Show me how to import my threading.csv to Python, then plot the "threads" and "data" columns as a linear regression up to 1000 with test size of 10% a scatterplot and a line with matplotlib.
system
mujhe dikhaao ki kaise mere threading ko aayaat karen. paythan main.
user
hamen uske liye Matplotlib, Scikit-Learn, Numpy or Pandas DataFrames kaa upyog karnaa hoga.

# modul aayaat karen
Sklearn aayaat dataset se, Linear_model
aayaat matplotlib
PLT ke rup main matplotlib.pyplot aayaat karen
enpi ke rup main sankhya ko aayaat karen
pidi ke rup main pandas aayaat karen

# CSV fil lod karen
df = pd.read_csv ("ththing.csv")
# X or y maanon ko paribhaashit karen
y = df ["threads"]
x = df ["data"]
x = x.Reshape (len (x), 1)
y = y.reshape (len (y), 1)
# prashikshan or pareekshan data main data ko vibhajit karen
x_train = x [:-100]
x_test = x [-100:]
y_train = y [:-100]
y_test = y [-100:]

# data plot karen
plt.scatter (x_test, y_test)
plt.xlabel ("threads")
plt.ylabel ("data")
plt.xticks (())
plt.yticks (())

# model ko prashikshit karen or pratigaman line banaaen
regr = linear_model.linearregression ()
regr.fit (x_train, y_train)
plt.plot (x_test, regr.predict (x_test))

# plot dikhaao
plt.show ()

pehle kaa code pehle `Sklearn`,` Matplotlib`, or `pandas` modul aayaat karata he.pands modul, `pidi`, kaa upyog siesavi fil" threading.siesavi "se data aayaat ke pehle charan main kiya jaataa he.us data kaa upyog `x` or` y` char ko paribhaashit karne ke liye kiya jaataa he, jise `.reshape ()` vidhi prashikshan or pareekshan ke liye upyukt saraniyon main phir se khol degi.phir data ko prashikshan or pareekshan data, `x_train`,` x_test`, `y_train`, or` y_test` main vibhajit kiya jaataa he, kul data ke 10% ke rup main prashikshan data ke saath.pareekshan data ko `plt.scatter ()` ke saath graph par ek scaterplot ke liye, x or y kulhadiyon ke liye label ke saath plot kiya jaataa he.ant main, `Sklearn` fnction` linear_model.linearregression () `kaa upyog data ko ek pratigaman line main feet karne ke liye kiya jaataa he, jise graph par bhavishyavaanee kii jaati he or plot kiya jaataa he.`Plt.show ()` line antim graph pradarshit karti he.
assistant
<|system|>
</s>
<|user|>
mujhe dikhaao ki kaise mere threading ko aayaat karen. paythan main.</s>
<|assistant|>
hamen uske liye Matplotlib, Scikit-Learn, Numpy or Pandas DataFrames kaa upyog karnaa hoga.

# modul aayaat karen
Sklearn aayaat dataset se, Linear_model
aayaat matplotlib
PLT ke rup main matplotlib.pyplot aayaat karen
enpi ke rup main sankhya ko aayaat karen
pidi ke rup main pandas aayaat karen

# CSV fil lod karen
df = pd.read_csv ("ththing.csv")
# X or y maanon ko paribhaashit karen
y = df ["threads"]
x = df ["data"]
x = x.Reshape (len (x), 1)
y = y.reshape (len (y), 1)
# prashikshan or pareekshan data main data ko vibhajit karen
x_train = x [:-100]
x_test = x [-100:]
y_train = y [:-100]
y_test = y [-100:]

# data plot karen
plt.scatter (x_test, y_test)
plt.xlabel ("threads")
plt.ylabel ("data")
plt.xticks (())
plt.yticks (())

# model ko prashikshit karen or pratigaman line banaaen
regr = linear_model.linearregression ()
regr.fit (x_train, y_train)
plt.plot (x_test, regr.predict (x_test))

# plot dikhaao
plt.show ()

pehle kaa code pehle `Sklearn`,` Matplotlib`, or `pandas` modul aayaat karata he.pands modul, `pidi`, kaa upyog siesavi fil" threading.siesavi "se data aayaat ke pehle charan main kiya jaataa he.us data kaa upyog `x` or` y` char ko paribhaashit karne ke liye kiya jaataa he, jise `.reshape ()` vidhi prashikshan or pareekshan ke liye upyukt saraniyon main phir se khol degi.phir data ko prashikshan or pareekshan data, `x_train`,` x_test`, `y_train`, or` y_test` main vibhajit kiya jaataa he, kul data ke 10% ke rup main prashikshan data ke saath.pareekshan data ko `plt.scatter ()` ke saath graph par ek scaterplot ke liye, x or y kulhadiyon ke liye label ke saath plot kiya jaataa he.ant main, `Sklearn` fnction` linear_model.linearregression () `kaa upyog data ko ek pratigaman line main feet karne ke liye kiya jaataa he, jise graph par bhavishyavaanee kii jaati he or plot kiya jaataa he.`Plt.show ()` line antim graph pradarshit karti he.</s>
