Suppose I have a DataFrame with some NaNs: >>> import pandas as pd >>> df = pd.DataFrame([[1, 2, 3], [4, None, None], [None, None, 9]]) >>> df 0 1 2 0 1 2 3 1 4 NaN NaN 2 NaN NaN 9 What I need to do is replace every NaN with the first non-NaN … Read more
I’ve a csv file without header, with a DateTime index. I want to rename the index and column name, but with df.rename() only the column name is renamed. Bug? I’m on version 0.12.0 In [2]: df = pd.read_csv(r’D:\Data\DataTimeSeries_csv//seriesSM.csv’, header=None, parse_dates=[[0]], index_col=[0] ) In [3]: df.head() Out[3]: 1 0 2002-06-18 0.112000 2002-06-22 0.190333 2002-06-26 0.134000 2002-06-30 … Read more
Working with a data frame similar to this: set.seed(100) df <- data.frame(cat = c(rep(“aaa”, 5), rep(“bbb”, 5), rep(“ccc”, 5)), val = runif(15)) df <- df[order(df$cat, df$val), ] df cat val 1 aaa 0.05638315 2 aaa 0.25767250 3 aaa 0.30776611 4 aaa 0.46854928 5 aaa 0.55232243 6 bbb 0.17026205 7 bbb 0.37032054 8 bbb 0.48377074 9 … Read more
What is the most efficient way to organise the following pandas Dataframe: data = Position Letter 1 a 2 b 3 c 4 d 5 e into a dictionary like alphabet[1 : ‘a’, 2 : ‘b’, 3 : ‘c’, 4 : ‘d’, 5 : ‘e’]? 7 Answers 7
I have some trouble to convert my data.frame from a wide table to a long table. At the moment it looks like this: Code Country 1950 1951 1952 1953 1954 AFG Afghanistan 20,249 21,352 22,532 23,557 24,555 ALB Albania 8,097 8,986 10,058 11,123 12,246 Now I would like to transform this data.frame into a long … Read more
I am trying to highlight exactly what changed between two dataframes. Suppose I have two Python Pandas dataframes: “StudentRoster Jan-1”: id Name score isEnrolled Comment 111 Jack 2.17 True He was late to class 112 Nick 1.11 False Graduated 113 Zoe 4.12 True “StudentRoster Jan-2”: id Name score isEnrolled Comment 111 Jack 2.17 True He … Read more
I have pandas dataframe df1 and df2 (df1 is vanila dataframe, df2 is indexed by ‘STK_ID’ & ‘RPT_Date’) : >>> df1 STK_ID RPT_Date TClose sales discount 0 000568 20060331 3.69 5.975 NaN 1 000568 20060630 9.14 10.143 NaN 2 000568 20060930 9.49 13.854 NaN 3 000568 20061231 15.84 19.262 NaN 4 000568 20070331 17.00 6.803 … Read more
I am trying to fill none values in a Pandas dataframe with 0’s for only some subset of columns. When I do: import pandas as pd df = pd.DataFrame(data={‘a’:[1,2,3,None],’b’:[4,5,None,6],’c’:[None,None,7,8]}) print df df.fillna(value=0, inplace=True) print df The output: a b c 0 1.0 4.0 NaN 1 2.0 5.0 NaN 2 3.0 NaN 7.0 3 NaN 6.0 … Read more
I’m new to pandas and trying to figure out how to add multiple columns to pandas simultaneously. Any help here is appreciated. Ideally I would like to do this in one step rather than multiple repeated steps… import pandas as pd df = {‘col_1’: [0, 1, 2, 3], ‘col_2’: [4, 5, 6, 7]} df = … Read more
I have a pandas dataframe and I wish to divide it to 3 separate sets. I know that using train_test_split from sklearn.cross_validation, one can divide the data in two sets (train and test). However, I couldn’t find any solution about splitting the data into three sets. Preferably, I’d like to have the indices of the … Read more
