Python calculate_statistics Examples

Example #1

File: build.py Project: viishnu712/descriptive_statistics_project

def plot():
    plt.hist(sale_price)
    plt.title("sales price")
    plt.xlabel("Price")
    plt.ylabel("Frequency")
    plt.axvline(x = calculate_statistics()[0], linewidth=1, color='r', linestyle='dashed',label='Mean')
    plt.axvline(x = calculate_statistics()[1], linewidth=1, color='g', linestyle='dashed',label='Median')
    plt.axvline(x = calculate_statistics()[2], linewidth=1, color='y', linestyle='dashed',label='Mode')
    plt.show()

Example #2

File: build.py Project: sacvijai/descriptive_statistics_project

def plot():
    plt.figure(figsize=(10, 6))
    plt.hist(sale_price, bins=40)
    plt.axvline(calculate_statistics()[0], label='mean', color='Red')
    plt.axvline(calculate_statistics()[1], label='median', color='Green')
    plt.axvline(calculate_statistics()[2], label='mode', color='Yellow')
    plt.legend()
    plt.show()
    return

Example #3

File: build.py Project: zob19/descriptive_statistics_project

def plot():
    mean,median,mode=calculate_statistics()
    plt.hist(sale_price)
    plt.axvline(x=mean,c='r')
    plt.axvline(x=median,c='y')
    plt.axvline(x=mode,c='g')
    plt.show()

Example #4

def plot():
    list_1 = calculate_statistics()
    plt.hist(sale_price)
    plt.axvline(list_1[0])
    plt.axvline(list_1[1])
    plt.axvline(list_1[2])
    plt.show()

Example #5

def plot():
    me, md, mo = calculate_statistics()
    plt.hist(sale_price, bins=50)
    plt.axvline(x=me, color='r')
    plt.axvline(x=md, color='b')
    plt.axvline(x=mo, color='g')
    plt.show()

Example #6

def plot():
    plt.hist(sale_price, bins=70)
    mean.median.mode = calculate_statistics()
    plt.axvline(mean)
    plt.axvline(median)
    plt.axvline(mode)
    plt.show()

Example #7

def plot():
    t = calculate_statistics()
    sale_price.hist()
    plt.axvline(t[0], color='b', linestyle='solid', linewidth=2)
    plt.axvline(t[1], color='r', linestyle='dashed', linewidth=4)
    plt.axvline(t[2], color='1', linestyle='dotted', linewidth=2)
    plt.show()

Example #8

File: build.py Project: HardikaB/descriptive_statistics_project

def plot():
    m,md,mo=calculate_statistics()
    plt.hist(sale_price)
    plt.axvline(x=m,label='mean',c='r')
    plt.axvline(x=md,label='median',c='g')
    plt.axvline(x=mo,label='mode',c='y')
    plt.show()

Example #9

File: build.py Project: riteshk28/descriptive_statistics_project

def plot():
    sale_price.hist(bins=50)
    mean, median, mode = calculate_statistics()
    plt.axvline(x=mean, color='red')
    plt.axvline(x=median, color='black')
    plt.axvline(x=mode, color='yellow')
    plt.show()

Example #10

File: build.py Project: kravigupta/descriptive_statistics_project

def plot():
    mean, median, mode = calculate_statistics() #sale_price.mean(), sale_price.median(), sale_price.mode()[0]
    plt.hist(sale_price)
    plt.axvline(x=mean, label='mean', color='r')
    plt.axvline(x=median, label='median', color='c')
    plt.axvline(x=mode, label='mode', color='b')
    plt.show()

Example #11

File: build.py Project: swapcy/descriptive_statistics_project

def plot():
    mean, median, mode = calculate_statistics()
    plt.hist(sale_price, color='green', alpha=0.5, bins=200)
    plt.axvline(x=mean, color='red', label='mean')
    plt.axvline(x=median, color='blue', label='median')
    plt.axvline(x=mode, color='yellow', label='mode')
    plt.legend()
    plt.show()

Example #12

File: build.py Project: CharulataShelar/descriptive_statistics_project

def plot():
    mean, median, mode = calculate_statistics()
    #print(mean, median, mode)
    plt.hist(sale_price, bins=20)
    plt.axvline(mean, color='r')
    plt.axvline(median, color='g')
    plt.axvline(mode, color='y')
    plt.show()

Example #13

def plot():
    value = calculate_statistics()
    #print(value[0])
    plt.hist(sale_price)
    plt.axvline(value[0])
    plt.axvline(value[1])
    plt.axvline(value[2])
    plt.show()

Example #14

File: build.py Project: amrutasawant13/descriptive_statistics_project

def plot():

    mean, median, mod = calculate_statistics()
    x = sale_price
    plt.hist(x, bins=100, color='c', edgecolor='k', alpha=0.65)
    plt.axvline(mean, color='k', linestyle='dashed', linewidth=1)
    plt.axvline(median, color='r', linestyle='dashed', linewidth=1)
    plt.axvline(mod, color='g', linestyle='dashed', linewidth=1)
    plt.show()

Example #15

File: build.py Project: greyatomtestuser2/descriptive_statistics_project

def plot():
    mean, median, mode = calculate_statistics()
    plt.hist(sale_price, color='c')
    plt.axvline(mean, color='b', linestyle='dashed', linewidth=2)
    plt.axvline(median, color='b', linestyle='dashed', linewidth=2)
    plt.axvline(pd.Series(mode).values,
                color='b',
                linestyle='dashed',
                linewidth=2)

Example #16

File: build.py Project: samir0719/descriptive_statistics_project

def plot():
    sale_price = dataframe['SalePrice']
    mean, median, mode = calculate_statistics()
    plt.hist(dataframe['SalePrice'], bins=20, color='c')
    x = sale_price.value_counts()
    d = np.asscalar(x[x.values == x.values.max()].index)
    plt.axvline(mean, color='b', linestyle='dashed', linewidth=2)
    plt.axvline(median, color='r', linestyle='dashed', linewidth=2)
    plt.axvline(d, color='g', linestyle='dashed', linewidth=2)
    plt.show()

Example #17

File: build.py Project: arushikumar/descriptive_statistics_project

def plot():
    mean_sale, median_sale, mode_sale = calculate_statistics()
    #sales = [mean_sale, median_sale, mode_sale]
    plt.hist(sale_price, color="b")
    #plt.axvline((mean_sale, median_sale, mode_sale), color='r', linestyle='dashed', linewidth=2)
    plt.axvline(mean_sale, color='g', linestyle='dashed', linewidth=2)
    plt.axvline(median_sale, color='r', linestyle='dashed', linewidth=2)
    plt.axvline(mode_sale[0], color='c', linestyle='dashed', linewidth=2)
    #plt.axvline(sales[0], sales[1],sales[2])
    plt.show()

Example #18

def plot():
    mean, median, mode = calculate_statistics()
    ax = sale_price.plot(kind='hist',grid=True, color='c')
    ax.set_xlabel("Sales Price")
    ax.axvline(mean, color='r', label='Mean', linestyle='--', lw='1.9')
    ax.axvline(median, color='g', label='Median', linestyle='--', lw='1.9')
    ax.axvline(mode, color='m', label='Mode', linestyle='--', lw='1.9')
    ax.legend()
    ax.set_title('Histogram of Sale Price with Mean, Median and Mode')
    plt.show()

Example #19

File: build.py Project: ankit-a-mehta/descriptive_statistics_project

def plot():
    mean, median, mode = calculate_statistics()
    plt.figure(figsize=(10, 6))
    plt.hist(sale_price, bins=40)
    plt.plot([mode] * 300, range(300), label='mode')
    plt.plot([median] * 300, range(300), label='median')
    plt.plot([mean] * 300, range(300), label='mean')
    plt.ylim(0, 250)
    plt.legend()
    plt.show()

Example #20

def plot():
    mean, median, mode = calculate_statistics()

    plt.axvline(mean, label="Mean", color='g')
    plt.axvline(median, label="Median", color='r')
    plt.axvline(mode, label="Mode", color="y")
    plt.legend()
    plt.show()

    return

Example #21

def plot():
    x=calculate_statistics()
    mean=x[0]
    median=x[1]
    mode=x[2]
    plt.hist(sale_price,color='c')
    plt.axvline(mean,linestyle='dashed',color='b',label='mean')
    plt.axvline(median,linestyle='dashed',color='r',label='median')
    plt.axvline(mode[0],linestyle='dashed',color='g',label='mode')
    plt.legend(loc='upper right')
    plt.show()

Example #22

File: build.py Project: sohelahmadkhan/descriptive_statistics_project

def plot():
    a = calculate_statistics()
    Mean = a[0]
    Median = a[1]
    Mode = a[2]
    result = plt.hist(sale_price, color='y')
    #plt.axvline(sale_price.mean(), color='red', linestyle='dashed', linewidth=2)
    #plt.axvline(sale_price.median(), color='g', linestyle='dashed', linewidth=2)
    plt.axvline(Mean, color='r', linestyle='dashed', linewidth=2)
    plt.axvline(Median, color='g', linestyle='dashed', linewidth=2)
    plt.axvline(Mode, color='b', linestyle='dashed', linewidth=2)
    plt.show()

Example #23

File: build.py Project: smoolya17/descriptive_statistics_project

def plot():
    mean, median, mode = calculate_statistics()
    plt.figure(figsize=(14, 4))
    plt.subplot(131)
    plt.hist(sale_price)
    plt.title('Mean')
    plt.axvline(mean, color='b', linestyle='dashed', linewidth=2)
    plt.subplot(132)
    plt.hist(sale_price)
    plt.title('Median')
    plt.axvline(median, color='b', linestyle='dashed', linewidth=2)
    plt.subplot(133)
    plt.hist(sale_price)
    plt.title('Mode')
    plt.axvline(mode, color='b', linestyle='dashed', linewidth=2)
    plt.show()

Example #24

File: build.py Project: ms10031990/descriptive_statistics_project

def plot():
    #Get the mean, median and mode from calculate_statistics function for saleprice for housing Iowa
    args = calculate_statistics()

    #figure(figsize=(1,1)) creates an inch-by-inch image, which will be 80-by-80 pixels unless you also give a different dpi argument.
    plt.figure(figsize=(10, 6))

    #plot the histogram for sale_price {bins = range of values on x axis and y denotes the count of elements falling between those range}
    plt.hist(sale_price, bins=40)

    #plot the mean by value on x being mode/mean/median plotted 300 times while on y being plotted 0-299 times to get a straight line
    plt.plot([args[0]] * 300, range(300), label='mode')
    plt.plot([args[1]] * 300, range(300), label='median')
    plt.plot([args[2]] * 300, range(300), label='mean')

    #limit the length of y till 250 only
    plt.ylim(0, 250)

    #plot the lables as well defined in mean, median and mode plotting
    plt.legend()

    #finally show the histogram along with mean, median and mode
    plt.show

Example #25

# %load q02_plot/build.py
# Default Imports
import pandas as pd
import matplotlib.pyplot as plt
from greyatomlib.descriptive_stats.q01_calculate_statistics.build import calculate_statistics

plt.switch_backend('agg')
dataframe = pd.read_csv('data/house_prices_multivariate.csv')
sale_price = dataframe.loc[:, 'SalePrice']

# Draw the plot for the mean, median and mode for the dataset

list_1 = calculate_statistics()


def plot():
    list_1 = calculate_statistics()
    plt.hist(sale_price)
    plt.axvline(list_1[0])
    plt.axvline(list_1[1])
    plt.axvline(list_1[2])
    plt.show()


#calculate_statistics()
plot()

Example #26

File: build.py Project: aditya81295/descriptive_statistics_project

# Default Imports
import pandas as pd

import matplotlib.pyplot as plt
plt.switch_backend('agg')
from greyatomlib.descriptive_stats.q01_calculate_statistics.build import calculate_statistics

dataframe = pd.read_csv('data/house_prices_multivariate.csv')
sale_price = dataframe.loc[:, 'SalePrice']
mmm = calculate_statistics()
mean = mmm[0]
median = mmm[1]
mode = mmm[2]

# Draw the plot for the mean, median and mode for the dataset


def plot():

    plt.figure(figsize=(10, 6))
    plt.hist(sale_price, bins=40)
    plt.plot([mode] * 300, range(300), label='mode')
    plt.plot([median] * 300, range(300), label='median')
    plt.plot([mean] * 300, range(300), label='mean')
    #plt.ylim(0, 250)
    plt.legend()
    plt.show()

Example #27

# %load q02_plot/build.py
# Default Imports
import pandas as pd
import matplotlib.pyplot as plt
plt.switch_backend('agg')
from greyatomlib.descriptive_stats.q01_calculate_statistics.build import calculate_statistics
mean,median,mode=calculate_statistics()
dataframe = pd.read_csv('data/house_prices_multivariate.csv')
sale_price = dataframe.loc[:,'SalePrice']


# Draw the plot for the mean, median and mode for the dataset
def plot():
    plt.figure(figsize=(10, 6))
    plt.hist(sale_price, bins=40)
    plt.plot([mode]*300, range(300), label='mode')
    plt.plot([median]*300, range(300), label='median')
    plt.plot([mean]*300, range(300), label='mean')
    plt.ylim(0, 250)
    plt.legend()
    return plt.show()
plot()