Created a year ago
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import matplotlib.patches as mpatches
%matplotlib inline
import seaborn as sns
import calendar
import plotly as pt
from plotly import graph_objs as go
import plotly.express as px
import plotly.figure_factory as ff
from pylab import *
import matplotlib.patheffects as PathEffects
import dask.dataframe as dd
import warnings
warnings.filterwarnings('ignore')
datafile = './Data/US_Accidents_March23.csv'
Data Preparation and Cleaning
- Load the file using Pandas
- Look at some information about the data & the columns
- Fix any missing or incorrect values
%%time
df = dd.read_csv(datafile)
Wall time: 23.4 ms
%%time
df = df.compute()
Wall time: 1min 57s