I would like to add a column ‘D’ to a dataframe like this: U,L 111,en 112,en 112,es 113,es 113,ja 113,zh 114,es based on the following Dictionary: d = {112: 'en', 113: 'es', 114: 'es', 111: 'en'} so that the resulting dataframe appears as: U,L,D 111,en,en 112,en,en 112,es,en 113,es,es 113,ja,es 113,zh,es 114,es,es So far I tried … Read more
I have a csv file containing numerical values such as 1524.449677. There are always exactly 6 decimal places.
I have a dataframe with this type of data (too many columns):
I would like to know if there is someway of replacing all DataFrame negative numbers by zeros?
Y1961 Y1962 Y1963 Y1964 Y1965 Region 0 82.567307 83.104757 83.183700 83.030338 82.831958 US 1 2.699372 2.610110 2.587919 2.696451 2.846247 US 2 14.131355 13.690028 13.599516 13.649176 13.649046 US 3 0.048589 0.046982 0.046583 0.046225 0.051750 US 4 0.553377 0.548123 0.582282 0.577811 0.620999 US In the above dataframe, I would like to get average of each row. currently, … Read more
I have a dataframe that looks like this:
I want to subtract dates in ‘A’ from dates in ‘B’ and add a new column with the difference.
It sounds somewhat weird， but I need to save the Pandas console output string to png pics. For example:
Column names are: ID,1,2,3,4,5,6,7,8,9.
How do I get the exponential weighted moving average in NumPy just like the following in pandas?