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Given an array update the second column by the square root of those values.
As rafaelc suggested, you can use np.sqrt on a specific column.
a = np.array([[1.,2.,3.],[1.,2.,3.]])
a[:,1] = np.sqrt(a[:,1])
a has two rows and three columns. a[:,1] is the second column.
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I have a large panel dataset of countries. I want to drop a large number of countries and keep a few only for a certain number of year. What would be the appropriate command?
I can't see your code but you might be able to use boolean masks
newdf = df[(df["Countries"] == "Ireland")|(df["Countries"] == "South Africa")]
newdf = newdf[df["Year"] == 2011]
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i have used pandas to read the csv file already
i have some questions, is the csv file been set to be some sort of list, or do i have to store the data?
i used df = pd.read.cv bla2
Your df would be a pandas dataframe object that includes all of the data.
As others have mentioned the data will be loaded as a DataFrame. I believe the correct syntax you are after is:
df = pd.read_csv('data.csv')
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I have a csv file that contains the attendance of a few students on particular dates.
Here is my csv file
Name,RollNumber,Attendance,Date,Day,Time
student1,1,Present,1/30/2019,Wednesday,12:34:05
student2,2,Present,1/30/2019,Wednesday,12:34:05
student3,3,Present,1/30/2019,Wednesday,12:34:05
student4,4,Present,1/30/2019,Wednesday,12:34:05
student1,1,Absent,1/31/2019,Thursday,23:34:05
student2,2,Present,1/31/2019,Thursday,23:34:05
student3,3,Present,1/31/2019,Thursday,23:34:05
student4,4,Present,1/31/2019,Thursday,12:34:05
student1,1,Present,2/1/2019,Friday,12:34:05
student2,2,Absent,2/1/2019,Friday,12:34:05
student3,3,Absent,2/1/2019,Friday,12:34:05
student4,4,Present,2/1/2019,Friday,12:34:05
student1,1,Absent,2/2/2019,Saturday,12:34:05
student2,2,Absent,2/2/2019,Saturday,12:34:05
student3,3,Absent,2/2/2019,Saturday,12:34:05
student4,4,Absent,2/2/2019,Saturday,12:34:05
I want to plot a graph that show the number of students present and absent on each date from the csv file. How do I do this with matplotlib?
The easiest way in my opinion is to work with pandas pivot_table as follow:
df = pd.read_csv('your_csv_filepath_here')
# Create a duplicate of your target value
df['attendance'] = a.Attendance
# Pivot your dataframe
df_pivot = df.pivot_table(index=['Date'], columns='Attendance', values='attendance', aggfunc='count')
# Plot it using pandas (barplot is probably what you want)
df_pivot.plot(kind='bar')
Of course further plot customizations are possible, as well as other methods would achieve the same result
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I have some large matrices and vectors calculated in R. I want to transfer this data to Python (2.7) in order to do some further data analysis.
What is a recommended way to do this?
I am very familiar with R, but a beginner in Python.
Use write.csv(matrix, "~/filename.csv) in R and then in Python either (if you want to use pandas)
import pandas as pd
new_matrix = pd.read_csv("~/filename.csv")
or (if you want to use numpy)
import numpy as np
new_matrix = np.genfromtxt("~/filename.csv", delimiter = ",")