ζ 提交于 2019-12-08 04:07:38
问题 Apologies in advance if this question is naive. I am new to Python. I am trying to perform a t-test on two columns of my dataframe. It only makes sense to do the t-test after having grouped the columns by another column in the same dataframe. I am dealing with something like this: rand_array = np.random.randint(low=10, high=30, size=9) rand_array2 = np.random.randint(low=10, high=30, size=9) d = {'key1':[0,0,1,0,1,1,1,0,1], 'key2': rand_array, 'key3': rand_array2} df1 = pd.DataFrame(d) print
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