pd.read_excel('path_to_file.xls', sheetname='Sheet1')
There are many parsing options for read_excel (similar to the options in read_csv.
pd.read_excel('path_to_file.xls',
sheetname='Sheet1', header=[0, 1, 2],
skiprows=3, index_col=0) # etc.
// A simple adder function defined as a lambda expression.
// Unlike with regular functions, parameter types often may be omitted because the
// compiler can infer their types
let adder = |a, b| a + b;
// Lambdas can span across multiple lines, like normal functions.
let multiplier = |a: i32, ...
Unlike regular functions, lambda expressions can capture their environments. Such lambdas are called closures.
// variable definition outside the lambda expression...
let lucky_number: usize = 663;
// but the our function can access it anyway, thanks to the closures
let print_lucky_number = ...
Since lambda functions are values themselves, you store them in collections, pass them to functions, etc like you would with other values.
// This function takes two integers and a function that performs some operation on the two arguments
fn apply_function<T>(a: i32, b: i32, func: T) -> ...
If no ordering function is passed, std::sort will order the elements by calling operator< on pairs of elements, which must return a type contextually convertible to bool (or just bool). Basic types (integers, floats, pointers etc) have already build in comparison operators.
We can overload this ...
// Include sequence containers
#include <vector>
#include <deque>
#include <list>
// Insert sorting algorithm
#include <algorithm>
class Base {
public:
// Constructor that set variable to the value of v
Base(int v): variable(v) {
}
i...
C++11
// Include sequence containers
#include <vector>
#include <deque>
#include <list>
#include <array>
#include <forward_list>
// Include sorting algorithm
#include <algorithm>
class Base {
public:
// Constructor that set variable to the va...
BigInteger is in an immutable object, so you need to assign the results of any mathematical operation, to a new BigInteger instance.
Addition:
10 + 10 = 20
BigInteger value1 = new BigInteger("10");
BigInteger value2 = new BigInteger("10");
BigInteger sum = value1.add(value...
You can access each property that belongs to an object with this loop
for (var property in object) {
// always check if an object has a property
if (object.hasOwnProperty(property)) {
// do stuff
}
}
You should include the additional check for hasOwnProperty because an o...
pip may be used to install BeautifulSoup. To install Version 4 of BeautifulSoup, run the command:
pip install beautifulsoup4
Be aware that the package name is beautifulsoup4 instead of beautifulsoup, the latter name stands for old release, see old beautifulsoup
Here is an example class which has a couple of instance variables, without using properties:
@interface TestClass : NSObject {
NSString *_someString;
int _someInt;
}
-(NSString *)someString;
-(void)setSomeString:(NSString *)newString;
-(int)someInt;
-(void)setSomeInt:(NSString *)...
Assuming a source file of hello_world.v and a top level module of hello_world. The code can be run using various simulators. Most simulators are compiled simulators. They require multiple steps to compile and execute.
Generally the
First step is to compile the Verilog design.
Second step is to ...
The syntax for Java generics bounded wildcards, representing the unknown type by ? is:
? extends T represents an upper bounded wildcard. The unknown type represents a type that must be a subtype of T, or type T itself.
? super T represents a lower bounded wildcard. The unknown type repres...
For programmers coming from GCC or Clang to Visual Studio, or programmers more comfortable with the command line in general, you can use the Visual C++ compiler from the command line as well as the IDE.
If you desire to compile your code from the command line in Visual Studio, you first need to set...
DataFrame:
import pandas as pd
import numpy as np
np.random.seed(5)
df = pd.DataFrame(np.random.randint(100, size=(5, 5)), columns = list("ABCDE"),
index = ["R" + str(i) for i in range(5)])
df
Out[12]:
A B C D E
R0 99 78 61 16 73...
Group by one column
Using the following DataFrame
df = pd.DataFrame({'A': ['a', 'b', 'c', 'a', 'b', 'b'],
'B': [2, 8, 1, 4, 3, 8],
'C': [102, 98, 107, 104, 115, 87]})
df
# Output:
# A B C
# 0 a 2 102
# 1 b 8 98
# 2 c 1 107
# 3 a...
The prototype pattern focuses on creating an object that can be used as a blueprint for other objects through prototypal inheritance. This pattern is inherently easy to work with in JavaScript because of the native support for prototypal inheritance in JS which means we don't need to spend time or e...
